Sparse Differential Resultant for Laurent Differential Polynomials
DOI: 10.1007/s10208-015-9249-9
© The Author(s) 2015
Received: 11 September 2012
Accepted: 8 January 2015
Published: 18 February 2015
Abstract
In this paper, we first introduce the concept of Laurent differentially essential systems and give a criterion for a Laurent differential polynomial system to be Laurent differentially essential in terms of its support matrix. Then, the sparse differential resultant for a Laurent differentially essential system is defined, and its basic properties are proved. In particular, order and degree bounds for the sparse differential resultant are given. Based on these bounds, an algorithm to compute the sparse differential resultant is proposed, which is single exponential in terms of the Jacobi number and the size of the system.
Keywords
Sparse differential resultant Jacobi number Poisson product formula Differential toric variety BKK bound Single exponential algorithmMathematics Subject Classification
Primary 12H05 68W30 Secondary 14M25 14Q991 Introduction
The multivariate resultant, which gives conditions for an overdetermined system of polynomial equations to have common solutions, is a basic concept in algebraic geometry [13, 19, 27, 45]. In recent years, the multivariate resultant has emerged as one of the most powerful computational tools in elimination theory due to its ability to eliminate several variables simultaneously without introducing many extraneous solutions. Many algorithms with best complexity bounds for problems such as polynomial equation solving and first-order quantifier elimination are strongly based on the multivariate resultant [4, 5, 15, 16, 26, 38].
In the theory of multivariate resultants, polynomials are assumed to involve all the monomials with degrees up to a given bound. In practical problems, most polynomials are sparse in that they only contain certain fixed monomials. For such sparse polynomials, the multivariate resultant often becomes identically zero and cannot provide any useful information.
As a major advance in algebraic geometry and elimination theory, the concept of sparse resultant was introduced by Gelfand, Kapranov, Sturmfels, and Zelevinsky [19, 45]. The degree of the sparse resultant is the Bernstein–Kushnirenko–Khovanskii (BKK) bound [2] instead of the Beźout bound [19, 37, 46], which makes the computation of the sparse resultant more efficient. The concept of sparse resultants originated from the work of Gelfand et al. [18] on generalized hypergeometric functions, where the central concept of \(\mathcal {A}\)-discriminant is studied. Kapranov et al. [28] introduced the concept of \(\mathcal {A}\)-resultant. Sturmfels further introduced the general mixed sparse resultant and gave a single exponential algorithm to compute the sparse resultant [45, 46]. Canny and Emiris showed that the sparse resultant is a factor of the determinant of a Macaulay style matrix and gave an efficient algorithm to compute the sparse resultant based on this matrix representation [14, 15]. D’Andrea further proved that the sparse resultant is the quotient of two Macaulay style determinants [11]. The representation given in [11] is used to develop efficient algorithms for computing sparse resultants [16].
Using the analog between ordinary differential operators and univariate polynomials, the differential resultant for two linear ordinary differential operators was implicitly given by Ore [36] and then studied by Berkovich and Tsirulik [1] using Sylvester style matrices. The subresultant theory was first studied by Chardin [7] for two differential operators and then by Li [35] and Hong [24] for the more general Ore polynomials.
For nonlinear differential polynomials, it is more difficult to define and study the differential resultant. The differential resultant for two nonlinear differential polynomials in one variable was defined by Ritt [41, p. 47]. In [50, p. 46], Zwillinger proposed to define the differential resultant of two differential polynomials as the determinant of a matrix following the idea of algebraic multivariate resultants, but did not give details. General differential resultants were defined by Carrà-Ferro [6] using Macaulay’s definition of algebraic resultants. But, the treatment in [6] is not complete. For instance, the differential resultant for two generic differential polynomials with positive orders and degrees greater than one is always identically zero if using the definition in [6]. In [48], Yang, Zeng, and Zhang used the idea of algebraic Dixon resultant to compute the differential resultant. Although efficient, this approach is not complete, because it is not proved that the differential resultant can always be computed in this way. Differential resultants for linear ordinary differential polynomials were studied by Rueda–Sendra [43, 44]. In [17], a rigorous definition for the differential resultant of \(n+1\) differential polynomials in \(n\) variables was first presented and its properties were proved.
This paper, together with its preliminary version [34], initiates the study of the sparse differential resultant which is an extension of the sparse resultant and the differential resultant. In [34], we studied the sparse differential resultant for a system of differential polynomials with nonvanishing degree zero terms. For more general systems, our first observation is that the sparse differential resultant is closely connected with non-polynomial solutions of algebraic differential equations, that is, solutions with nonvanishing derivatives to any order. As a consequence, the sparse differential resultant should be more naturally defined for Laurent differential polynomials. This is similar to the algebraic sparse resultant [19, 46], where nonzero solutions of Laurent polynomials are considered.
The concept of Laurent differentially essential system is introduced, which is a necessary and sufficient condition for the existence of the sparse differential resultant. \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) are called Laurent differentially essential if \(\mathcal {I}_{{\mathbf {u}}}=\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}\cap {\mathbb Q}\{{\mathbf {u}}_0\ldots ,{\mathbf {u}}_n\}\) is a prime differential ideal of codimension one, where \(\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}=[{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n]\) is the differential ideal generated in the \({\mathbb {Y}}\)-Laurent differential polynomial ring \(\mathbb {Q}\{{\mathbb {Y}}^{\pm };{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). This concept is similar to (but weaker than) the concept of essential supports introduced by Sturmfels [46]. We have the following criteria for a Laurent differential polynomial system to be Laurent differentially essential.
Theorem 1.1
- 1) :
-
The differential transcendence degree of \({\mathbb Q}\langle {\mathbf {u}}_0\ldots ,{\mathbf {u}}_n\rangle \langle \frac{{\mathbb {P}}_0}{M_{00}},\ldots ,\frac{{\mathbb {P}}_n}{M_{n0}}\rangle \) over \({\mathbb Q}\langle {\mathbf {u}}_0\ldots ,{\mathbf {u}}_n\rangle \) is equal to \(\mathrm{rank}(\mathrm{{D}}_{\mathbb {P}})\).
- 2) :
-
Let \(\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}=[{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n]\subset \mathbb {Q}\{{\mathbb {Y}}^{\pm };{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). Then \(\mathcal {I}_{{\mathbf {u}}}=\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}\cap {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) is a prime differential ideal of codimension \(n+1-\mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}})\). So \(\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) is Laurent differentially essential if and only if \(\mathrm{rank}(\mathrm{{D}}_{\mathbb {P}})=n\).
- 3) :
-
\(\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) is Laurent differentially essential if and only if there exist \(k_i\,(i=0,\ldots ,n)\) with \(1\le k_i\le l_i\) such that \(\mathrm{rank}(\mathrm{{D}}_{k_0,\ldots ,k_n})=n\) where \(\mathrm{{D}}_{k_0,\ldots ,k_n}\) is the symbolic support matrix for the Laurent differential monomials \(M_{0k_0}/M_{00},\ldots , M_{nk_n}/M_{n0}\).
With the above theorem, computing the differential transcendence degree of certain differential polynomials is reduced to computing the rank of their symbolic support matrix. Similar to the case of linear equations, this result provides a useful tool to study generic differential polynomials. As an application of the above result, the differential dimension conjecture [42, p. 178] for a class of generic differential polynomials is proved.
If \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) in (1) are Laurent differentially essential, then \(\mathcal {I}_{\mathbf {u}}\) defined in Theorem 1.1 is a prime differential ideal of codimension one. Hence, there exists an irreducible differential polynomial \({\mathbf {R}}\in {\mathbb Q}\{{\mathbf {u}}_0\ldots ,{\mathbf {u}}_n\}\) such that \(\mathcal {I}_{\mathbf {u}}=\mathrm{sat}({\mathbf {R}})\) and \({\mathbf {R}}\) is defined to be the sparse differential resultant of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\). Properties of the sparse differential resultant are summarized in the following theorem.
Theorem 1.2
- 1) :
-
Let \(\mathcal {Z}({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n)\) be the set of all specializations of the coefficients \(u_{ik}\) of \({\mathbb {P}}_i\) under which \({\mathbb {P}}_i=0\,(i=0,\ldots ,n)\) have a common non-polynomial solution and \(\overline{\mathcal {Z}({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n)}\) the Kolchin differential closure of \(\mathcal {Z}({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n)\). Then \(\overline{\mathcal {Z}({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n)}={\mathbb {V}}\big (\mathrm{sat}({\mathbf {R}})\big )\).
- 2) :
-
\({\mathbf {R}}({\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n)\) is differentially homogenous in each \({\mathbf {u}}_i\,(i=0,\ldots ,n)\).
- 3) :
-
(Poisson product formula) Let \(h_0={\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_0)\ge 0\). Then \(t_0=\mathrm{deg}({\mathbf {R}},\) \(u_{00}^{(h_0)})\ge 1\) and there exist differential fields \((\mathbb {Q}_\tau ,\delta _\tau )\) and \(\xi _{\tau k}\in \mathbb {Q}_\tau \) for \(\tau =1,\ldots ,t_0\) and \(k=1,\ldots ,l_0\) such thatwhere \(A\) is a polynomial in \(\mathbb {Q}\langle {\mathbf {u}}_1,\ldots ,{\mathbf {u}}_n\rangle [{\mathbf {u}}_0^{[h_0]}\backslash u_{00}^{(h_0)}]\). Furthermore, if 1) every \(n\) of the \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) form a differentially independent set over \({\mathbb Q}\langle {\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\rangle \) and 2) for each \(j=1,\ldots ,n\), \(\mathbf e _j\in \hbox {Span}_{\mathbb {Z}}\{\alpha _{ik}-\alpha _{i0}:k=1,\ldots ,l_i;i=0,\ldots ,n\}\), then there exist \(\eta _{\tau k}\in {\mathbb Q}_\tau \) \((\tau =1,\ldots ,t_0;\,k=1,\ldots ,n)\) such that$$\begin{aligned} {\mathbf {R}}=A\prod _{\tau =1}^{t_0} \left( u_{00}+\sum \limits _{k=1}^{l_0} u_{0k}\xi _{\tau k}\right) ^{(h_0)},\end{aligned}$$where \(\eta _\tau =(\eta _{\tau 1},\ldots ,\eta _{\tau n})\) and \(\mathbf e _j\) is the exponent vector of \(y_j\). Moreover, \(\eta _\tau \,(\tau =1,\ldots ,t_0)\) are generic points of the prime differential ideal \([{\mathbb {P}}_1^\text {N},\ldots ,{\mathbb {P}}_n^\text {N}]\hbox {:}\mathbb {m}\) in \(\mathbb {Q}\langle {\mathbf {u}}_1,\ldots ,{\mathbf {u}}_n\rangle \{{\mathbb {Y}}\}\), where \(\mathbb {m}\) is the set of all differential monomials in \({\mathbb {Y}}\).$$\begin{aligned} {\mathbf {R}}&= A\prod _{\tau =1}^{t_0}\bigg [\frac{{\mathbb {P}}_0(\eta _\tau )}{M_{00}(\eta _\tau )}\bigg ]^{(h_0)}, \end{aligned}$$
- 4) :
-
Assume that \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) have the same monomial set \({\mathcal A}={\mathcal A}_i\,(i=0,\ldots ,n)\). The differential toric variety \(X_{\mathcal A}\) associated with \({\mathcal A}\) is defined and is shown to be an irreducible projective differential variety of dimension \(n\). Furthermore, the differential Chow form [17, 34] of \(X_{\mathcal A}\) is \({\mathbf {R}}\).
- 5) :
-
\(h_i = {\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\le \text {J}_i=\mathrm{Jac}(\widehat{{\mathbb {P}}}_{\hat{i}})\) for \(i=0,\ldots ,n\), where \(\widehat{{\mathbb {P}}}_{\hat{i}}=\{{\mathbb {P}}_0^\text {N},\ldots ,{\mathbb {P}}_n^\text {N}\}\backslash \{{\mathbb {P}}_i^\text {N}\}\).
- 6) :
-
\(\mathrm{deg}({\mathbf {R}})\le \prod _{i=0}^n (m_i+1)^{h_i+1}\le (m+1)^{\sum _{i=0}^n(\text {J}_i+1)}=(m+1)^{\text { J}+n+1}\), where \(m_i=\mathrm{deg}({\mathbb {P}}_i^\text {N},{\mathbb {Y}})\), \(m=\mathrm{max}_i\{m_i\}\), and \(\text { J} = \sum _{i=0}^n \text { J}_i\).
- 7) :
-
Let \({\mathrm{ord}}({\mathbb {P}}_i^\text {N},y_j)=e_{ij}\) and \(N_{i0}=M_i M_{i0}\). Then \({\mathbf {R}}\) has the following representationwhere \(G_{ij}\in {\mathbb Q}[{\mathbf {u}}_0^{[h_0]},\ldots ,{\mathbf {u}}_n^{[h_n]},y_1^{[t_1]},\ldots ,y_n^{[t_n]}]\) with \(t_j=\mathrm{max}_{i=0}^n\{h_i+e_{ij}\}\) such that \(\mathrm{deg}(G_{ij}({\mathbb {P}}_{i}^{\text {N}})^{(j)})\le [m+1+\sum _{i=0}^n(h_i+1)\mathrm{deg}(N_{i0})]\mathrm{deg}({\mathbf {R}})\).$$\begin{aligned} \prod _{i=0}^n N_{i0}^{(h_i+1)\mathrm{deg}({\mathbf {R}})}\cdot {\mathbf {R}}=\sum _{i=0}^n\sum _{j=0}^{h_i}G_{ij}\big ({\mathbb {P}}_{i}^\text {N}\big )^{(j)} \end{aligned}$$
Although similar to the properties of algebraic sparse resultants, each property given above is an essential extension of its algebraic counterpart. For instance, it needs lots of efforts to obtain the Poisson product formula. Property 5) is unique for the differential case and reflects the sparseness of the system in a certain sense.
Let \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) in (1) be generic differential polynomials such that all monomials with order \(\le s_i\) and degree \(\le m_i\) appear effectively in \({\mathbb {P}}_i\) and \({\mathbf {R}}({\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n)\) the differential resultant of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\). Then a BKK style degree bound is given:
Theorem 1.3
In principle, the sparse differential resultant can be computed with characteristic set methods for differential polynomials via symbolic computation [3, 8, 25, 42, 47]. But in general, differential elimination procedures based on characteristic sets do not have an elementary complexity bound [20].
Based on order and degree bounds given in (5)–(7) of Theorem 1.2, a single exponential algorithm to compute the sparse differential resultant \({\mathbf {R}}\) is proposed. The idea of the algorithm is to compute \({\mathbf {R}}\) with its order and degree increasing incrementally and to use linear algebra to find the coefficients of \({\mathbf {R}}\) with the given order and degree. The order and degree bounds serve as the termination condition. Precisely, we have
Theorem 1.4
The sparse differential resultant of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) can be computed with at most \(O\Big ( \big ((\text { J}+n+2)^{O(l \text { J}+l)}(m+1)^{O((l\text { J}+l)(\text { J}+n+2))}\big )/{n^{n}}\Big )\) \({\mathbb Q}\)-arithmetic operations, where \(l=\sum _{i=0}^n (l_i+1)\), \(m=\mathrm{max}_{i=0}^n m_i\), and \(\text { J}=\sum _{i=0}^n \text { J}_i\).
Since \(n<l\), the complexity of the algorithm is single exponential in terms of \(l\) and \(\text { J}\). The sparseness is reflected in the quantity \(l\) which is called the size of the system and the Jacobi number \(\text { J}\). Note that even for algebraic sparse resultants, the computational complexity is single exponential [15, 45]. This seems to be the first algorithm which eliminates several variables from nonlinear differential polynomials with a single exponential complexity.
As mentioned above, a preliminary version of this paper was reported in ISSAC 2011 [34], where the sparse differential resultant of differential polynomials with nonvanishing degree zero terms is studied. To be more precise, in [34], differential polynomials of the form (1) are required to satisfy that all \(M_{ik}\) are differential monomials and \(M_{i0}=1\) for each \(i=0,\ldots ,n\). There, (2), (3), (6), and (7) of Theorem 1.2 and Theorem 1.4 in that case are proved. In this paper, we consider sparse differential resultants for general Laurent differential polynomial systems. Moreover, Theorem 1.1, (1), (4), and (5) of Theorem 1.2, and Theorem 1.3 are newly studied here.
The rest of the paper is organized as follows. In Sect. 2, preliminary results are introduced. In Sect. 3, the sparse differential resultant for Laurent differentially essential systems is defined. In Sect. 4, Theorem 1.1 is proved. In Sect. 5, properties (1)–(4) of Theorem 1.2 are proved. In Sect. 6, properties 5)–7) of Theorem 1.2, Theorem 1.3, and Theorem 1.4 are proved. In Sect. 7, the paper is concluded and several unsolved problems for differential sparse resultant are proposed.
2 Preliminaries
In this section, some basic notations and preliminary results in differential algebra will be given. For more details about differential algebra, please refer to [3, 17, 29, 42].
2.1 Differential Polynomial Algebra and Kolchin Topology
Let \(\mathcal {F}\) be a fixed ordinary differential field of characteristic zero with a derivation operator \(\delta \). An element \(c\in \mathcal {F}\) such that \(\delta (c)=0\) is called a constant of \(\mathcal {F}.\) In this paper, unless otherwise indicated, \(\delta \) is kept fixed during any discussion and we use primes and exponents \((i)\) to indicate derivatives under \(\delta \). Let \(\Theta \) denote the free commutative semigroup with unit (written multiplicatively) generated by \(\delta \).
A typical example of differential fields is \(\mathbb {Q}(x)\) which is the field of rational functions in a variable \(x\) with \(\delta =\frac{d}{dx}\).
Let \(S\) be a subset of a differential field \(\mathcal {G}\) which contains \(\mathcal {F}\). We will denote, respectively, by \(\mathcal {F}[S]\), \(\mathcal {F}(S)\), \(\mathcal {F}\{S\}\), and \(\mathcal {F}\langle S\rangle \) the smallest subring, the smallest subfield, the smallest differential subring, and the smallest differential subfield of \(\mathcal {G}\) containing \(\mathcal {F}\) and \(S\). If we denote \(\Theta (S)\) to be the smallest subset of \(\mathcal {G}\) containing \(S\) and stable under \(\delta \), we have \(\mathcal {F}\{S\}=\mathcal {F}[\Theta (S)]\) and \(\mathcal {F}\langle S\rangle =\mathcal {F}(\Theta (S))\). A differential extension field \(\mathcal {G}\) of \(\mathcal {F}\) is said to be finitely generated if \(\mathcal {G}\) has a finite subset \(S\) such that \(\mathcal {G}=\mathcal {F}\langle S\rangle \).
A subset \(\Sigma \) of a differential extension field \(\mathcal {G}\) of \(\mathcal {F}\) is said to be differentially dependent over \(\mathcal {F}\) if the set \((\theta \alpha )_{\theta \in \Theta , \alpha \in \Sigma }\) is algebraically dependent over \(\mathcal {F}\), and otherwise, it is said to be differentially independent over \(\mathcal {F}\), or to be a family of differential indeterminates over \(\mathcal {F}\). In the case \(\Sigma \) consists of only one element \(\alpha \), we say that \(\alpha \) is differentially algebraic or differentially transcendental over \(\mathcal {F}\), respectively. A maximal subset \(\Omega \) of \(\mathcal {G}\) which is differentially independent over \(\mathcal {F}\) is said to be a differential transcendence basis of \(\mathcal {G}\) over \(\mathcal {F}\). We use \(\hbox {{d.tr.deg}}\,\mathcal {G}/\mathcal {F}\) (see [29, pp. 105–109]) to denote the differential transcendence degree of \(\mathcal {G}\) over \(\mathcal {F}\), which is the cardinal number of \(\Omega \). Considering \(\mathcal {F}\) and \(\mathcal {G}\) as purely algebraic fields, we denote the algebraic transcendence degree of \(\mathcal {G}\) over \(\mathcal {F}\) by \(\hbox {{tr.deg}}\,\mathcal {G}/\mathcal {F}\).
A homomorphism \(\varphi \) from a differential ring \((\mathcal {R},\delta )\) to a differential ring \((\mathcal {S},\delta _1)\) is a differential homomorphism if \(\varphi \circ \delta =\delta _1\circ \varphi \). If \(\mathcal {R}_0\) is a common differential subring of \(\mathcal {R}\) and \(\mathcal {S}\) and the homomorphism \(\varphi \) leaves every element of \(\mathcal {R}_0\) invariant, then \(\varphi \) is said to be a homomorphism over \(\mathcal {R}_0\). If, in addition, \(\mathcal {R}\) is an integral domain and \(\mathcal {S}\) is a differential field, \(\varphi \) is called a differential specialization of \(\mathcal {R}\) into \(\mathcal {S}\) over \(R_0\). The following property about differential specialization will be needed in this paper, and it can be proved similarly to [17, Theorem 2.16].
Lemma 2.1
Let \(P_{i}({\mathbb {U}}, {\mathbb {Y}})\in \mathcal {F}\langle {\mathbb {Y}}\rangle \{{\mathbb {U}}\}\) \((i=1, \ldots , m)\) where \({\mathbb {U}}\) and \({\mathbb {Y}}\) are sets of differential indeterminates. If \(\theta _{ij}\big (P_{i}({\mathbb {U}}, {\mathbb {Y}})\big )\,(i=1, \ldots , m; j=1,\ldots ,n_{i})\) are algebraically dependent over \(\mathcal {F}\langle {\mathbb {U}}\rangle \) for \(\theta _{ij}\in \Theta \), then for any differential specialization \({\mathbb {U}}^0\subset \mathcal {F}\) of \({\mathbb {U}}\) over \(\mathcal {F}\), \(\theta _{ij}\big (P_{i}({\mathbb {U}}^0, {\mathbb {Y}})\big )\) are algebraically dependent over \(\mathcal {F}\). In particular, if \(P_{i}({\mathbb {U}}, {\mathbb {Y}})\) \((i=1, \ldots , m)\) are differentially dependent over \(\mathcal {F}\langle {\mathbb {U}}\rangle \), then for any differential specialization \({\mathbb {U}}^0\subset \mathcal {F}\) of \({\mathbb {U}}\) over \({\mathcal {F}}\), \(P_{i}({\mathbb {U}}^0,{\mathbb {Y}})\) are differentially dependent over \(\mathcal {F}\).
A differential extension field \(\mathcal {E}\) of \(\mathcal {F}\) is called a universal differential extension field, if for any finitely generated differential extension field \(\mathcal {F}_1\subset \mathcal {E}\) of \(\mathcal {F}\) and any finitely generated differential extension field \(\mathcal {F}_2\) of \(\mathcal {F}_1\) not necessarily in \(\mathcal {E}\), \(\mathcal {F}_2\) can be embedded in \(\mathcal {E}\) over \(\mathcal {F}_1\), i.e., there exists a differential extension field \(\mathcal {F}_3\) in \(\mathcal {E}\) that is differentially isomorphic to \(\mathcal {F}_2\) over \(\mathcal {F}_1\). Such a differential universal extension field of \(\mathcal {F}\) always exists [29, Theorem 2, p. 134]. By definition, any finitely generated differential extension field of \(\mathcal {F}\) can be embedded over \(\mathcal {F}\) into \(\mathcal {E}\), and \(\mathcal {E}\) is a universal differential extension field of every finitely generated differential extension field of \(\mathcal {F}\). In particular, for any natural number \(n\), we can find in \(\mathcal {E}\) a subset of cardinality \(n\) whose elements are differentially independent over \(\mathcal {F}.\) Throughout the present paper, \(\mathcal {E}\) stands for a fixed universal differential extension field of \(\mathcal {F}\).
Now suppose \({\mathbb {Y}}=\{y_{1}, y_{2}, \ldots , y_{n}\}\) is a set of differential indeterminates over \(\mathcal {E}\). For any \(y\in {\mathbb {Y}}\), denote \(\delta ^ky\) by \(y^{(k)}.\) The elements of \(\mathcal {F}\{{\mathbb {Y}}\}=\mathcal {F}[y_j^{(k)}\,|\,j=1,\ldots ,n;k\in \mathbb {N}]\) are called differential polynomials over \(\mathcal {F}\) in \({\mathbb {Y}}\), and \(\mathcal {F}\{{\mathbb {Y}}\}\) itself is called the differential polynomial ring over \(\mathcal {F}\) in \({\mathbb {Y}}\). A differential polynomial ideal \(\mathcal {I}\) in \(\mathcal {F}\{{\mathbb {Y}}\}\) is an ordinary algebraic ideal which is closed under derivation, i.e., \(\delta (\mathcal {I})\subset \mathcal {I}\). And a prime (resp. radical) differential ideal is a differential ideal which is prime (resp. radical) as an ordinary algebraic polynomial ideal. For convenience, a prime differential ideal is assumed not to be the unit ideal in this paper.
By a differential affine space, we mean any one of the sets \(\mathcal {E}^n\,(n\in \mathbb {N}).\) An element \(\eta =(\eta _1,\ldots ,\eta _n)\) of \(\mathcal {E}^n\) will be called a point. Let \(\Sigma \) be a subset of differential polynomials in \(\mathcal {F}\{{\mathbb {Y}}\}\). A point \(\eta =(\eta _{1},\ldots ,\eta _{n}) \in \mathcal {E}^n\) is called a differential zero of \(\Sigma \) if \(f(\eta )=0\) for any \(f \in \Sigma \). The set of differential zeros of \(\Sigma \) is denoted by \(\mathbb {V}(\Sigma )\), which is called a differential variety defined over \(\mathcal {F}\). When the base field is clear from the context, we simply call it a differential variety. The differential varieties in \(\mathcal {E}^n\) (resp. the differential varieties in \(\mathcal {E}^n\) that are defined over \(\mathcal {F}\)) are the closed sets in a topology called the Kolchin topology (resp. the Kolchin \(\mathcal {F}\)-topology).
For \(V\subset \mathcal {E}^n\), let \(\mathbb {I}(V)\) be the set of all differential polynomials in \(\mathcal {F}\{{\mathbb {Y}}\}\) that vanish at every point of \(V\). Clearly, \(\mathbb {I}(V)\) is a radical differential ideal in \(\mathcal {F}\{{\mathbb {Y}}\}\). By the differential Nullstellensatz, there exists a bijective correspondence between Kolchin \(\mathcal {F}\)-closed sets and radical differential ideals in \(\mathcal {F}\{{\mathbb {Y}}\}\). That is, for any differential variety \(V\) defined over \(\mathcal {F}\), \(\mathbb {V}(\mathbb {I}(V))=V\) and for any radical differential ideal \(\mathcal {I}\) in \(\mathcal {F}\{{\mathbb {Y}}\}\), \(\mathbb {I}(\mathbb {V}(\mathcal {I}))=\mathcal {I}\).
Similarly as in algebraic geometry, an \(\mathcal {F}\)-irreducible differential variety can be defined. And there is a bijective correspondence between \(\mathcal {F}\)-irreducible differential varieties and prime differential ideals in \(\mathcal {F}\{{\mathbb {Y}}\}\). A point \(\eta \in {\mathbb {V}}({\mathcal {I}})\) is called a generic point of a prime ideal \({\mathcal {I}}\subset \mathcal {F}\{{\mathbb {Y}}\}\), or of the irreducible variety \({\mathbb {V}}({\mathcal {I}})\), if for any polynomial \(P\in \mathcal {F}\{{\mathbb {Y}}\}\) we have \(P(\eta )=0 \Leftrightarrow P\in {\mathcal {I}}\). It is well known that [42, p. 27] a non-unit differential ideal is prime if and only if it has a generic point. Notice that irreducibility depends on the base field over which the polynomials are defined. In this paper, to emphasize the differential ring where differential ideals are generated, we use the notation \(\mathcal {I}_{\mathcal {F}\{{\mathbb {Y}}\}}\) or \((\mathcal {I})_{\mathcal {F}\{{\mathbb {Y}}\}}\)to mean that \(\mathcal {I}\) is a differential ideal in \(\mathcal {F}\{{\mathbb {Y}}\}\).
Let \(\mathcal {I}\) be a prime differential ideal in \(\mathcal {F}\{{\mathbb {Y}}\}\) and \(\xi =(\xi _{1},\ldots ,\xi _{n})\) a generic point of \(\mathcal {I}\) [29, p. 19]. The dimension of \(\mathcal {I}\) or of \(\mathbb {V}(\mathcal {I})\) is defined to be the differential transcendence degree of the differential extension field \(\mathcal {F}\langle \xi _{1},\ldots ,\xi _{n}\rangle \) over \(\mathcal {F}\), that is, \(\hbox {{dim}}(\mathcal {I})=\hbox {{d.tr.deg}}\, \mathcal {F}\langle \xi _{1},\ldots ,\xi _{n}\rangle /\mathcal {F}\).
We will conclude this section by introducing some basic concepts in projective differential algebraic geometry which will be used in Sect. 5.4. For more details, please refer to [31, 33]. And unless otherwise stated, in the whole paper, we only consider the affine differential case.
For each \(l\in \mathbb {N}\), consider a projective space \(\mathbf P (l)\) over \(\mathcal {E}\). By a differential projective space, we mean any one of the sets \(\mathbf P (l)\,(l\in \mathbb {N}).\) Denote \(z_0,z_1,\ldots ,z_l\) to be the homogenous coordinates and \({\mathbf {z}}=\{z_0,z_1,\ldots ,z_l\}\).
Definition 2.2
Let \(\mathcal {I}\) be a differential ideal of \(\mathcal {F}\{{\mathbf {z}}\}\) and \(\mathcal {I}\hbox {{:}}{\mathbf {z}}=\{f\in \mathcal {F}\{{\mathbf {z}}\}|\,z_jf\in \mathcal {I}, j=0,\ldots ,l\}\). Call \(\mathcal {I}\) a differentially homogenous differential ideal of \(\mathcal {F}\{{\mathbf {z}}\}\) if \(\mathcal {I}\hbox {{:}}{\mathbf {z}}=\mathcal {I}\) and for every \(P\in \mathcal {I}\) and a differential indeterminate \(\lambda \) over \(\mathcal {F}\{{\mathbf {z}}\}\), \(P(\lambda {\mathbf {z}})\in \mathcal {F}\{\lambda \}\mathcal {I}\) in \(\mathcal {F}\{\lambda ,{\mathbf {z}}\}\).
Consider a differential polynomial \(P\in \mathcal {F}\{{\mathbf {z}}\}\) and a point \(\alpha \in \mathbf P (l)\). Say that \(P\) vanishes at \(\alpha \) and that \(\alpha \) is a zero of \(P\), if \(P\) vanishes at \(\lambda \alpha \) for every \(\lambda \) in \(\mathcal {E}\). For a subset \(\fancyscript{M}\) of \(\mathbf P (l)\), let \(\mathbb {I}(\fancyscript{M})\) denote the set of all differential polynomials in \(\mathcal {F}\{{\mathbf {z}}\}\) that vanish at \(\fancyscript{M}\). Let \({\mathbb {V}}(S)\) denote the set of points of \(\mathbf P (l)\) that are zeros of the subset \(S\) of \(\mathcal {F}\{{\mathbf {z}}\}\). And a subset \(V\subset \mathbf P (l)\) is called a projective differential \(\mathcal {F}\) -variety if there exists \(S\subset \mathcal {F}\{{\mathbf {z}}\}\) such that \(V={\mathbb {V}}(S)\). There exists a one-to-one correspondence between projective differential varieties and radical differentially homogenous differential ideals. And a projective differential \(\mathcal {F}\)-variety \( V\) is \(\mathcal {F}\)-irreducible if and only if \(\mathbb {I}(V)\) is prime.
Let \(\mathcal {I}\) be a prime differentially homogenous ideal and \(\xi =(\xi _0,\xi _1,\ldots ,\xi _l)\) be a generic point of \(\mathcal {I}\) with \(\xi _0\ne 0\). Then the differential dimension of \({\mathbb {V}}(\mathcal {I})\) is defined to be the differential transcendence degree of \(\mathcal {F}\langle (\xi _0^{-1}\xi _k)_{1\le k\le l}\rangle \) over \(\mathcal {F}\).
2.2 Characteristic Sets of a Differential Polynomial System
Let \(f\) be a differential polynomial in \(\mathcal {F}\{{\mathbb {Y}}\}\). We define the order of \(f\) w.r.t. \(y_i\) to be the greatest number \(k\) such that \(y_{i}^{(k)}\) appears effectively in \(f\), which is denoted by \({\mathrm{ord}}(f,y_{i})\). And if \(y_{i}\) does not appear in \(f\), then we set \({\mathrm{ord}}(f,y_{i})=-\infty \). The order of \(f\) is defined to be \(\mathrm{max}_{i}\,{\mathrm{ord}}(f,y_{i})\), that is, \({\mathrm{ord}}(f)=\mathrm{max}_{i}\,{\mathrm{ord}}(f,y_{i})\).
- 1)
\(\delta \theta y_{j} >\theta y_{j}\) for all derivatives \(\theta y_{j}\in \Theta ({\mathbb {Y}})\).
- 2)
\(\theta _{1} y_{i} >\theta _{2} y_{j}\) \(\Longrightarrow \) \(\delta \theta _{1} y_{i} >\delta \theta _{2} y_{j}\) for \(\theta _{1} y_{i}, \theta _{2} y_{j}\in \Theta ({\mathbb {Y}})\).
- 1)
Elimination ranking: \(y_{i} > y_{j}\) \(\Longrightarrow \) \(\delta ^{k} y_{i} >\delta ^{l} y_{j}\) for any \(k, l\ge 0\).
- 2)
Orderly ranking: \(k>l\) \(\Longrightarrow \) \(\delta ^{k} y_{i} >\delta ^{l} y_{j}\), for any \(i, j \in \{1, 2, \ldots , n\}\).
Let \(f\) and \(g\) be two differential polynomials and \(\hbox {{rk}}(f)=u_{f}^{d}\). Then \(g\) is said to be partially reduced w.r.t. \(f\) if no proper derivatives of \(u_{f}\) appear in \(g\). And \(g\) is said to be reduced w.r.t. \(f\) if \(g\) is partially reduced w.r.t. \(f\) and \(\mathrm{deg}(g,u_{f})<d\). A set of differential polynomials \(\mathcal {A}\) is said to be an auto-reduced set if each polynomial of \(\mathcal {A}\) is reduced w.r.t. any other element of \(\mathcal {A}\). Every auto-reduced set is finite.
In terms of characteristic sets, the cardinal number of a characteristic set of \(\mathcal {I}\) is equal to the codimension of \(\mathcal {I}\), that is, \(n-\hbox {{dim}}(\mathcal {I})\). When \(\mathcal {I}\) is of codimension one, it has the following property.
Lemma 2.3
[42, p. 45] Let \(\mathcal {I}\) be a prime differential ideal of codimension one in \(\mathcal {F}\{{\mathbb {Y}}\}\). Then there exists an irreducible differential polynomial \(A\) such that \(\mathcal {I}=\mathrm{sat}(A)\) and \(\{A\}\) is the characteristic set of \(\mathcal {I}\) w.r.t. any ranking.
3 Sparse Differential Resultants for Laurent Differential Polynomials
In this section, the concepts of Laurent differential polynomial and Laurent differentially essential system are first introduced, and then the sparse differential resultant for a Laurent differentially essential system is defined.
3.1 Laurent Differential Polynomials
Let \({\mathcal {F}}\) be an ordinary differential field with a derivation operator \(\delta \) and \({\mathcal {F}}\{{\mathbb {Y}}\}\) the ring of differential polynomials in the differential indeterminates \({\mathbb {Y}}=\{y_1,\ldots ,y_n\}\). Let \(\mathcal {E}\) be a universal differential extension field of \(\mathcal {F}\). For any element \(e\in \mathcal {E}\), \(e^{[k]}\) denotes the set \(\{e^{(0)},\ldots ,e^{(k)}\}\).
The sparse differential resultant is closely related to Laurent differential polynomials, which will be defined below.
Definition 3.1
A Laurent differential monomial of order \(s\in {\mathbb N}\) is a Laurent monomial in variables \({\mathbb {Y}}^{[s]}=(y_i^{(k)})_{1\le i\le n;0\le k\le s}\). More precisely, it has the form \(\prod _{i=1}^n\prod _{k=0}^s(y_i^{(k)})^{m_{ik}}\), where \(m_{ik}\) are integers which can be negative. A Laurent differential polynomial is a finite linear combination of Laurent differential monomials with coefficients from \(\mathcal {E}\).
Clearly, the collection of all Laurent differential polynomials forms a commutative differential ring under the obvious sum and product operations and the usual derivation operator \(\delta \), where all Laurent differential monomials are invertible. We denote the differential ring of Laurent differential polynomials with coefficients in \(\mathcal {F}\) by \(\mathcal {F}\{y_1,y_1^{-1},\ldots ,y_n,y_n^{-1}\}\), or simply by \(\mathcal {F}\{{\mathbb {Y}}^{\pm }\}\).
Remark 3.2
\(\mathcal {F}\{{\mathbb {Y}}^{\pm }\}=\mathcal {F}\{y_1,y_1^{-1},\ldots ,y_n,y_n^{-1}\}\) is only a notation for Laurent differential polynomial ring. It is not equal to \(\mathcal {F}[y_{i}^{(k)},(y_{i}^{-1})^{(k)}\,|\,k\ge 0]\).
-
Given \(\mathcal {I}=[F_1,\ldots ,F_s]_{ \mathcal {F}\{{\mathbb {Y}}^{\pm }\}} \in \mathcal {S}\). Since each \(F_i\in \mathcal {F}\{{\mathbb {Y}}^{\pm }\}\), a vector \((M_1,\ldots ,M_s)\in \mathbb {m}^s \) can be chosen such that each \(M_iF_i\in \mathcal {F}\{{\mathbb {Y}}\}\). We then define \(\phi (\mathcal {I})\mathop {=}\limits ^{\triangle }([M_1F_1,\ldots ,M_sF_s]\hbox {{:}}\mathbb {m})_{\mathcal {F}\{{\mathbb {Y}}\}}\).
-
Given \(\mathcal {J}=([f_1,\ldots ,f_r]\hbox {{:}}\mathbb {m})_{_{\mathcal {F}\{{\mathbb {Y}}\}}}\in \mathcal {T}\), define \(\psi (\mathcal {J})=[f_1,\ldots ,f_r]_{\mathcal {F}\{{\mathbb {Y}}^{\pm }\}}\).
Lemma 3.3
The above maps \(\phi \) and \(\psi \) are well defined. Moreover, \(\phi \circ \psi =\text { id}_{\mathcal {T}}\) and \(\psi \circ \phi =\text { id}_{\mathcal {S}}\).
Proof
\(\psi \) is obviously well defined. To show that \(\phi \) is well defined, it suffices to show that given another \((N_1,\ldots ,N_s)\in \mathbb {m}^s\) with \(N_iF_i\in \mathcal {F}\{{\mathbb {Y}}\}\,(i=0,\ldots ,n)\), \(([M_1F_1,\ldots ,M_sF_s]\hbox {{:}}\mathbb {m})_{\mathcal {F}\{{\mathbb {Y}}\}}=([N_1F_1,\ldots ,N_sF_s]\hbox {{:}}\mathbb {m})_{\mathcal {F}\{{\mathbb {Y}}\}}\). It follows from the fact that \(N_iF_i\in ([M_1F_1,\ldots ,M_sF_s]\hbox {{:}}\mathbb {m})_{\mathcal {F}\{{\mathbb {Y}}\}}\) and \(M_iF_i\in ([N_1F_1,\ldots ,N_sF_s]\hbox {{:}}\mathbb {m})_{\mathcal {F}\{{\mathbb {Y}}\}}\). For each \(\mathcal {I}=[F_1,\ldots ,F_s]_{ \mathcal {F}\{{\mathbb {Y}}^{\pm }\}}\in \mathcal {S}\), \(\psi \circ \phi (\mathcal {I})=\psi (([M_1F_1,\ldots ,\) \(M_sF_s]\hbox {{:}}\mathbb {m})_{ \mathcal {F}\{{\mathbb {Y}}\}})=[M_1F_1,\ldots ,M_sF_s]_{ \mathcal {F}\{{\mathbb {Y}}^{\pm }\}}= \mathcal {I}\) where \(M_iF_i\in \mathcal {F}\{{\mathbb {Y}}\}\). So we have \(\psi \circ \phi =\text { id}_{\mathcal {S}}\). And for each \(\mathcal {J}=([f_1,\ldots ,f_r]\hbox {{:}}\mathbb {m})_{ \mathcal {F}\{{\mathbb {Y}}\}}\in \mathcal {T}\), \(\phi \circ \psi (\mathcal {J})=\phi ([f_1,\ldots ,f_r]_{ \mathcal {F}\{{\mathbb {Y}}^{\pm }\}})=\mathcal {J}\). Thus, \(\phi \circ \psi =\text { id}_{\mathcal {T}}\) follows. \(\square \)
From the above, for a finitely generated Laurent differential ideal \(\mathcal {I}=[F_1,\ldots ,F_s]_{\mathcal {F}\{{\mathbb {Y}}^{\pm }\}}\in \mathcal {S}\), although \(\phi (\mathcal {I})\) is unique, different vectors \((M_1,\ldots ,M_s)\in \mathbb {m}^s\) can be chosen to give different representations for \(\phi (\mathcal {I})\). Now the norm form for a Laurent differential polynomial is introduced to fix the choice of \((M_1,\ldots ,M_s)\in \mathbb {m}^s\) when we consider \(\phi (\mathcal {I})\).
Definition 3.4
For every Laurent differential polynomial \(F\in \mathcal {E}\{{\mathbb {Y}}^{\pm }\}\), there exists a unique Laurent differential monomial \(M\) such that (1) \(M\cdot F\in \mathcal {E}\{{\mathbb {Y}}\}\) and (2) for any Laurent differential monomial \(T\) with \(T\cdot F\in \mathcal {E}\{{\mathbb {Y}}\}\), \(T\cdot F\) is divisible by \(M\cdot F\) as differential polynomials. This \(M\cdot F\) is defined to be the norm form of \(F\), denoted by \(F^{\text {N}}\). The order of \(F^{\text {N}}\) is defined to be the effective order of F, denoted by \(\hbox {{Eord}}(F)\). Clearly, \(\hbox {{Eord}}(F)\le {\mathrm{ord}}(F)\). And the degree of \(F\) is defined to be the degree of \(F^{\text {N}}\), denoted by \(\mathrm{deg}(F)\).
In the following, we consider zeros for Laurent differential polynomials.
Definition 3.5
Let \(\mathcal {E}^{\wedge }=\mathcal {E}\backslash \{a\in \mathcal {E}\big |\,\exists k\in \mathbb {N}, \,\text { s.t.}\, a^{(k)}=0 \}\). Let \(F\) be a Laurent differential polynomial in \(\mathcal {F}\{{\mathbb {Y}}^{\pm }\}\). A point \((a_1,\ldots ,a_n)\in (\mathcal {E}^{\wedge })^n\) is called a non-polynomial differential zero of \(F\) if \(F(a_1,\ldots ,a_n)=0.\)
It becomes apparent why non-polynomial elements in \(\mathcal {E}^{\wedge }\) are considered as zeros of Laurent differential polynomials when defining the zero set of an ideal. If \(F\in \mathcal {I}\), then \((y_i^{(k)})^{-1}F\in \mathcal {I}\) for any positive integer \(k\), and in order for \((y_i^{(k)})^{-1}F\) to be meaningful, we need to assume \(y_i^{(k)}\ne 0\). We will see later in Example 5.2 how non-polynomial solutions are naturally related to the sparse differential resultant.
3.2 Definition of Sparse Differential Resultant
In this section, the definition of the sparse differential resultant will be given. Since the study of sparse differential resultants becomes more transparent if we consider not individual differential polynomials but differential polynomials with indeterminate coefficients, the sparse differential resultant for Laurent differential polynomials with differential indeterminate coefficients will be defined first. Then the sparse differential resultant for a given Laurent differential polynomial system with concrete coefficients is the value that the generic resultant takes for the coefficients of the given system.
Definition 3.6
A set of Laurent differential polynomials of the form (3) is said to be a Laurent differentially essential system if there exist \(k_i\,(i=0,\ldots ,n)\) with \(1\le k_i\le l_i\) such that \(\hbox {{d.tr.deg}}\,\mathbb {Q}\langle \frac{M_{0k_0}}{M_{00}},\) \(\frac{M_{1k_1}}{M_{10}},\ldots ,\frac{M_{nk_n}}{M_{n0}}\rangle /\mathbb {Q}=n.\) In this case, we also say that \(\mathcal {A}_0,\ldots ,\mathcal {A}_n\) or \({\mathbb {S}}_0,\ldots ,\) \({\mathbb {S}}_n\) form a Laurent differentially essential system.
Although \(M_{i0}\) are used as denominators to define Laurent differentially essential systems, the following lemma shows that the definition does not depend on the choice of \(M_{i0}\).
Lemma 3.7
- 1.
There exist \(k_0,\ldots ,k_n\) with \(1\le k_i\le l_i\) such that \(\mathrm{d.tr.deg}\,\mathbb {Q}\langle \frac{M_{0k_0}}{M_{00}},\ldots ,\frac{M_{nk_n}}{M_{n0}}\rangle /\mathbb {Q}=n.\)
- 2.
There exist pairs \((k_i,j_i)\,(i=0,\ldots ,n)\) with \(k_i\ne j_i\in \{0,\ldots ,l_i\}\) such that\(\mathrm{d.tr.deg}\,\mathbb {Q}\langle \frac{M_{0k_0}}{M_{0j_0}},\) \(\ldots ,\frac{M_{nk_n}}{M_{nj_n}}\rangle /\mathbb {Q}=n.\)
Proof
It is trivial that 1) implies 2). For the other direction, assume 2) holds. Without loss of generality, suppose \(\frac{M_{1k_1}}{M_{1j_1}},\ldots ,\frac{M_{nk_n}}{M_{nj_n}} \) are differentially independent over \(\mathbb {Q}\). We need to show (1) holds. Suppose the contrary, then for any \(m_i\in \{1,\ldots ,l_{i}\}\), \(\frac{M_{1m_1}}{M_{10}},\ldots ,\frac{M_{nm_n}}{M_{n0}}\) are differentially dependent over \({\mathbb Q}\). Now we claim that \((*)\) suppose for each \(i\in \{1,2\}\), \(a\) and \(b_i\) are differentially dependent over \(\mathbb {Q}\), then \(a\) and \(b_1/b_2\) are differentially dependent over \(\mathbb {Q}\). Indeed, if \(a\) is differentially algebraic over \(\mathbb {Q}\), then \((*)\) follows. If \(a\) is differentially transcendental over \(\mathbb {Q}\), then each \(b_i\) is differentially algebraic over \(\mathbb {Q}\langle a\rangle \). Thus, \(b_1/b_2\) is differentially algebraic over \(\mathbb {Q}\langle a\rangle \) [29, p. 102] and the claim is proved. Since \(\frac{M_{ik_i}}{M_{ij_i}}=\frac{M_{ik_i}}{M_{i0}}\big /\frac{M_{ij_i}}{M_{i0}}\), by claim \((*)\), \(\frac{M_{ik_i}}{M_{ij_i}}\,(i=1,\ldots ,n)\) are differentially dependent over \({\mathbb Q}\), which leads to a contradiction. \(\square \)
Lemma 3.8
\(\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}=\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\).
Proof
It is obvious that the right elimination ideal is contained in the left one. For the other direction, let \(G\) be any element in the left ideal. Then there exist \(H_{ij}\in \mathbb {Q}\{{\mathbb {Y}}^{\pm };{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) such that \(G=\sum _{i,j}H_{ij}{\mathbb {P}}_i^{(j)}\). So \(G=\sum _{i,j}H_{ij}\big (\frac{{\mathbb {P}}_i^{\text {N}}}{M_i}\big )^{(j)}=\sum _{i,j}\widetilde{H}_{ij}\big ({\mathbb {P}}_i^{\text {N}}\big )^{(j)}\) with \(\widetilde{H}_{ij}\in \mathbb {Q}\{{\mathbb {Y}}^{\pm };{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). Thus, there exists an \(M\in \mathbb {m}\) such that \(MG\in [{\mathbb {P}}_0^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]_{\mathbb {Q}\{{\mathbb {Y}},{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}}\) and \(G\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) follows. \(\square \)
Theorem 3.9
- 1) :
-
\(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is a prime differential ideal in \({\mathbb Q}\{{\mathbb {Y}};{\mathbf {u}}_0,\) \(\ldots ,{\mathbf {u}}_n\}\) with \(\theta \) given in (9) as a generic point.
- 2) :
-
The prime differential ideal \(\mathcal {I}_{\mathbf {u}}=\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) is of codimension one if and only if \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) form a Laurent differentially essential system.
Proof
To prove 1), it suffices to show that \(\theta =(\eta ;\zeta )\) is a generic point of \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Clearly, \({\mathbb {P}}_i^{\text {N}}=M_i{\mathbb {P}}_i\) vanishes at \(\theta \) \((i=0,\ldots ,n)\). For any \(f\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\), there exists an \(M\in \mathbb {m}\) such that \(Mf\in [{\mathbb {P}}_0^{\text {N}},{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]_{{\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}}\). It follows that \(f(\theta )=0\). Conversely, let \(f\) be any differential polynomial in \({\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) satisfying \(f(\theta )=0\). Clearly, \({\mathbb {P}}_0^{\text {N}},{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}\) constitute an auto-reduced set with \(u_{i0}\) as leaders. Let \(f_1\) be the differential remainder of \(f\) w.r.t. this auto-reduced set. Since \({\mathbb {P}}_i^\text {N}\) is linear in \(u_{i0}\), \(f_1\) is free from \(u_{i0}\,(i=0,\ldots ,n)\). By (2), there exist \(k_i\ge 0\) such that \(\prod _{i=0}^n(N_{i0})^{k_i}\cdot f\equiv f_1,\mathrm{{mod}}\,[{\mathbb {P}}_0^{\text {N}},{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]\). Hence, \(f_1(\theta )=0\). Since \(f_1\in {\mathbb Q}\{{\mathbf {u}},{\mathbb {Y}}\}\), \(f_1(\theta )=f_1(\eta ,{\mathbf {u}})=0\) means \(f_1=0\). Thus, \(f\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). So \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is a prime differential ideal with \(\theta \) as its generic point.
Consequently, \(\mathcal {I}_{\mathbf {u}}=\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) is a prime differential ideal with a generic point \(\zeta =(\zeta _0,u_{01},\ldots ,u_{0l_0};\ldots ;\zeta _n,u_{n1},\ldots ,u_{nl_n})\). From (9), it is clear that \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \zeta \rangle /{\mathbb Q}\) \(\le \sum _{i=0}^nl_i+n\). Suppose \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) form a Laurent differentially essential system, that is, there exist pairs \((i_k,j_k)\) \((k=1,\ldots ,n)\) with \(1\le j_k\le l_{i_k}\) and \(i_{k_1}\ne i_{k_2}\) \((k_1\ne k_2)\) such that \(\frac{N_{i_1j_1}}{N_{i_10}},\ldots ,\frac{N_{i_nj_n}}{N_{i_n0}}\) are differentially independent over \({\mathbb Q}\). Then by Lemma 2.1, \(\zeta _{i_1},\ldots ,\zeta _{i_n}\) are differentially independent over \({\mathbb Q}\langle {\mathbf {u}}\rangle \). For if not, by specializing \(u_{i_kj_k}\) to \(-1\) and the other \({\mathbf {u}}\) to \(0\), Lemma 2.1 guarantees that \(\frac{N_{i_1j_1}}{N_{i_10}},\ldots ,\frac{N_{i_nj_n}}{N_{i_n0}}\) are differentially dependent over \({\mathbb Q}\), a contradiction. Then it follows that \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \zeta \rangle /{\mathbb Q}= \sum _{i=0}^nl_i+n\). Thus, \(\mathcal {I}_{\mathbf {u}}\) is of codimension 1.
Conversely, assume that \(\mathcal {I}_{\mathbf {u}}\) is of codimension 1. That is, \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \zeta \rangle /{\mathbb Q}= \sum _{i=0}^nl_i+n\). We need to show that there exist pairs \((i_k,j_k)\) \((k=1,\ldots ,n)\) with \(1\le j_k\le l_{i_k}\) and \(i_{k_1}\ne i_{k_2}\) \((k_1\ne k_2)\) such that \(\frac{N_{i_1j_1}}{N_{i_10}},\ldots ,\frac{N_{i_nj_n}}{N_{i_n0}}\) are differentially independent over \({\mathbb Q}\). Suppose the contrary, i.e., \(\frac{N_{i_1j_1}(\eta )}{N_{i_10}(\eta )},\ldots ,\frac{N_{i_nj_n}(\eta )}{N_{i_n0}(\eta )}\) are differentially dependent for any \(n\) different \(i_k\) and \(j_k\in \{1,\ldots ,l_{i_k}\}\). Since each \(\zeta _{i_k}\) is a linear combination of \(\frac{N_{i_kj_k}(\eta )}{N_{i_k0}(\eta )}\) \((j_k=1,\ldots ,l_{i_k})\), it follows that \(\zeta _{i_1},\ldots ,\zeta _{i_n}\) are differentially dependent over \({\mathbb Q}\langle {\mathbf {u}}\rangle \). So \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \zeta \rangle /{\mathbb Q}< \sum _{i=0}^nl_i+n\), a contradiction. \(\square \)
Now the definition of sparse differential resultant is given as follows:
Definition 3.10
\({\mathbf {R}}({\mathbf {u}}_{0},\ldots ,{\mathbf {u}}_{n})\in {\mathbb Q}\{{\mathbf {u}}_{0},\ldots ,{\mathbf {u}}_{n}\}\) in (10) is defined to be the sparse differential resultant of the Laurent differentially essential system \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\), denoted by \(\hbox {Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n}\) or \(\hbox {Res}_{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n}\). And when all the \(\mathcal {A}_i\) are equal to the same \(\mathcal {A}\), we simply denote it by \(\hbox {Res}_\mathcal {A}\).
From the proof of Theorem 3.9 and Eq. (10), \({\mathbf {R}}\) has the following useful properties.
Corollary 3.11
\(\mathcal {I}_{\mathbf {u}}=\mathrm{sat}({\mathbf {R}})\) is a prime differential ideal in \( {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) with a generic zero \(\zeta \), where \(\zeta \) is defined in (9).
Corollary 3.12
\(\mathcal {I}_{\mathbf {u}}=\mathrm{sat}({\mathbf {R}})\) is a prime differential ideal in \({\mathbb Q}\{{\mathbf {u}},u_{00},\ldots ,u_{n0}\}\) with a generic zero \(\zeta =({\mathbf {u}},\zeta _0,\ldots ,\zeta _n)\), where \(\zeta _i\) is defined in (9).
Denote \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\) to be the maximal order of \({\mathbf {R}}\) in \(u_{ik}\,(k=0,\ldots ,l_i)\), that is, \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)=\mathrm{max}_{k}\,{\mathrm{ord}}({\mathbf {R}},u_{ik})\). If \({\mathbf {u}}_i\) does not occur in \({\mathbf {R}}\), then set \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)=-\infty \).
Corollary 3.13
For each \(i\), if \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)=h_i\ge 0\), then \({\mathrm{ord}}({\mathbf {R}},u_{ik})=h_i\,(k=0,\ldots ,l_i)\).
Proof
Firstly, we claim that \({\mathrm{ord}}({\mathbf {R}},u_{i0})=h_i\). For if not, suppose \({\mathrm{ord}}({\mathbf {R}},u_{ik})=h_i\ge 0\) for some \(k\ne 0\). By (11), \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}({\mathbf {u}};\zeta _0,\ldots ,\zeta _n)=0\), where \( \zeta _i\) are defined in (9). By Corollary 3.12, we have \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\in \mathrm{sat}({\mathbf {R}})\), a contradiction since \({\mathbf {R}}\) is irreducible. Thus, \({\mathrm{ord}}({\mathbf {R}},u_{i0})=h_i\). For each \(k\ne 0\), \({\mathrm{ord}}({\mathbf {R}},u_{ik})\le h_i\). If \({\mathrm{ord}}({\mathbf {R}},u_{ik})< h_i\), by (11), we have \(\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}({\mathbf {u}};\zeta _0,\ldots ,\zeta _n)\cdot (-\frac{N_{ik}(\eta )}{N_{i0}(\eta )})=0\). So \(\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}({\mathbf {u}};\zeta _0,\ldots ,\zeta _n)=0\) and \(\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}\in \mathrm{sat}({\mathbf {R}})\), a contradiction. Thus, for each \(k=0,\ldots ,l_i\), \({\mathrm{ord}}({\mathbf {R}},u_{ik})=h_i\). \(\square \)
Corollary 3.14
For \(i=1,\ldots ,n\) and \(k\in {\mathbb N}\), \(y_i^{(k)}\not \in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\).
Proof
Assume the contrary, \(y_i^{(k)}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Since \(\zeta \) in (9) is a generic point of \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\), we have \(\eta _i^{(k)}=0\), which contradicts to the fact that \(\eta =(\eta _1,\ldots ,\eta _n)\) is a generic point of \(([0])_{\mathbb {Q}\langle {\mathbf {u}}\rangle \{{\mathbb {Y}}\}}\). \(\square \)
Remark 3.15
Due to Lemma 3.8, the sparse differential resultant can also be defined as follows: \(\mathcal {I}_{{\mathbb {Y}}^{\pm },{\mathbf {u}}}\cap {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}= \mathrm{sat}({\mathbf {R}})\). Although the sparse differential resultant is defined for Laurent differential polynomials \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\), it is more convenient to prove its properties using \({\mathbb {P}}_0^\text {N},\ldots ,{\mathbb {P}}_n^\text {N}\) instead of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\), since \({\mathbb {P}}_i^\text {N}\) are differential polynomials, and we can thus use results from differential algebra freely.
Remark 3.16
The sparse differential resultant can be computed with characteristic set methods for differential polynomials [3, 8, 25, 42, 47], which is implemented in the diffalg package of Maple. In Sect. 6, we will give an algorithm to compute the sparse differential resultant, which has a better complexity bound.
We give five examples that will be used throughout the paper.
Example 3.17
The following example shows that for a Laurent differentially essential system, its sparse differential resultant may not involve the coefficients of some \({\mathbb {P}}_i\).
Example 3.18
Example 3.19
Let \(\mathcal {A}_0=\{\mathbf{1 },y_1y_2\}\), \(\mathcal {A}_1=\{\mathbf{1 },y_1y'_2\}\), and \(\mathcal {A}_2=\{\mathbf{1 },y'_1y'_2\}\). It is easy to verify that \(\mathcal {A}_0,\mathcal {A}_1,\mathcal {A}_2\) form a Laurent differentially essential system. And \(\hbox {Res}_{{\mathcal {A}}_0,{\mathcal {A}}_1,{\mathcal {A}}_2}=u_{10}u_{01}u_{21}u_{11}u'_{00}-u_{10}u_{00}u_{11}u_{21}u'_{01} -u_{01}^2u_{21}u_{10}^2-u_{01}u_{00}u_{11}^2u_{20}.\)
Example 3.20
Let \(n=1\) and \(\mathcal {A}_0=\mathcal {A}_1=\{y_1^2,(y_1')^2,y_1y_1'\}\). Clearly, \(\mathcal {A}_0,\mathcal {A}_1\) form a Laurent differentially essential system and \(\hbox {Res}_{\mathcal {A}}=u_{11}^2u_{00}^2-2u_{01}u_{10}u_{11}u_{00}+u_{01}^2u_{10}^2- u_{12}u_{02}u_{11}u_{00}-u_{12}u_{02}u_{01}u_{10}+u_{12}^2u_{01}u_{00}+u_{10}u_{11}u_{02}^2\).
Example 3.21
Let \(n=1\) and \(\mathcal {A}_0=\mathcal {A}_1=\{y_1,y_1',y_1^2\}\). Clearly, \(\mathcal {A}_0,\mathcal {A}_1\) form a Laurent differentially essential system and \(\hbox {Res}_{\mathcal {A}}=-u_{12}u_{01}u_{00}u_{10} -u_{12}u_{01} ^2u'_{10}+u_{12}u_{01}u'_{11}u_{00} + u_{12}u_{01}u_{11}u'_{00}-u_{11}u_{02}u_{00}u_{10}+u_{11}u_{02}u'_{10}u_{01} + u_{02}u_{01}u_{10}^2-u_{11}^2u_{02}u'_{00}+u_{11}u_{02}u'_{01}u_{10} +u_{11}u_{00}^2u_{12}\) \( + u_{11}^2u'_{02}u_{00}-u_{11}u'_{02}u_{01}u_{10} -u_{11}u_{01}u'_{12}u_{00} + u_{01}^2u'_{12}u_{10} -u_{11}u'_{01}u_{12}u_{00}-u'_{11}u_{02}u_{01}u_{10}. \)
Remark 3.22
When all the \(\mathcal {A}_i\,(i=0,\ldots ,n)\) are sets of differential monomials as in the above examples, unless explicitly mentioned, we always consider \({\mathbb {P}}_i\) as Laurent differential polynomials. In this paper, sometimes we regard \({\mathbb {P}}_i\) as differential polynomials where it will be indicated.
We now define the sparse differential resultant for any set of specific Laurent differential polynomials over a Laurent differentially essential monomial system. For any finite set \(\mathcal {A}\) of Laurent differential monomials, denote by \(\mathcal {L}(\mathcal {A})\) the set of all Laurent differential polynomials of the form \(\sum _{M\in \mathcal {A}}a_{M}M\) where \(a_{M}\in \mathcal {E}\). Then \(\mathcal {L}(\mathcal {A})\) can be considered as the affine space \(\mathcal {E}^l\) or the projective space \(\mathbf P (l-1)\) over \(\mathcal {E}\) where \(l=|\mathcal {A}|\).
Definition 3.23
Let \(\mathcal {A}_i=\{M_{i0},M_{i1},\ldots ,M_{il_i}\}\,(i=0,\ldots ,n)\) be finite sets of Laurent differential monomials which form a Laurent differentially essential system. Consider \(n+1\) Laurent differential polynomials \((F_0,\ldots ,F_n)\in \prod _{i=0}^n\mathcal {L}(\mathcal {A}_i)\). The sparse differential resultant of \(F_0,\ldots ,F_n\), denoted as \(\hbox {Res}_{F_0,\ldots ,F_n}\), is obtained by replacing \({\mathbf {u}}_i\) by the corresponding coefficient vector of \(F_i\) in \(\hbox {Res}({\mathbf {u}}_{0},\ldots ,{\mathbf {u}}_{n})\) which is the sparse differential resultant of the \(n+1\) generic Laurent differential polynomials in (3).
We will show in Sect. 5.1 that the sparse differential resultant \(\hbox {Res}_{F_0,\ldots ,F_n}=0\) will approximately measure whether or not the overdetermined equation system \(F_i=0\,(i=0,\ldots ,n)\) has a common non-polynomial solution.
4 Criterion for Laurent Differentially Essential System in Terms of Supports
Let \({\mathcal A}_i\,(i=0,\ldots ,n)\) be finite sets of Laurent differential monomials. According to Definition 3.6, in order to check whether they form a Laurent differentially essential system, we need to check whether there exist \(M_{ik_i}, M_{ij_i}\in {\mathcal A}_i (i=0,\ldots ,n)\) such that \(\hbox {{d.tr.deg}}\, {\mathbb Q}\langle M_{0k_0}/M_{0j_0},\) \(\ldots ,M_{nk_n}/M_{nj_n}\rangle /{\mathbb Q}=n\). This can be done with the differential characteristic set method via symbolic computation [3, 17, 25]. In this section, a criterion will be given to check whether a Laurent differential system is essential in terms of their supports, which is conceptually and computationally simpler than the naive approach based on the characteristic set method.
4.1 Laurent Differential Monomials in Reduced and T-shape Forms
In this section, the differential transcendence degree of a set of Laurent differential monomials over \(\mathbb {Q}\) is shown to be equal to the rank of a certain matrix. The idea is to transform a Laurent differential monomial set to a standard form called T-shape whose differential transcendence degree is easy to compute.
Note that there is a one-to-one correspondence between Laurent differential monomials and their symbolic support vectors, so we will not distinguish these two concepts whenever there is no confusion. The same is true for a set of Laurent differential monomials and its symbolic support matrix.
Definition 4.1
A set of Laurent differential monomials \(B_1, B_2, \ldots , B_m\) or its symbolic support matrix \(\mathrm{{D}}\) is called reduced if for each \(i\le \min (m,n)\), \(-\infty \ne {\mathrm{ord}}(B_i,y_i) > {\mathrm{ord}}(B_{i+k},y_i)\), or equivalently \(-\infty \ne \mathrm{deg}(d_{ii},x_i)>\mathrm{deg}(d_{i+k,i},x_i)\), holds for all \(k>0\).
Note that a reduced symbolic support matrix is always of full rank. The reason is that the term \(\prod _{i=1}^{\min (m,n)}\) \(x_i^{{\mathrm{ord}}(B_i,y_i)}\) will appear effectively in the determinant of the \(\min (m,n)\)th principal minor when expanded.
Example 4.2
Before giving the property of reduced symbolic support matrices, the following simple result about the differential transcendence degree is needed.
Lemma 4.3
For \(\eta _1,\eta _2\) in an extension field of \(\mathbb {Q}\), \(\mathrm{d.tr.deg}\,\mathbb {Q}\langle \eta _1^{a_1},\eta _1^{a_2}\eta _2 \rangle /\mathbb {Q}=\mathrm{d.tr.deg}\,\mathbb {Q}\langle \eta _1,\) \(\eta _2 \rangle /\mathbb {Q}\), where \(a_1,a_2\) are nonzero rational numbers.
Proof
The differential transcendence degree of a set of reduced Laurent differential monomials is easy to compute.
Theorem 4.4
Let \(B_1, B_2, \ldots , B_m\) be a set of reduced Laurent differential monomials in \({\mathbb {Y}}\). Then \(\mathrm{d.tr.deg}\,{\mathbb Q}\langle B_1, B_2, \ldots , B_m\rangle /{\mathbb Q}=\min (m,n)\).
Proof
It suffices to prove the case \(m = n\) by the following two facts. In the case \(m>n\), we need only to prove that \(B_1,\ldots , B_n\) are differentially independent. And in the case \(m<n\), we can treat \(y_{m+1},\ldots ,y_n\) as parameters, then \(B_1, B_2, \ldots , B_m\) are still reduced Laurent differential monomials. So if we have proved the result for \(m=n\), \(\hbox {{d.tr.deg}}\, {\mathbb Q}\langle B_1, B_2, \ldots , B_m\rangle /{\mathbb Q}\ge \hbox {{d.tr.deg}}\, {\mathbb Q}\langle y_{m+1},\ldots ,y_n\rangle \langle B_1, B_2, \ldots , B_m\rangle /{\mathbb Q}\langle y_{m+1},\ldots ,y_n\rangle \) \( = m\) follows.
Now, we prove that \(B_1,\ldots ,B_n\) are differentially independent over \(\mathbb {Q}\). Suppose the contrary, then there exists a nonzero differential polynomial \(P\in \mathbb {Q}\{z_1,\ldots ,z_n\}\) such that \(P(B_1,\ldots ,B_n) = 0\). Let \(P = \sum _k c_k P_k \), where \(P_k\) is a monomial and \(c_k\in {\mathbb Q}\backslash \{0\}\). Then, the leading monomial of \(P_k(B_1,\ldots ,B_n)\) is a product of \(LM_{it}\, (i=1,\ldots ,n; t\ge 0)\). We denote this product by \(LMP_k\), then \(LMP_k \ne LMP_j\) for \(k\ne j\) since these \(LM_{it}\) are algebraically independent. But there exists one and only one product which has the highest order, which cannot be eliminated by the others, which means that \(P(B_1,\ldots ,B_n)\ne 0\), a contradiction. \(\square \)
In general, we cannot reduce a symbolic support matrix to a reduced one. We will show that any symbolic support matrix can be reduced to a more general standard form called T-shape to be defined below.
A generalized Laurent differential monomial is a differential monomial with rational numbers as exponents, that is, a monomial of the form \(\prod _{j=1}^n\prod _{k=0}^s (y_{j}^{(k)})^{t_{jk}}\) for \(t_{jk}\in {\mathbb Q}\). Let \(B_1,\ldots ,B_m\) be generalized Laurent differential monomials. Then their symbolic support matrix is \(\mathrm{{D}}=(d_{ij})_{m\times n}\) where \(d_{ij}\in {\mathbb Q}[x_j]\).
Definition 4.5
A set of generalized Laurent differential monomials \(B_1,\ldots ,B_m\) or their symbolic support matrix \(\mathrm{{D}}\) is said to be in T-shape with index \((i,j)\), if there exist \(1\le i\le \min (m,n), 0\le j \le \min (m,n)-i\) such that all elements except those in the first \(i\) rows and the \(i+1,\ldots ,(i+j)\)th columns of \(\mathrm{{D}}\) are zeros and the sub-matrix consisting of the first \(i+j\) columns of \(\mathrm{{D}}\) is reduced.
In Fig. 1, an illustration of a matrix in T-shape is given, where the sub-matrices \(\mathrm{{D}}_1\) and \(\mathrm{{D}}_2\) of the matrix are reduced. It is easy to see that \(\mathrm{{D}}_1\) must be an \(i\times i\) square matrix. Since the first \(i+j\) columns of a T-shape matrix \(\mathrm{{D}}\) are a reduced sub-matrix, we have
Lemma 4.6
The rank of a T-shape matrix with index \((i,j)\) equals to \(i+j\). Furthermore, a T-shape matrix is reduced if and only if it is of full rank, that is, \(i+j=\min {(m,n)}\).
The sub-matrices \(\mathrm{{Z}}_1\) and \(\mathrm{{Z}}_2\) in Fig. 1 are zero matrices and \((\mathrm{{Z}}_1,\mathrm{{Z}}_2)\) is called the zero sub-matrix of \(\mathrm{{D}}\). For a \(k\times l\) zero matrix \(A\), we define its \(0\) -rank to be \(k+l\).
Lemma 4.7
A T-shape matrix \(\mathrm{{D}}\) of index \((i,j)\) is not of full rank if and only if the \(0\)-rank \(r=m+n-i-j\) of its zero sub-matrix satisfies \(r \ge \mathrm{max}(m,n)+1\).
Proof
Note that the zero sub-matrix of \(\mathrm{{D}}\) is an \((m-i)\times (n-j)\) matrix with \(0\)-rank \(r=m+n-i-j\). By Lemma 4.6, \(\mathrm{{D}}\) is not of full rank if and only if \(i+j < \min (m,n)\), which is equivalent to \(r=m+n-i-j>m+n-\min (m,n)\) or \(r\ge \mathrm{max}(m,n)+1\). \(\square \)
The differential transcendence degree of a set of Laurent differential monomials in T-shape can be easily determined, as shown by the following result.
Theorem 4.8
Let \(B_1,\ldots ,B_m\) be generalized Laurent differential monomials and \(\mathrm{{D}}\) their symbolic support matrix which is in T-shape with index \((i,j)\). Then \(\mathrm{d.tr.deg}\,\) \( {\mathbb Q}\langle B_1, \ldots , B_m\rangle /{\mathbb Q}=\mathrm{rank}(\mathrm{{D}})=i+j\).
Proof
Without loss of generality, each \(B_i\) is assumed to be a Laurent differential monomial. For otherwise, by Lemma 4.3, we may consider \(B_i^{k_i}\) for certain \(k_i\in {\mathbb N}\), which is a Laurent differential monomial.
To express the differential transcendence degree of a set \(S\) of Laurent differential monomials in terms of the rank of its symbolic support matrix, it remains to show that \(S\) can be reduced to a set of Laurent differential monomials in T-shape, which has the same differential transcendence degree with \(S\).
We first define the transformations that will be used to reduce each symbolic support matrix to one in T-shape. A \({\mathbb Q}\) -elementary transformation for a matrix \(\mathrm{{D}}\) consists of two types of matrix row operations and one type of matrix column operations. To be more precise, Type 1 operations consist of interchanging two rows of \(\mathrm{{D}}\), Type 2 operations consist of adding a rational number multiple of one row to another, and Type 3 operations consist of interchanging two columns.
Let \(B_1,\ldots ,B_m\) be Laurent differential monomials and \(\mathrm{{D}}\) their symbolic support matrix. Then \({\mathbb Q}\)-elementary transformations of \(\mathrm{{D}}\) correspond to certain transformations of the monomials. Indeed, interchanging the \(i\)th and the \(j\)th rows of \(\mathrm{{D}}\) means interchanging \(B_i\) and \(B_j\), and interchanging the \(i\)th and the \(j\)th columns of \(\mathrm{{D}}\) means interchanging \(y_i\) and \(y_j\) in \(B_1,\ldots ,B_m\)(or in the variable order). Multiplying the \(i\)th row of \(\mathrm{{D}}\) by a rational number \(r\) and adding the result to the \(j\)th row mean changing \(B_j\) to \(B_i^rB_j\). It is clear that by applying \(Q\)-elementary transformations to \(B_1,\ldots ,B_m\), we obtain a set of generalized Laurent differential monomials. As a direct consequence of Lemma 4.3, we have the following result.
Lemma 4.9
Let \(B_1,\ldots ,B_m\) be Laurent differential monomials and \(C_1,\ldots ,C_m\) generalized Laurent differential monomials obtained from \(B_1,\ldots ,B_m\) by a series of \({\mathbb Q}\)-elementary transformations. Then \(\mathrm{d.tr.deg}\,{\mathbb Q}\langle B_1, \ldots , B_m\rangle /{\mathbb Q}=\mathrm{d.tr.deg}\, {\mathbb Q}\langle C_1,\) \(\ldots , C_m\rangle /{\mathbb Q}\).
In “Appendix”, we will prove the following theorem.
Theorem 4.10
The symbolic support matrix of any Laurent differential monomials \(B_1,\) \( \ldots , B_m\) can be reduced to a T-shape matrix by a finite number of \({\mathbb Q}\)-elementary transformations.
We now have the main result of this section.
Theorem 4.11
Let \(B_1,\ldots , B_m\) be Laurent differential monomials in \({\mathbb {Y}}\) and \(\mathrm{{D}}\) their symbolic support matrix. Then \(\mathrm{d.tr.deg}\,{\mathbb Q}\langle B_1, \ldots , B_m\rangle /{\mathbb Q}=\mathrm{rank}(\mathrm{{D}})\).
Proof
By Lemma 4.9, \({\mathbb Q}\)-elementary transformations keep the differential transcendence degree unchanged. The result follows from Theorems 4.8 and 4.10. \(\square \)
Theorem 4.11 can be used to check whether the Laurent polynomial system (3) is differentially essential as shown by the following result.
Corollary 4.12
The Laurent differential system (3) is Laurent differentially essential if and only if there exist \(M_{ij_i}\,(i=0,\ldots ,n)\) with \(1\le j_i\le l_{i}\) such that the symbolic support matrix of the Laurent differential monomials \(M_{0j_0}/M_{00},\ldots ,M_{nj_n}/M_{n0}\) is of rank \(n\).
By Corollary 3.4 of [16] , the complexity to compute the determinant of a sub-matrix \(\mathrm{{D}}_s\) of \(\mathrm{{D}}\) with size \(k\times k\) is bounded by \(O(k^{k+2}L\gamma ^{\frac{2}{k+3}}\Delta )\), where \(L = \log ||\mathrm{{D}}_s||\), \(\gamma \) denotes the number of arithmetic operations required for multiplying a scalar vector by the matrix \(\mathrm{{D}}_s\), and \(\Delta \) is the degree bound of \(\mathrm{{D}}_s\). So, the complexity to compute the rank of \(\mathrm{{D}}\) is single exponential at most.
Remark 4.13
-
Choose \(n+1\) monomials \(M_{ij_i}\,(i=0,\ldots ,n)\) with \(1\le j_i\le l_{i}\).
-
Use Algorithm TSHAPE in “Appendix” to reduce the symbolic support matrix of \(M_{0j_0}/M_{00},\) \(\ldots ,M_{nj_n}/M_{n0}\) to a T-shape matrix \(\mathrm{{D}}\).
-
Use Theorem 4.8 to check whether the rank of \(\mathrm{{D}}\) is \(n\).
-
If the rank of \(\mathrm{{D}}\) is \(n\), then the system is essential. Otherwise, we need to choose another set of \(n+1\) monomials and repeat the procedure.
The number of possible choices for the \(n+1\) monomials is \(\prod _{i=0}^n l_i\), which is very large. But, the procedure is more efficient than computing the rank of the symbolic support matrix for two reasons. Firstly, in Algorithm TSHAPE, since the maximal degree of polynomials in each column of the matrix is not increased, there is no size swell in the elimination procedure. Secondly, the probability for \(n+1\) Laurent differential monomials to have differential transcendence degree \(n\) is very high. As a consequence, we do not need to repeat the procedure for many choices of \(n+1\) monomials.
4.2 Rank Essential Laurent Differential Polynomial Systems
In this section, the result in the preceding section is used to determine a rank essential sub-system of \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\), which is the minimal subset of \({\mathbb {P}}\) whose coefficients occur in \({\mathbf {R}}\).
Lemma 4.14
Let \(\mathrm{{D}}_{k_1,\ldots ,k_m}\) be the symbolic support matrix of the Laurent differential monomials \((M_{1k_1}/M_{10},\ldots ,M_{mk_m}/M_{m0})\). Then \(\mathrm{rank}(\mathrm{{D}}_{\mathbb {P}}) = \mathrm{max}_{ 1\le k_i \le l_i} \mathrm{rank}(\mathrm{{D}}_{k_1,\ldots ,k_m})\).
Proof
Let the rank of \(\mathrm{{D}}_{\mathbb {P}}\) be \(r\). Without loss of generality, we assume that the \(r\times r\) leading principal sub-matrix of \(\mathrm{{D}}_{\mathbb {P}}\), say \(\mathrm{{D}}_{{\mathbb {P}},r}\), is of full rank. By the properties of determinants, \(\det (\mathrm{{D}}_{{\mathbb {P}},r}) = \sum \limits _{k_1=1}^{ l_1}\cdots \sum \limits _{k_r=1}^{ l_r} \prod _{i=1}^r u_{ik_i}\det (k_1,\ldots ,k_r)\) where \(\det (k_1,\ldots ,k_r)\) is the determinant of the \(r\times r\) leading principal sub-matrix of \(\mathrm{{D}}_{k_1,\ldots ,k_m}\). So \(\det (\mathrm{{D}}_{{\mathbb {P}},r})\ne 0\) if and only if there exist \(k_1,\ldots ,k_r\) such that \(\det (k_1,\ldots ,k_r)\ne 0\). Hence, the rank of \(\mathrm{{D}}_{k_1,\ldots ,k_m}\) is no less than the rank of \(\mathrm{{D}}_{\mathbb {P}}\). On the other hand, let \(s= \mathrm{max}_{ 1\le k_i \le l_i} \mathrm{rank}(\mathrm{{D}}_{k_1,\ldots ,k_m})\). Without loss of generality, we assume \(\det (k_1,\ldots ,k_s)\ne 0\), then, \(\det (\mathrm{{D}}_{{\mathbb {P}},s})\ne 0\). Hence, \(s\) is no greater than the rank of \(\mathrm{{D}}_{\mathbb {P}}\). \(\square \)
The following result is interesting in that it reduces the computation of differential transcendence degree for a set of generic Laurent differential polynomials to the computation of the rank of a matrix, which is analogous to the similar result for linear equations.
Theorem 4.15
For \({\mathbb {P}}_i\) given in (12), \(\mathrm{d.tr.deg}\,{\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle \langle {\mathbb {P}}_1/M_{10},\ldots , {\mathbb {P}}_m/M_{m0}\rangle /\) \({\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle = \mathrm{rank}(\mathrm{{D}}_{\mathbb {P}})\).
Proof
By Lemma 2.1, \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle \langle {\mathbb {P}}_1/M_{10},\ldots , {\mathbb {P}}_m/M_{m0}\rangle /{\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle \) is no less than the maximal differential transcendence degree of \(M_{1k_1}/M_{10},\ldots ,M_{mk_m}/M_{m0}\) over \({\mathbb Q}\).
On the other hand, the differential transcendence degree will not increase by linear combinations, since for any differential polynomial \(a_i\) and \( \bar{a}_1\), \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \lambda \rangle \langle a_1+\lambda \bar{a}_1,a_2,\ldots ,a_k\rangle /{\mathbb Q}\langle \lambda \rangle \le \mathrm{max}\{\hbox {{d.tr.deg}}\,{\mathbb Q}\langle a_1,a_2\ldots ,a_k\rangle /{\mathbb Q},\) \( \hbox {{d.tr.deg}}\,{\mathbb Q}\langle \bar{a}_1,a_2,\ldots ,a_k\rangle /{\mathbb Q}\}\). So, the differential transcendence degree of \({\mathbb {P}}_1/M_{10},\ldots , {\mathbb {P}}_m/M_{m0}\) over \({\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i \rangle \) is no greater than the maximal differential transcendence degree of \(M_{1k_1}/M_{10},\ldots ,M_{mk_m}/M_{m0}\).
Thus, \(\hbox {{d.tr.deg}}\,{\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle \langle {\mathbb {P}}_1/M_{10},\ldots , {\mathbb {P}}_m/M_{m0}\rangle /{\mathbb Q}\langle \cup _{i=1}^m{\mathbf {u}}_i\rangle =\mathrm{max}_{ k_i}\hbox {{d.tr.deg}}\,\mathbb {Q}\langle M_{1k_1}/M_{10},\) \(\ldots ,M_{mk_m}/M_{m0}\rangle /\mathbb {Q}\). By Theorem 4.11 and Lemma 4.14, the differential transcendence degree of \({\mathbb {P}}_1/M_{10},\ldots , {\mathbb {P}}_m/M_{m0}\) equals to the rank of \(\mathrm{{D}}_{\mathbb {P}}\).\(\square \)
By Lemma and 4.14 and Theorem 4.15, we have the following criterion for system (3) to be differentially essential.
Corollary 4.16
The Laurent differential system \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) defined in (3) is Laurent differentially essential if and only if \(\mathrm{rank}(\mathrm{{D}}_{\mathbb {P}})=n\).
The difference between Corollary 4.12 and Corollary 4.16 is that in the later case we need only to compute the rank of a single matrix whose elements are multivariate polynomials in \(\sum _{i=0}^n (l_i+1)+n\) variables, while in the former case we need to compute the ranks of up to \(\prod _{i=0}^n l_i\) matrices whose elements are univariate polynomials in \(n\) separate variables.
Theorem 4.17
The above \(\mathcal {I}_u\) is a differential prime ideal with codimension \(m-\mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}})\).
Proof
In the following, two applications of Theorem 4.17 will be given. The first application is to identify certain \({\mathbb {P}}_i\) such that their coefficients will not occur in the sparse differential resultant. This will lead to simplifications in the computation of the resultant.
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) be given in (3) and \(I\subset \{0,1,\ldots ,n\}\). Denote \({\mathbf {u}}_I=\cup _{i\in I}{\mathbf {u}}_i\). Also denote by \({\mathbb {P}}_I\) the Laurent differential polynomial set consisting of \({\mathbb {P}}_i\,( i\in I)\) and \(\mathrm{{D}}_{{\mathbb {P}}_I}\) its symbolic support matrix. Let \({\mathbb {P}}_I^{\text {N}}=\{{\mathbb {P}}_i^{\text {N}}| i\in I\}\). For a subset \(I\subset \{0,1,\ldots ,n\}\), the cardinal number of \(I\) is denoted by \(|I|\). If \(|I|= \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_I})\), then \({\mathbb {P}}_I\), or \(\{\mathcal {A}_i\,|\,i\in I\}\), is called a differentially independent set.
Lemma 4.18
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) given in (3) be a Laurent differentially essential system and \(I\subset \{0, 1,\ldots , n \}\). If \(|I|- \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_I}) = 1\), then \(([{\mathbb {P}}_I^{\text {N}}]\hbox {:}\mathbb {m})_{{\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_I\}}\cap {\mathbb Q}\{{\mathbf {u}}_I\}=\mathrm{sat}({\mathbf {R}})\).
Proof
By Theorem 4.17, \(\mathcal {I}_1=([{\mathbb {P}}_I^{\text {N}}]\hbox {:}\mathbb {m})_{{\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_I\}}\cap {\mathbb Q}\{{\mathbf {u}}_I\}\) is of codimension \(|I|-\mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_I})=1\). Then \(\mathcal {I}_1=\mathrm{sat}({\mathbf {R}}_1)\subset \mathrm{sat}({\mathbf {R}})\) for an irreducible differential polynomial \({\mathbf {R}}_1\in {\mathbb Q}\{{\mathbf {u}}_I\}\). By Lemma 2.3, \({\mathbf {R}}\) can reduce \({\mathbf {R}}_1\) to zero under any ranking. If \(I = \{0,1,\ldots ,n\}\), then the lemma is proved. Otherwise, for any \(k\in \{0,1,\ldots ,n\}\setminus I\), we claim that \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_k)=-\infty \). Suppose the contrary, then under an arbitrary elimination ranking satisfying \({\mathbf {u}}_k > {\mathbf {u}}_i\) for \(i\ne k\), \({\mathbf {R}}_1\) cannot be reduced to zero w.r.t \({\mathbf {R}}\), a contradiction to \({\mathbf {R}}_1\in \mathrm{sat}({\mathbf {R}})\). So \({\mathbf {R}}\in {\mathbb Q}\{{\mathbf {u}}_I\}\) and it is easy to check that \({\mathbf {R}}\in ([{\mathbb {P}}_I^{\text {N}}]\hbox {:}\mathbb {m})_{{\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_I\}}\cap {\mathbb Q}\{{\mathbf {u}}_I\}=\mathrm{sat}({\mathbf {R}}_1)\). Then \(\mathrm{sat}({\mathbf {R}})=\mathrm{sat}({\mathbf {R}}_1)\) and the lemma is proved. \(\square \)
Definition 4.19
Let \(I\subset \{0,1,\ldots ,n\}\). Then we say \(I\) or \({\mathbb {P}}_I\) is rank essential if the following conditions hold: (1) \(|I| - \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_I}) = 1\) and (2) \(|J| = \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_J})\) for each proper subset \(J\) of \(I\).
Note that a rank essential system is the differential analog of the essential system introduced in [46]. Using this definition, we have the following property, which is similar to Corollary 1.1 in [46].
Theorem 4.20
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) given in (3) be a Laurent differentially essential system. Then for any \(I\subset \{0, 1,\ldots , n \}\), \(|I|- \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_I}) \le 1\) and there exists a unique \(I\) which is rank essential. If \(I\) is rank essential, then \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\ge 0\) if and only if \(i\in I\).
Proof
Let \(I\) be a rank essential set. By Lemma 4.18, the sparse differential resultant \({\mathbf {R}}\) of \({\mathbb {P}}\) involves only the coefficients of \({\mathbb {P}}_i\,({i\in I})\). For any \(i\in I\), let \(I_{\hat{i}}=I\setminus \{i\}\). Since \(I\) is rank essential, we have \(([{\mathbb {P}}_{I_{\hat{i}}}]\hbox {:}\mathbb {m})_{{\mathbb Q}\{{\mathbb {Y}},{\mathbf {u}}_{I_{\hat{i}}}\}}\cap {\mathbb Q}\{{\mathbf {u}}_{I_{\hat{i}}}\}=[0]\) and hence \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\ge 0\) for any \(i\in I\). \(\square \)
Remark 4.21
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) given in (3) be a Laurent differentially essential system. We can obtain a rank essential set \(I\subset \{0, 1,\ldots , n \}\) as follows. Let \(J=\{0, 1,\ldots , n \}\). If for all \(j\in J\), \(|J\setminus \{j\}| = \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_{J\setminus \{j\}}})\), then \(J\) is rank essential. Otherwise, by Theorem 4.20, there exists an \(j_0\in J\) such that \(|J\setminus \{j_0\}| = \mathrm{rank}(\mathrm{{D}}_{{\mathbb {P}}_{J\setminus \{j_0\}}})+1\). Repeating the procedure for \(J:=J\setminus \{j_0\}\), we will eventually obtain a rank essential system.
Example 4.22
In Example 3.18, \(\{{\mathbb {P}}_0,{\mathbb {P}}_1\}\) is a rank essential set since they involve \(y_1\) only.
A more interesting example is given below.
Example 4.23
The second application of Theorem 4.17 is to prove the dimension conjecture for a class of generic differential polynomials. The differential dimension conjecture proposed by Ritt [42, p. 178] claims that the dimension of each component of the differential ideal generated by \(m\) differential polynomials in \(m\le n\) variables is no less than \(n-m\). In [17], the dimension conjecture is proved for quasi-generic differential polynomials. The following theorem proves the conjecture for a larger class of differential polynomials.
Theorem 4.24
Let \({\mathbb {P}}_i= u_{i0} + \sum \limits _{k=1}^{l_i}u_{ik} M_{ik}\,(i=1,\ldots ,m;\,m\le n)\) be generic differential polynomials in \(n\) differential indeterminates \({\mathbb {Y}}\) and \({\mathbf {u}}_i=(u_{i0},\ldots ,u_{il_i})\). Then \([{\mathbb {P}}_1,\ldots ,{\mathbb {P}}_m]_{{\mathbb Q}\langle {\mathbf {u}}_1,\ldots ,{\mathbf {u}}_m\rangle \{{\mathbb {Y}}\}}\) is either the unit ideal or a prime differential ideal of dimension \(n-m\).
Proof
Use the notation introduced in the proof of Theorem 4.17 with \(M_{i0}=1\). Let \(\mathcal {I}_0 = [{\mathbb {P}}_1,\ldots ,{\mathbb {P}}_m]_{{\mathbb Q}\{{\mathbf {u}}_1,\ldots ,{\mathbf {u}}_m, {\mathbb {Y}}\}}\) and \(\mathcal {I}_1 = [{\mathbb {P}}_1,\ldots ,{\mathbb {P}}_m]_{{\mathbb Q}\langle {\mathbf {u}}_1,\ldots ,{\mathbf {u}}_m\rangle \{{\mathbb {Y}}\}}\). Since \({\mathbb {P}}_i\) contains a nonvanishing degree zero term \(u_{i0}\), it is clear that \(\mathcal {I}_0=\mathcal {I}_0\hbox {{:}}\mathbb {m}=\mathcal {I}_1\cap {\mathbb Q}\{{\mathbf {u}}_1,\ldots ,{\mathbf {u}}_m, {\mathbb {Y}}\}\).
By Theorem 4.15, Theorem 4.17, and Corollary 4.16, properties 1) and 2) of Theorem 1.1 are proved.
5 Basic Properties of the Sparse Differential Resultant
In this section, we will prove basic properties for the sparse differential resultant \({\mathbf {R}}({\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n)\) of the generic Laurent differential polynomials given in (3).
5.1 Necessary and Sufficient Conditions for the Existence of Non-polynomial Solutions
In the algebraic case, the vanishing of the sparse resultant gives a necessary and sufficient condition for a system of polynomials to have common nonzero solutions in certain sense. We will show that this is also true for sparse differential resultants.
Lemma 5.1
Suppose the Laurent differential monomial sets \(\mathcal {A}_i\,(i=0,\ldots ,n)\) form a Laurent differentially essential system. Then \(\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)\subseteq {\mathbb {V}}\big (\mathrm{sat}(\mathrm{Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )\).
Proof
Example 5.2
Consider Example 3.17. Suppose \({\mathcal {F}}={\mathbb Q}(x)\) and \(\delta = \frac{d}{d x}\). In this example, we have \(\hbox {Res}_{{\mathbb {P}}_0,{\mathbb {P}}_1,{\mathbb {P}}_2}\ne 0\). But \(y_1=c_{11}x+c_{10}, y_2=c_{22}x^2+c_{21}x+c_{20}\) consist of a nonzero solution of \({\mathbb {P}}_0={\mathbb {P}}_1={\mathbb {P}}_2=0\) where \(c_{ij}\) are distinct arbitrary constants. This shows that Lemma 5.1 is not correct if we do not consider non-polynomial solutions. This example also shows why we need to consider non-polynomial differential solutions, or equivalently why we consider Laurent differential polynomials instead of the usual differential polynomials.
Let \(\overline{\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}\) be the Kolchin differential closure of \(\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)\) in \(\mathcal {E}^{l_0+1}\times \cdots \times \mathcal {E}^{l_n+1}\). Then we have the following theorem which gives another characterization of the sparse differential resultant.
Theorem 5.3
Suppose the Laurent differential monomial sets \(\mathcal {A}_i\,(i=0,\ldots ,n)\) form a Laurent differentially essential system. Then \(\overline{\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}\!=\!{\mathbb {V}}\big (\mathrm{sat}(\mathrm{Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )\).
Proof
Firstly, by Lemma 5.1, \(\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n) \subseteq {\mathbb {V}}\big (\mathrm{sat}(\hbox {Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )\). So \(\overline{\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)} \subseteq {\mathbb {V}}\big (\mathrm{sat}(\hbox {Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )\).
For the other direction, let \(\eta ,\zeta \) be as defined in (9). By Theorem 3.9, \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is a prime differential ideal with a generic point \((\eta ;\zeta )\). Let \((F_0,\ldots ,F_n)\in \mathcal {L}(\mathcal {A}_0)\times \cdots \times \mathcal {L}(\mathcal {A}_n)\) be a set of Laurent differential polynomials represented by \(\zeta \). Clearly, \(\eta \) is a non-polynomial solution of \(F_i=0\). Thus, \(\zeta \in \mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n) \subset \overline{\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}\). By Corollary 3.11, \(\zeta \) is a generic point of \(\mathrm{sat}(\hbox {Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\). It follows that \({\mathbb {V}}\big (\mathrm{sat}(\hbox {Res}_{\mathcal {A}_0,\ldots , \mathcal {A}_n})\big )\subseteq \overline{\mathcal {Z}(\mathcal {A}_0, \ldots ,\mathcal {A}_n)}\). As a consequence, \({\mathbb {V}}\big (\mathrm{sat}(\hbox {Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )= \overline{\mathcal {Z}(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}\). \(\square \)
The above theorem shows that the sparse differential resultant gives a sufficient and necessary condition for a differentially essential system to have non-polynomial solutions over an open set of \(\prod _{i=0}^n \mathcal {L}(\mathcal {A}_i)\) in the sense of the Kolchin topology.
In the rest of this section, we will analyze structures of non-polynomial solutions of the system (3). By Theorem 4.20 and Corollary 4.21, \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) in (3) can be divided into two disjoint sets \(\{{\mathbb {P}}_i\,|\,i\in I\}\) and \(\{{\mathbb {P}}_i\,|\,i\in \{0,1,\ldots ,n\}\backslash I\}\), where \(I\subseteq \{0,1,\ldots ,n\}\) is rank essential. In this section, we will assume that \(\{0,1,\ldots ,n\}\) is rank essential, that is, any \(n\) of the \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) form a differentially independent set, which is equivalent to the fact that each \({\mathbf {u}}_i\) occurs in \({\mathbf {R}}\) effectively.
Firstly, we will give the following theorem which shows the relation between the original differential system and their sparse differential resultant.
Theorem 5.4
Proof
Let \(\mathcal {J}=\big ([{\mathbf {R}},(Q_{ik})_{0\le i\le n;1\le k\le l_i}]\hbox {{:}}S^\infty \big )_{\mathbb {Q}\{{\mathbb {Y}},{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}}\). By Theorem 3.9, \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is a prime differential ideal with a generic point \(\theta =(\eta ;\zeta )\) given in (9). By Corollary 3.12, \(\zeta =({\mathbf {u}},\zeta _0,\ldots ,\zeta _n)\) is a generic zero point of \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}=\mathrm{sat}({\mathbf {R}})\). Since \(\frac{M_{ik}(\eta )}{M_{i0}(\eta )}=\frac{N_{ik}(\eta )}{N_{i0}(\eta )}\), by (11), \(Q_{ik}({\mathbf {u}},\zeta _0,\ldots ,\zeta _n)=0\). So \(Q_{ik}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\).
Since \({\mathbb {P}}\) is rank essential, \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\ge 0\). Substituting \(\big (Q_{ik}+N_{i0}\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\big )/\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}\) for \(N_{ik}\) in each \({\mathbb {P}}_i^\text {N}\), we obtain \({\mathbb {P}}_i^\text {N}=u_{i0}N_{i0}+\sum _{k=1}^{l_i}u_{ik}\big (Q_{ik}+N_{i0}\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\big )/\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}\). So \(\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}{\mathbb {P}}_i^\text {N}=\sum _{k=1}^{l_i} u_{ik}Q_{ik}+(\sum _{k=0}^{l_i}u_{ik}\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}})N_{i0}\). Since \(Q_{ik}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\), \(R_i=\sum _{k=0}^{l_i}u_{ik}\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Since \(R_i\) and \({\mathbf {R}}\) have the same degree and \({\mathbf {R}}\) is irreducible, there exists some \(a\in \mathbb {Q}\) such that \(R_i=a{\mathbf {R}}\). It follows that \({\mathbb {P}}_i^\text {N}\in \mathcal {J}\). For any differential polynomial \(f\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\), there exists a differential monomial \(M\in \mathbb {m}\) such that \(Mf\in [{\mathbb {P}}_0^\text {N},\ldots ,{\mathbb {P}}_n^\text {N}]\subset \mathcal {J}\). Thus, \(f\in \mathcal {J}\) and \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\subseteq \mathcal {J}\) follows. Conversely, for any differential polynomial \(g\in \mathcal {J}\), there exist some differential monomial \(M\) and some \(b\in \mathbb {N}\) such that \(M(\prod _{i}\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}})^bg\in [{\mathbf {R}},Q_{ik}]\subset \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Since \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is a prime differential ideal, \(g\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Hence, \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}=\mathcal {J}.\) \(\square \)
We conclude this section by giving a sufficient condition for a differentially essential system to have a unique non-polynomial solution. Following notations in Sect. 3.2, \(\mathcal {A}_i=\{M_{i0},M_{i1},\ldots ,M_{il_i}\}\) are finite sets of Laurent differential monomials, where \(M_{ik}= ({\mathbb {Y}}^{[s_i]})^{\alpha _{ik}}\) and \(\alpha _{ik}\in \mathbb {Z}^{n(s_i+1)}\) is an exponent vector written in terms of degrees of \(y_1,\ldots ,y_n,y'_1,\ldots ,y'_n,\) \(\ldots ,y_1^{(s_i)},\ldots ,y_{n}^{(s_i)}\). Let \(o=\mathrm{max}_i\{s_i\}\). Then, every vector \(\alpha _{ik}\) in \(\mathbb {Z}^{n(s_i+1)}\) can be embedded in \(\mathbb {Z}^{n(o+1)}\). For \(L\subset \mathbb {Z}^{n(o+1)}\), let \(\hbox {Span}_{\mathbb {Z}}(L)\) be the \(\mathbb {Z}\) module generated by \(L\). Let \(\mathbf e _i\) be the exponent vector for \(y_i\) in \(\mathbb {Z}^{n(o+1)}\) whose \(i\)th coordinate is 1 and other coordinates are equal to zero. Then we have the following definition.
Definition 5.5
\({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) given in (3) is called normal rank essential if \({\mathbb {P}}\) is rank essential and for each \(j=1,\ldots ,n\), \(\mathbf e _j\in \hbox {Span}_{\mathbb {Z}}(\{\alpha _{ik}-\alpha _{i0}\,|\,i=0,\ldots ,n;k=1,\ldots ,l_i\})\).
Lemma 5.6
Proof
Let \({\mathcal {J}}=\mathrm{sat}({\mathbf {R}},S_1y_1-T_1,\ldots ,S_ny_n-T_n)_{\mathbb {Q}\{{\mathbb {Y}},{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}}\). It is easy to verify that \({\mathcal {J}}\) is a prime differential ideal. Since \({\mathbb {P}}\) is rank essential, \(h_i={\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\ge 0\) for each \(i\). By equation (11), we have \(\frac{N_{ik}(\eta )}{N_{i0}(\eta )}= \frac{M_{ik}(\eta )}{M_{i0}(\eta )}=\overline{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}\big /\overline{\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}}\). Since \(\mathbf e _j\in \hbox {Span}_{\mathbb {Z}}(\{\alpha _{ik}-\alpha _{i0}\,|\,k=1,\ldots ,l_i;i=0,\ldots ,n\})\), for \(j=1,\ldots ,n\), there exist \(t_{jik}\in \mathbb {Z}\) such that \(\sum _{i,k}t_{jik}(\alpha _{ik}-\alpha _{i0})=\mathbf e _j\). So, \(\prod _{i,k}\Big (\frac{N_{ik}}{N_{i0}}\Big )^{t_{jik}}=y_j\). Thus, \(\prod _{i,k}\Big (\frac{N_{ik}(\eta )}{N_{i0}(\eta )}\Big )^{t_{jik}}=\eta _j=\prod _{i,k}\big (\overline{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}\big /\overline{\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}}\big )^{t_{jik}}\). By Theorem 3.9, there exist \(S_j\) and \(T_j\) which are nonnegative power products of \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\) such that \(S_jy_j-T_j\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Since \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\not \in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) and \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) is prime, \(S_j\not \in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) follows. Thus, \({\mathcal {J}}\subset \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). To prove \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\subset {\mathcal {J}}\), for each \(k=0,\ldots ,n\), let \(R_k\) be the differential remainder of \({\mathbb {P}}_k^\text {N}\) w.r.t. \({\mathbf {R}}, S_1y_1-T_1,\ldots ,S_ny_n-T_n\) under the given ranking. Then \(R_k\in {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). And by (2), \(R_k\in [{\mathbf {R}}, S_1y_1-T_1,\ldots ,S_ny_n-T_n,{\mathbb {P}}_k^\text {N}]\subset \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). So \(R_k\in {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\cap \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}=\mathrm{sat}({\mathbf {R}})\). Since \(R_k\) is reduced w.r.t. \({\mathbf {R}}\), \(R_k=0\) and \({\mathbb {P}}_k^\text {N}\in {\mathcal {J}}\) follows. By Corollary 3.14, \(y_i^{(j)}\not \in {\mathcal {J}}\subset \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\) for each \(i\) and \(j\). Thus, \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\subset {\mathcal {J}}\). \(\square \)
Theorem 5.7
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) given in (3) be normal rank essential. Let \(\overline{{\mathbb {P}}}_{i}\) be a specialization of \({\mathbb {P}}_i\) with coefficient vector \({\mathbf {v}}_i\,(i=0,\ldots ,n)\). Then there exists a differential polynomial set \(\mathcal {S}\subset {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) such that \({\mathbb {V}}({\mathbf {R}})\backslash \bigcup \limits _{S\in \mathcal {S}}{\mathbb {V}}(S)\ne \emptyset \) and whenever \(({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\in {\mathbb {V}}({\mathbf {R}}) \backslash \bigcup \limits _{S\in \mathcal {S}}{\mathbb {V}}(S)\), \(\overline{{\mathbb {P}}}_{i}=0\,(i=0,\ldots ,n)\) have a unique common non-polynomial solution.
Proof
By Lemma 5.6, \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}} = \mathrm{sat}({\mathbf {R}},A_1,\ldots ,A_n)\), where \(A_l=S_ly_l-T_l(l=1,\ldots ,n)\). Let \(\mathcal {S}=\{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}},(S_j)^{m+1}\big (\frac{T_j}{S_j}\big )^{(m)}\,\big |\,\) \(0\le i\le n;0\le k\le l_i;1\le j\le n;m\in \mathbb {N}\}\). Firstly, we show that \({\mathbb {V}}({\mathbf {R}})\backslash \bigcup \limits _{S\in \mathcal {S}}{\mathbb {V}}(S)\ne \emptyset \). Suppose the contrary, viz. \({\mathbb {V}}({\mathbf {R}})\subset \bigcup \limits _{S\in \mathcal {S}}{\mathbb {V}}(S)\). In particular, there exists one \(S\in \mathcal {S}\) such that \(S\) vanishes at the generic point \(\zeta \) of \(\mathrm{sat}({\mathbf {R}})\). It is obvious that \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\) does not vanish at \(\zeta \). If \((S_j)^{m+1}\big (\frac{T_j}{S_j}\big )^{(m)}\) vanishes at \(\zeta \) for some \(m\), \((S_j)^{m+1}\big (\frac{T_j}{S_j}\big )^{(m)}\in \mathrm{sat}({\mathbf {R}})\). Replacing \(\frac{T_j}{S_j}\) by \(y_j -\frac{A_j}{S_j}\), we have \(S_j^{m+1}y_j^{(m)}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Since \(S_j\) is a power product of certain \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\), \(S_j^{m+1}\not \in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Then, \(y_j^{(m)}\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\), contradicting to Corollary 3.14.
Suppose \(({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\in {\mathbb {V}}({\mathbf {R}})\backslash \bigcup \limits _{S\in \mathcal {S}}{\mathbb {V}}(S)\). Let \(\bar{T}_j=T_j({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\) and \(\bar{S_j}=S_j({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\). Since \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\ne 0\) for each \(i\) and \(k\), \(\bar{T}_j\bar{S}_j\ne 0\). Let \(\bar{y}_j=\frac{\bar{T}_j}{\bar{S}_j}\) and denote \(\bar{y}=(\bar{y}_1,\ldots ,\bar{y}_n)\). For each \(m\in \mathbb {N},\) \(\bar{y}_j^{(m)}=(\frac{\bar{T}_j}{\bar{S}_j})^{(m)}\ne 0\). Thus, \(\bar{y}\in (\mathcal {E}^\wedge )^n.\) Since \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}=\mathrm{sat}({\mathbf {R}},A_1,\ldots ,A_n)\), \(H\cdot {\mathbb {P}}_i^\text {N}\in [{\mathbf {R}},A_1,\ldots ,A_n]\) where \(H\) is a product of powers of \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\). Hence, \(\overline{{\mathbb {P}}}_{i}^\text {N}(\bar{y})= M_i(\bar{y})\cdot \overline{{\mathbb {P}}}_{i}(\bar{y})=0\), which implies that \(\overline{{\mathbb {P}}}_{i}(\bar{y})=0\). Thus, \(\bar{y}\) is a non-polynomial common solution of \(\overline{{\mathbb {P}}}_{i}\). On the other hand, if \(\xi \) is a non-polynomial common solution of \(\overline{{\mathbb {P}}}_{i}\), then \(\bar{S}_jy_j-\bar{T}_j\) vanishes at \(\xi \) for each \(i\). Hence, \(\xi =\bar{y}\). As a consequence, \(\overline{{\mathbb {P}}}_{i}=0\) have a unique common non-polynomial solution. \(\square \)
Theorem 5.7 can be rephrased as the following geometric form.
Corollary 5.8
Let \(\mathcal {Z}_1(\mathcal {A}_0,\ldots ,\mathcal {A}_n) \subset \mathcal {E}^{l_0+1}\times \cdots \times \mathcal {E}^{l_n+1}\) be the set consisting of \(({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\) for which the corresponding Laurent differential polynomials \(F_i=0\,(i=0,\ldots ,n)\) have a unique non-polynomial common solution and \(\overline{\mathcal {Z}_1(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}\) the Kolchin closure of \(\mathcal {Z}_1(\mathcal {A}_0,\ldots ,\mathcal {A}_n)\). Then if \(\mathcal {A}_0,\ldots ,\mathcal {A}_n\) are normal rank essential, \(\overline{\mathcal {Z}_1(\mathcal {A}_0,\ldots ,\mathcal {A}_n)}=\) \({\mathbb {V}}\big (\mathrm{sat}(\) \(\mathrm{Res}_{\mathcal {A}_0,\ldots ,\mathcal {A}_n})\big )\).
Example 5.9
In Example 3.18, the sparse differential resultant \({\mathbf {R}}\) of \({\mathbb {P}}_0,{\mathbb {P}}_1,{\mathbb {P}}_2\) is free from the coefficients of \({\mathbb {P}}_2.\) The system can be solved as follows: \(y_1\) can be solved from \({\mathbb {P}}_0={\mathbb {P}}_1=0\) and \({\mathbb {P}}_2=u_{10}+u_{11}y'_2\) is of order one in \(y_2\) which leads to an infinite number of solutions. Thus, the system cannot have a unique solution. This shows the importance of rank essential condition.
Example 5.10
In Example 3.19, the characteristic set of \([{\mathbb {P}}_0,{\mathbb {P}}_1,{\mathbb {P}}_2]\) w.r.t. the elimination ranking \(u_{ik}\prec y_2\prec y_1\) is \({\mathbf {R}},u_{11}u_{00}y'_2-u_{01}u_{10}y_2,u_{01}y_2y_1+u_{00}\). Here \(\mathcal {A}_0,\mathcal {A}_1,\mathcal {A}_2\) are rank essential but not normal rank essential, and the system \(\{{\mathbb {P}}_0,{\mathbb {P}}_1,{\mathbb {P}}_2\}\) does not have a unique solution under the condition \({\mathbf {R}}=0\).
5.2 Differential Homogeneity of the Sparse Differential Resultant
Following Kolchin [30], we now introduce the concept of differentially homogenous polynomials.
Definition 5.11
A differential polynomial \(f \in \mathcal {F}\{z_{0},\ldots ,z_{n}\}\) is called differentially homogenous of degree \(m\) if for a new differential indeterminate \(\lambda \), we have \(f(\lambda z_{0},\lambda z_{1}\ldots ,\lambda z_{n})=\lambda ^{m}f(z_{0},z_{1},\ldots ,z_{n}) \).
The differential analog of Euler’s theorem related to homogenous polynomials is valid.
Theorem 5.12
Sparse differential resultants have the following property.
Theorem 5.13
The sparse differential resultant is differentially homogenous in each \({\mathbf {u}}_i\) which is the coefficient vector of \({\mathbb {P}}_i\).
Proof
5.3 Poisson Product Formulas
In this section, we prove formulas for sparse differential resultants, which are similar to the Poisson product formulas for multivariate resultants [37].
In this way, \((\mathbb {Q}_\tau ,\delta _\tau )\) is a differential field which can be considered as a finitely generated differential extension field of \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \). Recall that \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \) is a finitely generated differential extension field of \(\mathbb {Q}\) contained in \(\mathcal {E}\). By the definition of universal differential extension field, there exists a differential extension field \(\mathcal {G}\subset \mathcal {E}\) of \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \) and a differential isomorphism \(\varphi _\tau \) over \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \) from \((\mathbb {Q}_\tau ,\delta _\tau )\) to \((\mathcal {G},\delta )\). Summing up the above results, we have
Lemma 5.14
\((\mathbb {Q}_\tau , \delta _\tau )\) defined above is a finitely generated differential extension field of \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \), which is differentially \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \)-isomorphic to a subfield of \(\mathcal {E}\).
Let \(G\) be a differential polynomial in \(\mathbb {Q}\{{\mathbf {u}}_0,{\mathbf {u}}_1,\ldots ,{\mathbf {u}}_n\} = \mathbb {Q}\{\tilde{{\mathbf {u}}},u_{00}\}\). For convenience, by the symbol \(G\Big |_{u_{00}^{(h_0)}=\gamma _{\tau }}\), we mean substituting \(u_{00}^{(h_0+i)}\) by \(\delta _\tau ^{i}\gamma _{\tau }\,(i\ge 0)\) in \(G\). Similarly, by saying \(G\) vanishes at \(u_{00}^{(h_0)}=\gamma _{\tau }\), we mean \(G\Big |_{u_{00}^{(h_0)}=\gamma _{\tau }}=0\). It is easy to prove the following lemma.
Lemma 5.15
Let \(G\) be a differential polynomial in \(\mathbb {Q}\{\tilde{{\mathbf {u}}},u_{00}\}\). Then \(G\in \mathrm{sat}({\mathbf {R}})\) if and only if \(G\) vanishes at \(u_{00}^{(h_0)}=\gamma _{\tau }\).
When a differential polynomial \(G\in \mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \{{\mathbb {Y}}\}\) vanishes at a point \(\eta \in \mathbb {Q}_\tau ^n\), it is easy to see that \(G\) vanishes at \(\varphi _\tau (\eta )\in \mathcal {E}^n\). For convenience, by saying \(\eta \) is a point in a differential variety \(V\) over \(\mathbb {Q}\langle \tilde{{\mathbf {u}}}\rangle \), we mean \(\varphi _\tau (\eta )\in V\).
With these preparations, we now give the following theorem.
Theorem 5.16
Proof
Note that the quantities \(\xi _{\tau \rho }\) are not expressions in terms of \(y_i\). In the following theorem, we will show that if \(\mathcal {A}_i\,(i=0,\ldots ,n)\) satisfy certain conditions, Theorem 5.16 can be strengthened to make \(\xi _{\tau \rho }\) as products of certain values of \(y_i\) and its derivatives.
Theorem 5.17
Proof
Since \({\mathbb {P}}\) is rank essential, each \({\mathbf {u}}_i\) effectively occurs in \({\mathbf {R}}\), so each \(h_i\ge 0.\) By Theorem 3.9, \(\theta =(\eta ;\zeta _0,u_{01},\ldots ,u_{0l_0};\ldots ; \zeta _n,u_{n1},\ldots ,u_{nl_n})\) is a generic point of \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). By Lemma 5.6, there exist \(S_j\) and \(T_j\) which are nonnegative power products of \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\) such that \(S_jy_j-T_j\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). That is, \(\eta _j=\overline{T_j}/\overline{S_j}\) for \(j=1,\ldots ,n\), where \(\overline{T_j} \) and \( \overline{S_j}\) are obtained by substituting \((u_{00},\ldots ,u_{n0})=(\zeta _0,\ldots ,\zeta _n)\) in \(T_j\) and \(S_j\), respectively. Since \({\mathbf {R}}\) is an irreducible polynomial, every \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\) does not vanishes at \(u_{00}^{(h_0)}=\gamma _\tau \). Let \(\eta _{\tau j}=\frac{T_j}{S_j}\big |_{u_{00}^{(h_0)}=\gamma _\tau }\) and \(\eta _\tau =(\eta _{\tau 1},\ldots ,\eta _{\tau n})\). By (11), \(\frac{N_{0k}(\eta )}{N_{00}(\eta )}= \prod \limits _{j=1}^n\prod \limits _{k=0}^{s_0}(\eta _j^{(k)})^{(\alpha _{0k}-\alpha _{00})_{jk}} =\overline{\frac{\partial {\mathbf {R}}}{\partial u_{0k}^{(h_0)}}}\Big /\overline{\frac{\partial {\mathbf {R}}}{\partial u_{00}^{(h_0)}}}\). So \(\prod \limits _{j=1}^n\prod \limits _{k=0}^{s_0}\Big [\Big (\frac{\overline{T_j}}{\overline{S_j}}\Big )^{(k)}\Big ]^{(\alpha _{0k}-\alpha _{00})_{jk}} =\overline{\frac{\partial {\mathbf {R}}}{\partial u_{0k}^{(h_0)}}}\Big /\overline{\frac{\partial {\mathbf {R}}}{\partial u_{00}^{(h_0)}}}\). Let \(\mathcal {S}\) be the differential polynomial set consisting of \(\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\) and \((S_j)^{m+1}\big (\frac{T_j}{S_j}\big )^{(m)}\) for all \(i=0,\ldots ,n;k=0,\ldots ,l_i;j=1,\ldots ,n\) and \(m\in \mathbb {N}\). By Corollary 3.12, there exists a finite set \(\mathcal {S}_1\) of \(\mathcal {S}\) and \(a\in \mathbb {N}\) such that \(H=\big (\prod \limits _{S\in \mathcal {S}_1}S\big )^a \Big (\prod \limits _{j=1}^n\prod \limits _{k=0}^{s_0} \big [\big (T_j/S_j\big )^{(k)}\big ]^{(\alpha _{0k}-\alpha _{00})_{jk}} -\frac{\partial {\mathbf {R}}}{\partial u_{0k}^{(h_0)}}\Big /\frac{\partial {\mathbf {R}}}{\partial u_{00}^{(h_0)}}\Big )\in \mathrm{sat}({\mathbf {R}})\). By Lemma 5.15, \(H\) vanishes at \(u_{00}^{(h_0)}=\gamma _\tau .\) And by the proof of Theorem 5.7, \(\mathcal {S}\cap \mathrm{sat}({\mathbf {R}})=\emptyset \). So \(\xi _{\tau k}=\frac{N_{0k}(\eta _\tau )}{N_{00}(\eta _\tau )}\). By Theorem 5.16, \({\mathbf {R}}=A\prod _{\tau =1}^{t_0} (u_{00}+\sum \limits _{k=1}^{l_0} u_{0 k}\xi _{\tau k})^{(h_0)}\). Thus, (20) follows.
To prove the second part of this theorem, we need first to show that \(\delta _\tau ^{k}\eta _{\tau j}\ne 0\) for each \(k\ge 0.\) Suppose the contrary, that is, there exists some \(k\) such that \(\delta _\tau ^{k}\eta _{\tau j}=0\). From \(\eta _{\tau j}=\frac{T_j}{S_j}\big |_{u_{00}^{(h_0)}=\gamma _\tau }\), \(\delta _\tau ^{k}\eta _{\tau j}=\big (\frac{T_j}{S_j}\big )^{(k)}\big |_{u_{00}^{(h_0)}=\gamma _\tau }=0\). Thus, \(S_j^{k+1}\big (\frac{T_j}{S_j}\big )^{(k)}\in \mathrm{sat}({\mathbf {R}})\). It follows that \(\eta _j^{(k)}=\big (\frac{\overline{T_j}}{\overline{S_j}}\big )^{(k)}=0\), a contradiction to the fact that \(\eta _j\) is a differential indeterminate.
Following the above procedure, we can show that \(\frac{N_{ik}(\eta _\tau )}{N_{i0}(\eta _\tau )}=\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}\big /\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}}\) where \(\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}=\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}\Big |_{u_{00}^{(h_0)}=\gamma _\tau }\). Similar to (19), we have \(\sum _{k=0}^{l_i}u_{ik}\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}=b{\mathbf {R}}\) for some \(b\) in \({\mathbb Q}\). So, for each \(i\ne 0\), \(\sum _{k=0}^{l_i}u_{ik}\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}=0.\) It follows that for each \(i\ne 0\), \({\mathbb {P}}_i(\eta _\tau )=\sum _{k=0}^{l_i}u_{ik}N_{ik}(\eta _\tau ) =\frac{N_{i0}(\eta _\tau )}{\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{i0}^{(h_i)}}}}\bigg (\sum _{k=0}^{l_i}u_{ik}\widehat{\frac{\partial {\mathbf {R}}}{\partial u_{ik}^{(h_i)}}}\bigg )=0\). So each \(\eta _\tau \) is a common non-polynomial differential zero of \({\mathbb {P}}_1,\ldots ,{\mathbb {P}}_n\). \(\square \)
Under the conditions of Theorem 5.17, we further have the following result.
Theorem 5.18
The elements \(\eta _\tau \,(\tau =1,\ldots ,t_0)\) defined in Theorem 5.17 are generic points of the prime ideal \(([{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]\hbox {{:}}\mathbb {m})_{ \mathbb {Q}\langle \hat{{\mathbf {u}}}\rangle \{{\mathbb {Y}}\}}\), where \(\hat{{\mathbf {u}}}=\cup _{i=1}^n{\mathbf {u}}_i\).
Proof
Let \({\mathcal {J}}=([{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]\hbox {{:}}\mathbb {m})_{\mathbb {Q}\langle \hat{{\mathbf {u}}}\rangle \{{\mathbb {Y}}\}}\) and \({\mathcal {J}}_0=([{\mathbb {P}}_1^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}]\hbox {{:}}\mathbb {m})_{\mathbb {Q}\{{\mathbb {Y}},\hat{{\mathbf {u}}}\}}\). Similar to the proof of Theorem 3.9, it is easy to show that \({\mathcal {J}}_0\) is a prime differential ideal. Since \({\mathbb {P}}\) is rank essential, \({\mathcal {J}}_0\cap \mathbb {Q}\{\hat{{\mathbf {u}}}\}=[0]\). Thus, \({\mathcal {J}}=([{\mathcal {J}}_0])_{\mathbb {Q}\langle \hat{{\mathbf {u}}}\rangle \{{\mathbb {Y}}\}}\) is a prime differential ideal and \({\mathcal {J}}\cap \mathbb {Q}\{{\mathbb {Y}},\hat{{\mathbf {u}}}\}={\mathcal {J}}_0\). Let \(\xi =(\xi _1,\ldots ,\xi _n)\) be a generic point of \({\mathcal {J}}\). Then \((\xi ;\hat{{\mathbf {u}}})\) is a generic point of \({\mathcal {J}}_0\). Let \(\beta =-\sum _{k=1}^{l_0}u_{0k}N_{0k}(\xi )/N_{00}(\xi )\). Then \((\xi ;\beta ,u_{01},\ldots ,u_{0l_0};\hat{{\mathbf {u}}})\) is a generic point of \(\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}=([{\mathbb {P}}_0^{\text {N}},{\mathbb {P}}_1^\text {N},\ldots ,{\mathbb {P}}_n^{\text {N}}]\hbox {{:}}\mathbb {m})_{\mathbb {Q}\{{\mathbb {Y}};{\mathbf {u}}_0,\hat{{\mathbf {u}}}\}}\). Since \(\mathrm{sat}({\mathbf {R}})=\mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\hat{{\mathbf {u}}}\}\), \(\gamma =(\beta ,u_{01},\ldots ,u_{0l_0};\hat{{\mathbf {u}}})\) is a generic point of \(\mathrm{sat}({\mathbf {R}})\). By Lemma 5.6, for \(j=1,\ldots ,n\), \(S_jy_j-T_j\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\). Then, \(\xi _j=\frac{T_j}{S_j}(\gamma )\).
By Theorem 5.17, \(\eta _\tau \) is a common non-polynomial solution of \({\mathbb {P}}_i^{\text {N}}=0\,(i=1,\ldots ,n)\) and thus also a differential zero of \({\mathcal {J}}\). Recall \(\eta _{\tau j}=\frac{T_j}{S_j}\big |_{u_{00}^{(h_0)}=\gamma _\tau }\). If \(f\) is any differential polynomial in \(\mathbb {Q}\langle \hat{{\mathbf {u}}}\rangle \{{\mathbb {Y}}\}\) such that \(f(\eta _\tau )=0\), then \(f(\frac{T_1}{S_1},\ldots ,\frac{T_n}{S_n})\big |_{u_{00}^{(h_0)}=\gamma _\tau }=0\). There exist \(a_j\in \mathbb {N}\) such that \(g=\prod _jS_j^{a_j}f(\frac{T_1}{S_1},\ldots ,\frac{T_n}{S_n})\in \mathbb {Q}\{{\mathbf {u}}_0,\hat{{\mathbf {u}}}\}.\) Then \(g|_{u_{00}^{(h_0)}=\gamma _\tau }=0\). By Lemma 5.15, \(g\in \mathrm{sat}({\mathbf {R}})\) while \(S_j\not \in \mathrm{sat}({\mathbf {R}})\). As a consequence, \(g(\gamma )=0\) and \(S_j(\gamma )\ne 0\). It follows that \(f(\xi )=f(\xi _1,\ldots ,\xi _n)=f(\frac{T_1}{S_1}(\gamma ),\ldots ,\frac{T_n}{S_n}(\gamma ))=0\) and hence \(f\in {\mathcal {J}}\), since \(\xi \) is a generic point of \({\mathcal {J}}\). Thus, \(\eta _\tau \) is a generic point of \({\mathcal {J}}\). \(\square \)
With Theorems 5.16, 5.17, and 5.18, property 3) of Theorem 1.2 is proved.
5.4 Differential Toric Variety and Sparse Differential Resultant
In this section, we will introduce the concept of differential toric variety and establish its relation with the sparse differential resultant.
Definition 5.19
The Kolchin projective differential closure of the image of \(\phi _{\mathcal {A}}\) is defined to be the differential toric variety w.r.t. \(\mathcal {A}\), denoted by \(X_\mathcal {A}\). That is, \(X_\mathcal {A}=\overline{\phi _{\mathcal {A}}\big ((\mathcal {E}^\wedge )^n\big )}\).
Then we have the following theorem.
Theorem 5.20
\(X_\mathcal {A}\) is an irreducible projective differential variety over \(\mathbb {Q}\) of dimension \(n\).
Proof
Let \({\mathcal {J}}_1={\mathcal {J}}\cap \mathbb {Q}\{z_0,z_1,\ldots ,z_l\}\). Then \({\mathcal {J}}_1\) is a prime differential ideal with a generic point \(\theta \). Denote \({\mathbf {z}}=(z_0,z_1,\ldots ,z_l)\). For any \(f\in {\mathcal {J}}_1\hbox {{:}}{\mathbf {z}}\), since \(z_0f\in {\mathcal {J}}_1\), \(z_0f\) vanishes at \(\theta \) and \(f(\theta )=0\) follows. So \(f\in {\mathcal {J}}_1\), and it follows that \({\mathcal {J}}_1\hbox {{:}}{\mathbf {z}}={\mathcal {J}}_1\). And for any \(f\in {\mathcal {J}}_1\subset {\mathcal {J}}\) and any differential indeterminate \(\lambda \) over \({\mathbb Q}\langle \eta ,v\rangle \), let \(f(\lambda {\mathbf {z}})=\sum \phi (\lambda )f_\phi ({\mathbf {z}})\) where \(\phi (\lambda )\) are distinct differential monomials in \(\lambda \) and \(f_\phi ({\mathbf {z}})\in {\mathbb Q}\{{\mathbf {z}}\}\). Then \(f(\lambda \theta )=0=\sum \phi (\lambda )f_\phi (\theta )\). So each \(f_\phi (\theta )=0\) and \(f_\phi \in {\mathcal {J}}_1\) follows. Thus, \(f(\lambda {\mathbf {z}})\in {\mathbb Q}\{\lambda \}{\mathcal {J}}_1\). By Definition 2.2, \({\mathcal {J}}_1\) is a differentially homogenous differential ideal. Then \(V={\mathbb {V}}({\mathcal {J}}_1)\) is an irreducible projective differential variety in \(\mathbf P (l)\). Since \(\theta \) is a generic point of \(V\) and \({\mathcal A}\) is differentially essential, \(\hbox {{dim}}(V)=\hbox {{d.tr.deg}}\,\mathbb {Q}\langle \frac{N_1(\eta )}{N_0(\eta )},\ldots ,\frac{N_l(\eta )}{N_0(\eta )}\rangle /\mathbb {Q}=n\). If we can show \(X_\mathcal {A}=V\), then it follows that \(X_\mathcal {A}\) is an irreducible projective differential variety of dimension \(n\).
For any point \(\xi \in (\mathcal {E}^\wedge )^n\), it is clear that \((\xi ;N_0(\xi ),N_1(\xi ),\ldots ,N_l(\xi ))\) is a differential zero of \({\mathcal {J}}\) and consequently \((N_0(\xi ),N_1(\xi ),\ldots ,N_l(\xi ))\in {\mathbb {V}}({\mathcal {J}}_1)=V\). So \(\phi _{\mathcal {A}}(\xi )=(N_0(\xi ),N_1(\xi ),\ldots ,\) \(N_l(\xi ))\in V\). Thus, \(\phi _{\mathcal {A}}\big ((\mathcal {E}^\wedge )^n\big )\subseteq V\) and \(X_{\mathcal {A}}=\overline{\phi _{\mathcal {A}}\big ((\mathcal {E}^\wedge )^n\big )} \subseteq V\) follows. Conversely, since \(\phi _{\mathcal {A}}(\eta )=(1,\frac{N_1(\eta )}{N_0(\eta )},\ldots ,\frac{N_l(\eta )}{N_0(\eta )})\in X_\mathcal {A}\) is a generic point of \(V\), \(V\subseteq X_\mathcal {A}\). Thus, \(V= X_\mathcal {A}\). \(\square \)
Let \(V\) be an irreducible projective differential variety of dimension \(d\) over \(\mathbb {Q}\) with a generic point \(\xi =(\xi _0,\xi _1,\ldots ,\xi _l)\). Suppose \(\xi _0\ne 0\). Let \({\mathbb {L}}_i=\sum _{k=0}^lu_{ik}z_k\,(i=0,\ldots ,d)\) be \(d+1\) generic projective differential hyperplanes. Denote \(\zeta _i=-\sum _{k=1}^lu_{ik}\xi _0^{-1}\xi _k\,(i=0,\ldots ,d)\) and \({\mathbf {u}}_i=(u_{i0},\ldots ,u_{il})\). Then it is proved in [33] that the prime ideal \(\mathbb {I}\big ((\zeta _0,\ldots ,\zeta _d)\big )\) over \(\mathbb {Q}\langle \cup _i{\mathbf {u}}_i\backslash \{u_{i0}\}\rangle \) is of codimension one. That is, there exists an irreducible differential polynomial \(F\in \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_d\}\) such that \(\mathbb {I}\big ((\zeta _0,u_{01},\ldots ,u_{0l};\ldots ;\zeta _d,u_{d1},\ldots ,u_{dl})\big )=\mathrm{sat}(F)\). This \(F\) is defined to be the differential Chow form of \({\mathbb {V}}(\mathcal {I})\) or \(\mathcal {I}\). We list one of its properties which will be used in this section.
Theorem 5.21
[33, Theorem4.7] Let \(F({\mathbf {u}}_{0},{\mathbf {u}}_{1},\ldots ,{\mathbf {u}}_{d})\) be the differential Chow form of \(V\) with \({\mathrm{ord}}(F)=h\) and \(S_{F}=\frac{\partial F}{\partial u_{00}^{(h)}}\) . Suppose that \({\mathbf {u}}_i\) are differentially specialized over \(\mathbb {Q}\) to sets \({\mathbf {v}}_i\subset \mathcal {E}\) and \(\overline{{\mathbb {P}}}_{i}\) are obtained by substituting \({\mathbf {u}}_i\) by \({\mathbf {v}}_i\) in \({\mathbb {P}}_i\,(i=0,\ldots ,d)\). If \(\overline{{\mathbb {P}}}_i=0\,(i=0,\ldots ,d)\) meet \(V\), then \(\mathrm{sat}(F)\) vanishes at \(({\mathbf {v}}_{0},\ldots ,{\mathbf {v}}_{d})\). Furthermore, if \(F({\mathbf {v}}_{0},\ldots ,{\mathbf {v}}_{d})=0\) and \(S_{F}({\mathbf {v}}_{0},\ldots ,{\mathbf {v}}_{d})\ne 0\), then the \(d+1\) differential hyperplanes \(\overline{{\mathbb {P}}}_{i}=0\) \(\,(i=0,\ldots ,d)\) meet \(V\).
The following theorem shows that the sparse differential resultant is closely related to the differential Chow form of \(X_\mathcal {A}\).
Theorem 5.22
Let \(\mathrm{Res}_{\mathcal {A}}\) be the sparse differential resultant of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\) given in (21). Then \(\mathrm{Res}_{\mathcal {A}}\) is the differential Chow form of \(X_\mathcal {A}\) with respect to the generic hyperplanes \({\mathbb {L}}_0,\ldots ,{\mathbb {L}}_n\) given in (23).
Proof
By the proof of Theorem 5.20, \(X_\mathcal {A}\) is an irreducible projective differential variety of dimension \(n\) with a generic point \((1,\frac{N_1(\eta )}{N_0(\eta )},\ldots ,\frac{N_l(\eta )}{N_0(\eta )})\). Let \(\zeta _i=-\sum _{k=1}^lu_{ik}\frac{N_k(\eta )}{N_0(\eta )}\,(i=0,\ldots ,n)\) and \(\zeta =(\zeta _0,u_{01},\ldots ,u_{0l};\ldots ;\zeta _n,u_{n1},\ldots ,u_{nl})\). Then \(\mathrm{sat}(\hbox {{Chow}}(X_\mathcal {A}))=\mathbb {I}(\zeta )\), which is the vanishing differential ideal of \(\zeta \) in \({\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). And by the definition of sparse differential resultant, \(\mathrm{sat}(\hbox {Res}_{\mathcal {A}})=\mathbb {I}(\zeta )\). By Lemma 2.3, \(\hbox {{Chow}}(X_\mathcal {A})\) and \(\hbox {Res}_{\mathcal {A}}\) can only differ at most by a nonzero element in \(\mathbb {Q}\). Thus, \(\hbox {Res}_{\mathcal {A}}\) is just the differential Chow form of \(X_\mathcal {A}\). \(\square \)
We give another characterization of the vanishing of sparse differential resultants below, where the zeros are taken from \(\mathcal {E}\) instead of \(\mathcal {E}^{\wedge }\).
Corollary 5.23
Let \(\overline{{\mathbb {L}}}_i=v_{i0}z_0+v_{i1}z_1+\cdots +v_{il}z_l=0\,(i=0,\ldots ,n)\) be projective differential hyperplanes with \({\mathbf {v}}_i=(v_{i0},\ldots ,v_{il})\in \mathcal {E}^{l+1}\). Denote \({\mathrm{ord}}(\mathrm{Res}_{\mathcal {A}})=h\) and \(S_{\mathbf {R}}=\frac{\partial \mathrm{Res}_{\mathcal {A}}}{\partial u_{00}^{(h)}}\). If \(X_\mathcal {A}\) meets \(\overline{{\mathbb {L}}}_i=0\,(i=0,\ldots ,n)\), then \(\mathrm{Res}_{\mathcal {A}}({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)=0\). And if \(\mathrm{Res}_{\mathcal {A}}({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)=0\) and \(S_{\mathbf {R}}({\mathbf {v}}_0,\ldots ,{\mathbf {v}}_n)\ne 0\), then \(X_\mathcal {A}\) meets \(\overline{{\mathbb {L}}}_i=0\,(i=0,\ldots ,n)\).
Example 5.24
Let \({\mathcal A}={\mathcal A}_0\), where \({\mathcal A}_0\) is given in Example 3.21. Following the proof of Theorem 5.20, let \({\mathcal {J}}=[y_1z_1-y_1'z_0,y_1z_2-y_1^2z_0]\hbox {{:}}\mathbb {m}\). It is easy to show that \(X_\mathcal {A}\) is the general component of \(z_1z_2-(z_0z_2'-z_0'z_2)\), that is, \(X_\mathcal {A}={\mathbb {V}}(\mathrm{sat}(z_1z_2-(z_0z_2'-z_0'z_2)))\). And \(\mathrm{Res}_\mathcal {A}\) is equal to the differential Chow form of \(X_\mathcal {A}\).
By Theorems 5.20 and 5.22, property 4) of Theorem 1.2 is proved.
6 A Single Exponential Algorithm to Compute the Sparse Differential Resultant
In this section, we give an algorithm to compute the sparse differential resultant for a Laurent differentially essential system with single exponential complexity. The idea is first to estimate the order and degree bounds for the resultant and then to use linear algebra to find the coefficients of the resultant.
6.1 Order Bounds of Sparse Differential Resultants in Terms of Jacobi Numbers
In this section, we will give an order bound for the sparse differential resultant in terms of the Jacobi number of the given system.
Let \(A=(a_{ij})\) be an \(n\times n\) matrix where \(a_{ij}\) is an integer or \(-\infty \). A diagonal sum of \(A\) is any sum \(\sum _{i=1}^n a_{i\sigma (i)}\) where \(\sigma \) a permutation of \(1,\ldots ,n\). If \(B\) is an \(m\times n\) matrix with \(w=\min \{m,n\}\), then a diagonal sum of \(B\) is a diagonal sum of any \(w\times w\) sub-matrix of \(A\). The Jacobi number of \(B\) is defined as the maximal diagonal sum of \(B\), denoted by \(\mathrm{Jac}(B)\).
Let \({\mathbb {P}}=\{{\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\}\) and \(\widehat{{\mathbb {P}}}=\{{\mathbb {P}}_0^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {\tiny N}}\}\) be given in (3) and (5), respectively. Let \({\mathrm{ord}}({\mathbb {P}}_i^{\text {N}},y_j)=e_{ij}\,(i=0,\ldots ,n;j=1,\ldots ,n)\) and \({\mathrm{ord}}({\mathbb {P}}_i^{\text {N}},{\mathbb {Y}})=e_i\). We call the \((n+1)\times n\) matrix \(E=(e_{ij})\) the order matrix of \({\mathbb {P}}_0,\ldots ,{\mathbb {P}}_n\). By \(E_{\hat{i}}\), we mean the sub-matrix of \(E\) obtained by deleting the \((i+1)\)th row from \(E\). Let \(\widehat{{\mathbb {P}}}_{\hat{i}}=\widehat{{\mathbb {P}}}\backslash \{{\mathbb {P}}_i^{\text {N}}\}\). We call \(\text { J}_i=\mathrm{Jac}(E_{\hat{i}})\) the Jacobi number of the system \(\widehat{{\mathbb {P}}}_{\hat{i}}\), also denoted by \(\mathrm{Jac}(\widehat{{\mathbb {P}}}_{\hat{i}})\). Before giving an order bound for the sparse differential resultant in terms of Jacobi numbers, we first give several lemmas.
Lemma 6.1
Let \({\mathbb {P}}\) be a Laurent differentially essential system and \({\mathbf {k}}=(k_0,k_1,\ldots ,k_n)\in \mathbb {Z}_{\ge 0}^{n+1}\) be a vector satisfying 26. Then \(\mathrm{ord}({\mathbf {R}},{\mathbf {u}}_i)\le k_i\) for each \(i=0,\ldots ,n\).
Proof
Denote \(\mathbb {m}^{[{\mathbf {k}}]}\) to be the set of all monomials in variables \({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]}\). Suppose \({\mathcal {I}}=(\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]})\hbox {{:}}\mathbb {m}^{[{\mathbf {k}}]}=\)
\(\{f\in \mathbb {Q}[{\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},{\mathbf {u}}^{[{\mathbf {k}}]}]\big | \exists M\in \mathbb {m}^{[{\mathbf {k}}]}, Mf\in (\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]}) \}\). Denote \(U={\mathbf {u}}^{[{\mathbf {k}}]}\backslash \cup _{i=0}^nu_{i0}^{[k_i]}\). Assume \({\mathbb {P}}_i^{\text {N}}=\sum _{k=0}^{l_i}u_{ik} N_{ik}\,(i=0,\ldots ,n)\). Let \(\zeta _{il}=-(\sum _{k=1}^{l_i}u_{ik}N_{ik}/N_{i0})^{(l)}\) for \(i=0,1,\ldots ,n;l=0,1,\ldots ,k_i\). Denote \(\bar{\zeta } =(U,\zeta _{0k_0},\ldots ,\zeta _{00},\ldots ,\zeta _{nk_n},\ldots ,\zeta _{n0})\). It is easy to show that \(({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},\bar{\zeta } )\) is a generic point of \({\mathcal {I}}\). Indeed, it is clear that each polynomial in \({\mathcal {I}}\) vanishes at \(({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},\bar{\zeta } )\). And if \(f\) is an arbitrary polynomial in \(\mathbb {Q}[{\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},{\mathbf {u}}^{[{\mathbf {k}}]}]\) such that \(f({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},\bar{\zeta } )=0\), substitute \(u_{i0}^{(l)}=\big (({\mathbb {P}}_i^{\text {N}}-\sum _{k=1}^{l_i}u_{ik}N_{ik})/N_{i0}\big )^{(l)}\) into \(f\), then we have \(\prod _{i=0}^nN_{i0}^{a_i}f\,\equiv \,f_1,\mathrm{{mod}}\,(\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]}),\) where \(f_1\in \mathbb {Q}[{\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},U]\). Clearly, \(f_1=0\) and \(f\in {\mathcal {I}}\) follows.
Let \({\mathcal {I}}_1={\mathcal {I}}\cap \mathbb {Q}[{\mathbf {u}}^{[{\mathbf {k}}]}]\). Then \({\mathcal {I}}_1\) is a prime ideal with \(\bar{\zeta } \) as its generic point. Since \(\mathbb {Q}(\bar{\zeta } )\subset \mathbb {Q}({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},U)\), \(\mathrm{Codim}({\mathcal {I}}_1)=|U|+\sum _{i=0}^n(k_i+1)-\hbox {{tr.deg}}\,\mathbb {Q}(\bar{\zeta } )/\mathbb {Q}\ge |U|+|\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]}|-\hbox {{tr.deg}}\,\mathbb {Q}({\mathbb {Y}}^{[\widetilde{\mathbf {k}}]},U)/\mathbb {Q}=|\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]}|-|{\mathbb {Y}}^{[\widetilde{\mathbf {k}}]}|\ge 1\). Thus, \({\mathcal {I}}_1\ne (0)\). Suppose \(f\) is any nonzero polynomial in \({\mathcal {I}}_1\). Clearly, \({\mathrm{ord}}(f,{\mathbf {u}}_{i})\le k_i\). Since \({\mathcal {I}}_1\subset \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap \mathbb {Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}=\mathrm{sat}({\mathbf {R}})\), \(f\in \mathrm{sat}({\mathbf {R}})\). Note that \({\mathbf {R}}\) is a characteristic set of \(\mathrm{sat}({\mathbf {R}})\) w.r.t. any ranking by Lemma 2.3. Thus, \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_{i})\le {\mathrm{ord}}(f,{\mathbf {u}}_i)\le k_i\). \(\square \)
Lemma 6.2
Let \({\mathbb {P}}\) be a Laurent differentially essential system and \(\text { J}_i\ge 0\) for each \(i=0,\ldots ,n\). Then \(\sum _{j=1}^n\mathrm{max}(e_{0j}+\text { J}_0,\cdots ,e_{nj}+\text { J}_{n})=\sum _{i=0}^n\text { J}_{i}\).
Proof
Let \(E = (e_{ij})\) be the \((n+1)\times n\) order matrix of \(\widehat{{\mathbb {P}}}\), where \(e_{ij} = {\mathrm{ord}}({\mathbb {P}}_i^{\text {N}},y_j)\). Without loss of generality, suppose \(\text { J}_{0} = e_{11} + e_{22} + \cdots + e_{nn}\).
Firstly, we will show that for each \(k\ne 1\), \(e_{11}+\text { J}_1 \ge e_{k1}+\text { J}_k\). Since \(\text { J}_k\) is the Jacobi number of \(\widehat{{\mathbb {P}}}_{\hat{k}}\) and \(k\ne 1\), \(\text { J}_k\) has a summand of the form \(e_{1p_1}\). Let \(m\) be the biggest \(s\) such that \(e_{1p_1}+e_{p_1p_2}+ \cdots + e_{p_{s-1}p_s}\) is a partial sum of successive summands in \(\text { J}_k\) and denote \(T_0=e_{1p_1}+e_{p_1p_2}+ \cdots + e_{p_{m-1}p_m}\). Suppose \(\text { J}_k = T_0 + T_1\). Since \(\text { J}_k\) is a diagonal sum, \(p_i\ne p_j\) for \(1\le i < j\). For otherwise, \(\text { J}_k\) contains \(e_{p_{i-1}p_i}\) and \(e_{p_{j-1}p_i}\) as summands \((p_0=1)\), a contradiction. Also note that \(p_i\ne 0\) for \(1\le i \le m\). Now we claim that \(p_m\) is either equal to \(1\) or equal to \(k\). Indeed, if \(p_m=1\) or \(p_m=k\), \(T_0\) cannot be any longer and these two cases may happen. But if \(p_m\ne 1\) and \(p_m\ne k\), then we can add another summand \(e_{p_{m}p_{m+1}}\) to \(T_0\), which contradicts the fact that \(T_0\) is the longest one. So \(p_m=1\) or \(k.\) Now three cases are considered.
Case 1) If \(p_1=1\), \(\text { J}_k = e_{11}+T_1\) and \(e_{k1}+\text { J}_k = e_{11} + e_{k1} + T_1\). Since \(e_{k1} + T_1\) is a diagonal sum of \(\widehat{{\mathbb {P}}}_{\hat{1}}\), \(e_{k1} + T_1 \le \text { J}_1\). Thus, \(e_{11}+\text { J}_1 \ge e_{k1}+\text { J}_k\).
Case 2) If \(p_m=1\) for \(m>1\), \(T_0 = e_{1p_1}+e_{p_1p_2}+\cdots +e_{p_{m-1}1}\). Since \(\text { J}_{0} = e_{11}+\cdots + e_{nn}\), \(T_0 \le e_{11} + e_{p_1p_1} + \cdots + e_{p_{m-1}p_{m-1}}\). For otherwise, since \(p_i\ne 0\), \(T_0+\sum _{k\in \{2,\ldots ,n\}\backslash \{p_1,\ldots ,p_{m-1}\}}e_{kk}\) is a diagonal sum of \(\widehat{{\mathbb {P}}}_{\hat{0}}\) which is greater than \(\text { J}_0\), a contradiction. Then \(e_{k1}+\text { J}_k = e_{k1}+T_0 + T_1 \le e_{k1}+e_{11} + e_{p_1p_1} + \cdots + e_{p_{m-1}p_{m-1}} + T_1\le e_{11}+\text { J}_1\), where the last inequality follows from the fact that \(e_{k1}+e_{p_1p_1} + \cdots + e_{p_{m-1}p_{m-1}} + T_1\) is a diagonal sum of \(\widehat{{\mathbb {P}}}_{\hat{1}}\).
Corollary 6.3
Let \({\mathbb {P}}\) be a Laurent differentially essential system and \(\text { J}_i\ge 0\) for each \(i=0,\ldots ,n\). Then \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)\le \text { J}_i\,(i=0,\ldots ,n)\).
The above corollary shows that when all the Jacobi numbers are not less that \(0\), then Jacobi numbers are order bounds for the sparse differential resultant. In the following, we deal with the remaining case when some \(\text { J}_i=-\infty \). To this end, two more lemmas are needed.
Lemma 6.4
[9, 32] Let \(E\) be an \(m\times n\) matrix whose entries are \(0\)’s and \(1\)’s. Let \(\mathrm{Jac}(E)=\text { J}<\min \{m,n\}\). Then \(E\) contains an \(a\times b\) zero sub-matrix with \(a+b=m+n-\text { J}\).
Lemma 6.5
Proof
Now, we are ready to prove the main result of this section.
Theorem 6.6
Proof
Corollary 6.7
Let \({\mathbb {P}}\) be rank essential. Then \(\text { J}_i\ge 0\) for \(i=0,\ldots ,n\) and \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i) \le \text { J}_i\).
Proof
From the proof of Theorem 6.6, if \(\hbox {J}_i=-\infty \) for some \(i\), then \({\mathbb {P}}\) contains a proper differentially essential sub-system, which contradicts Theorem 4.20. Therefore, \(\text { J}_i\ge 0\) for \(i=0,\ldots ,n\). \(\square \)
By Theorem 6.6, \(\text { J}_i\ge 0\) is a necessary condition for \({\mathbf {u}}_i\) appearing in \({\mathbf {R}}\). The following example shows that this condition is not sufficient.
Example 6.8
We conclude this section by giving two improved order bounds based on the Jacobi bound given in Theorem 6.6.
For each \(j\in \{1,\ldots ,n\}\), let \(\underline{o}_j=\min \{k\in \mathbb {N}| \,\exists \, i\, \text {s.t.}\, \mathrm{deg}({\mathbb {P}}_i^{\text {N}},y_j^{(k)})>0\}\). In other words, \(\underline{o}_j\) is the smallest number such that \(y_j^{(\underline{o}_j)}\) occurs in \(\{{\mathbb {P}}_0^{\text {N}},\ldots ,{\mathbb {P}}_n^{\text {N}}\}\). Let \(B=(e_{ij}-\underline{o}_j)\) be an \((n+1)\times n\) matrix. We call \(\bar{J}_i=\mathrm{Jac}(B_{\hat{i}})\) the modified Jacobi number of the system \({\mathbb {P}}_{\hat{i}}\). Denote \(\underline{\gamma }=\sum _{j=1}^n\underline{o}_j\). Clearly, \(\bar{J}_i=\text { J}_i-\underline{\gamma }.\) Then we have the following result.
Theorem 6.9
Proof
Remark 6.10
Let \({\mathbf {k}}=(e-e_0,e-e_1,\ldots ,e-e_n)\) where \(e=\sum _{i=0}^n e_i\). Clearly, \(|\widehat{{\mathbb {P}}}^{[{\mathbf {k}}]}|=ne+n+1=|{\mathbb {Y}}^{[e]}|+1 \ge |{\mathbb {Y}}^{[\widetilde{\mathbf {k}}]}|+1\). Then by Lemma 6.1, \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i) \le e-e_i\le s-s_i\). Here \(s_i\) is the order of \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) and \(s=\sum _{i=0}^ns_i\). If \(L_i = e-e_i-\gamma ({\mathbb {P}})\) where \(\gamma ({\mathbb {P}})=\sum _{j=1}^n (\underline{o}_j + \overline{e}_j)\) and \(\overline{e}_j = \min _i \{e_i-{\mathrm{ord}}({\mathbb {P}}^{\text {N}}_i,y_j) | {\mathrm{ord}}({\mathbb {P}}^{\text {N}}_i,y_j)\ne -\infty \}\). By [43], \((L_0,\ldots ,L_n)\) also consists of a solution to 26. Then \(\mathrm{deg}({\mathbf {R}},{\mathbf {u}}_i)\le L_i\). One can easily check that \(\bar{\text { J}}_i\le L_i \le e-e_i\) for each \(i\), and the modified Jacobi bound is better than the other two bounds as shown by the following example.
Example 6.11
Now, we assume that \({\mathbb {P}}\) is a Laurent differentially essential system which is not rank essential. Let \({\mathbf {R}}\) be the sparse differential resultant of \({\mathbb {P}}\). We will give a better order bound for \({\mathbf {R}}\). By Theorem 4.20, \({\mathbb {P}}\) contains a unique rank essential sub-system \({\mathbb {P}}_{I}\). Without loss of generality, suppose \(I = \{ 0,\ldots , r\}\) with \(r< n\). Let \(E_I\) be the order matrix of \({\mathbb {P}}_I\) and for \(i=0,\ldots ,r\), let \((E_{I})_{\hat{i}}\) be the matrix obtained from \(E_I\) by deleting the \((i+1)\)th row. Note that \((E_{I})_{\hat{i}}\) is an \(r\times n\) matrix. Then we have the following result.
Theorem 6.12
Proof
It suffices to show that \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i) \le \mathrm{Jac}((E_{I})_{\hat{i}})\) for \(i=0,\ldots ,r\). Let \({\mathbb {L}}_i = u_{i0} + \sum _{j=1}^n u_{ij}y_j\) for \(i=r+1,\ldots ,n\). Since \({\mathbb {P}}_{I}\) is rank essential, there exist \(\frac{N_{ik_i}}{N_{i0}}\,( i= 1,\ldots ,r)\) such that their symbolic support matrix \(B\) is of full rank. Without loss of generality, we assume that the \(r\)th principal sub-matrix of \(B\) is of full rank. Consider a new Laurent differential polynomial system \(\widetilde{\mathbb {P}} = {\mathbb {P}}_{I} \cup \{{\mathbb {L}}_{r+1},\ldots ,{\mathbb {L}}_{n}\}\). This system is also Laurent differentially essential since the symbolic support matrix of \(\frac{N_{1k_1}}{N_{10}},\ldots , \frac{N_{rk_r}}{N_{r0}},y_{r+1},\ldots ,y_n\) is of full rank. And \({\mathbf {R}}\) is also the sparse differential resultant of \(\widetilde{\mathbb {P}}\), for \({\mathbb {P}}_I\) is the rank essential sub-system of \(\widetilde{\mathbb {P}}\). The order vector of \({\mathbb {L}}_i\) is \((0,\ldots ,0)\) for \(i=r+1,\ldots ,n\). So \(\mathrm{Jac}(\widetilde{\mathbb {P}}_{\hat{i}})=\mathrm{Jac}((E_{I})_{\hat{i}})\) for \(i=0,\ldots ,r\). By Theorem 6.6, \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i) \le \mathrm{Jac}((E_{I})_{\hat{i}})\) for \(i=0,\ldots ,r\).\(\square \)
Example 6.13
6.2 Degree Bounds of Sparse Differential Resultants
In this section, we give an upper bound for the degree of the sparse differential resultant, which is crucial to our algorithm to compute the sparse resultant. We will recall several properties about the degrees of ideals in the algebraic case.
Let \(\mathcal {K}\) be a field and \(\overline{\mathcal {K}}\) its algebraic closure. Let \(\mathcal {I}\) be a prime ideal in \(\mathcal {K}[{\mathbb {X}}]=\mathcal {K}[x_1,\ldots ,x_n]\) with \(\hbox {{dim}}(\mathcal {I})=d\) and \(V\subset \overline{\mathcal {K}}^n\) be the irreducible variety defined by \(\mathcal {I}\). The degree of \(\mathcal {I}\) or \(V\), denoted by \(\mathrm{deg}(\mathcal {I})\) or \(\mathrm{deg}(V)\), is defined as the number of solutions of the zero-dimensional prime ideal \((\mathcal {I},{\mathbb {L}}_1,\ldots ,{\mathbb {L}}_d)_{\mathcal {K}_1[{\mathbb {X}}]}\) in the algebraic closure of \(\mathcal {K}_1\), where \({\mathbb {L}}_i = u_{i0}+\sum _{j=1}^n u_{ij} x_j \,(i=1,\ldots ,d)\) are \(d\) generic hyperplanes and \(\mathcal {K}_1=\mathcal {K}((u_{ij})_{1\le i\le n; 0\le j \le n})\) [23].
The following result gives a relation between the degree of an ideal and that of its elimination ideal, which has been proved in [34, Theorem2.1] and is also a consequence of [21, Lemma 2].
Lemma 6.14
Let \(\mathcal {I}\) be a prime ideal in \(\mathcal {K}[{\mathbb {X}}]\) and \(\mathcal {I}_r=\mathcal {I}\cap \mathcal {K}[x_1,\ldots ,x_r]\) for any \(1\le r\le n\). Then \(\mathrm{deg}(\mathcal {I}_r)\le \mathrm{deg}(\mathcal {I})\).
The notion of degree can be defined for more general sets of \(\overline{\mathcal {K}}^n\) other than varieties. A constructible set of \(\overline{\mathcal {K}}^n\) is a Boolean combination of varieties in \(\overline{\mathcal {K}}^n\), that is, a finite union of quasi-varieties in \(\overline{\mathcal {K}}^n\). Let \(X\subset \overline{\mathcal {K}}^n\) be constructible and \(V_1,\ldots ,V_l\) be the set of the irreducible components of the Zariski closure of \(X\). The degree of \(X\) is defined to be the sum of the degrees of \(V_i\), that is, \(\mathrm{deg}(X)=\sum _{i=1}^l \mathrm{deg}(V_i)\). The following lemma shows how degree behaves under intersections.
Lemma 6.15
[21, Theorem1] Let \(V_1,\ldots ,V_r\,(r\ge 2)\) be a finite number of constructible sets in \(\overline{\mathcal {K}}^n\). Then \(\mathrm{deg}(V_1\cap \cdots \cap V_r)\le \prod _{i=1}^r\mathrm{deg}(V_i).\)
We now give a degree bound for the sparse differential resultant. The idea is to express \(({\mathbf {R}})\) as the elimination ideal of certain algebraic ideals generated by \({\mathbb {P}}_i^{(j)}\) and use Lemmas 6.14 and 6.15 to estimate the degree of \({\mathbf {R}}\).
Theorem 6.16
- 1) :
-
\(\mathrm{deg}({\mathbf {R}})\le \prod _{i=0}^n (m_i+1)^{h_i+1}\le (m+1)^{\sum _{i=0}^n(\text { J}_i+1)}\), where \(m=\mathrm{max}_i\{m_i\}\).
- 2) :
-
\({\mathbf {R}}\) has a representationwhere \(G_{ij}\in {\mathbb Q}[{\mathbf {u}}_0^{[h_0]},\ldots ,{\mathbf {u}}_n^{[h_n]},y_1^{[t_1]},\ldots ,y_n^{[t_n]}]\) with \(t_j=\mathrm{max}_{i=0}^n\{h_i+e_{ij}\}\) such that \(\mathrm{deg}(G_{ij}({\mathbb {P}}_{i}^{\text {N}})^{(j)})\le [m+1+\sum _{i=0}^n(h_i+1)\mathrm{deg}(N_{i0})]\mathrm{deg}({\mathbf {R}})\).$$\begin{aligned} \prod _{i=0}^n N_{i0}^{(h_i+1)\mathrm{deg}({\mathbf {R}})}\cdot {\mathbf {R}}=\sum _{i=0}^n\sum _{j=0}^{h_i}G_{ij}\big ({\mathbb {P}}_{i}^{\text {N}}\big )^{(j)} \end{aligned}$$(27)
Proof
2) In \({\mathbf {R}}\), let \(u_{i0}\,(i=0,\ldots ,n)\) be replaced, respectively, by \(\big ({\mathbb {P}}_{i}^{\text {N}}-\sum _{k=1}^{l_i}u_{ik}N_{ik}\big )/N_{i0}\) and let \({\mathbf {R}}\) be expanded as polynomials in \({\mathbb {P}}_{i}^{\text {N}}\) and their derivatives with coefficients in \(\mathbb {Q}\{{\mathbb {Y}}^{\pm };{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\). We obtain \({\mathbf {R}}=\sum \limits _{M}q_M\cdot M({\mathbf {u}};u_{00},\ldots ,u_{n0})=\sum \limits _{M}q_M\cdot M\big ({\mathbf {u}};\frac{ {\mathbb {P}}_{0}^{\text {N}}-\sum _{k=1}^{l_0}u_{0k}N_{0k}}{N_{00}},\ldots ,\frac{{\mathbb {P}}_{n}^{\text {N}}-\sum _{k=1}^{l_n}u_{nk}N_{nk}}{N_{n0}}\big ) =\big (\sum \limits _{i=0}^n\sum \limits _{k=0}^{h_i}G_{ik}({\mathbb {P}}_{i}^{\text {N}})^{(k)}+T\big )\big /\prod \limits _{i=0}^nN_{i0}^{a_i}\), where \(q_M\in {\mathbb Q}\), \(a_i\in \mathbb {N}\), \(G_{ik}\in {\mathbb Q}[{\mathbf {u}}_0^{[h_0]},\ldots ,{\mathbf {u}}_n^{[h_n]},{\mathbb {Y}}^{[\mathbf t ]}]\) and \(T\in {\mathbb Q}\{{\mathbf {u}},{\mathbb {Y}}\}\) is free from \(u_{i0}\). So \(\prod \limits _{i=0}^nN_{i0}^{a_i}{\mathbf {R}}=\sum \limits _{i=0}^n\sum \limits _{k=0}^{h_i}G_{ik}({\mathbb {P}}_{i}^{\text {N}})^{(k)}+T\), and \(T\in \mathcal {I}_{{\mathbb {Y}},{\mathbf {u}}}\cap {\mathbb Q}\{{\mathbf {u}},{\mathbb {Y}}\}=\{0\}\) follows. Thus, \(T=0\) and we obtain a representation for \({\mathbf {R}}\) of the form (27).
Example 6.17
In Example 3.19, \(\text { J}_0=2\), \(\text { J}_1=\text { J}_2=1\) and \(m_0=m_1=m_2=2\). The expression of \({\mathbf {R}}\) shows that \(h_0={\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_0)=1< \text { J}_0\), \(h_i={\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)=0<\text { J}_i\,(i=1,2)\) and \(\mathrm{deg}({\mathbf {R}})=5<<3^4=\prod _{i=0}^2(m_i+1)^{h_i+1}.\)
With Theorem 6.16, properties 6) and 7) of Theorem 1.2 are proved.
6.3 A Single Exponential Algorithm to Compute Sparse Differential Resultants
If a polynomial \(R\) is a linear combination of some known polynomials \(F_i(i=1,\ldots ,s)\), that is, \(R=\sum _{i=1}^s H_i F_i\), and we know the upper bounds of the degrees of \(R\) and \(H_iF_i\), then a general idea to estimate the computational complexity of \(R\) is to use linear algebra to find the coefficients of \(R\).
For the sparse differential resultant, its degree bound and the degrees of the expressions in the linear combination are given in Theorem 6.16.
Theorem 6.18
- 1)
In terms of a degree bound \(D\) of \({\mathbf {R}}\), the algorithm needs at most \(O\Big (\frac{\big [\big (m(\text { J}+n+2)+1\big )D\big ]^{O(l\text { J}+l)}}{n^{n}}\Big )\) \({\mathbb Q}\)-arithmetic operations, where \(l=\sum _{i=0}^n(l_i+1)\) is the size of the system.
- 2)
The algorithm needs at most \(O\big ({(\text { J}+n+2)^{O(l \text { J}+l)}(m+1)^{O((l\text { J}+l)(\text { J}+n+2))}}/{n^{n}}\big )\) \({\mathbb Q}\)-arithmetic operations.
Proof
The algorithm finds a \(P\in {\mathbb Q}\{{\mathbf {u}}_0,\ldots ,{\mathbf {u}}_n\}\) satisfying (27), which has the smallest order and the smallest degree among those with the same order. Existence for such a differential polynomial is guaranteed by Theorem 6.16. Such a \(P\) is in \(\mathrm{sat}({\mathbf {R}})\) by (10). Since each differential polynomial in \(\mathrm{sat}({\mathbf {R}})\) not equal to \({\mathbf {R}}\) either has greater order than \({\mathbf {R}}\) or has the same order but greater degree than \({\mathbf {R}}\), \(P\) must be \({\mathbf {R}}\) (up to a factor in \(\mathbb {Q}\)).
We will estimate the complexity of the algorithm below. Denote \(D\) to be the degree bound of \({\mathbf {R}}.\) By Theorem 6.16, \(D\le (m+1)^{\sum _{i=0}^n(\text { J}_i+1)}=(m+1)^{\text { J}+n+1}\), where \(\text { J}=\sum _{i=0}^n\text { J}_i\). In each loop of Step 3, the complexity of the algorithm is clearly dominated by Step 3.1.2, where we need to solve a system of linear equations \(\mathcal {P}=0\) over \({\mathbb Q}\) in \({\mathbf {c}}_{0}\) and \({\mathbf {c}}_{ij}\). It is easy to show that \(|{\mathbf {c}}_{0}|={d+L_1-1\atopwithdelims ()L_1-1}\) and \(|{\mathbf {c}}_{ij}|={d_1-m_i-1+L_1+L_2\atopwithdelims ()L_1+L_2}\), where \(L_1=|U|=\sum \limits _{i=0}^n (h_i+1)(l_i+1)\), \(L_2=|{\mathbb {Y}}^{[\mathbf t ]}|=\sum \limits _{j=1}^n(\mathrm{max}_{i}\{h_i+e_{ij}\}+1)\) and \(d_1=[m+1+\sum _{i=0}^n(h_i+1)m_{i0}]d\). Then \(\mathcal {P}=0\) is a linear equation system with \(W_1={d+L_1-1\atopwithdelims ()L_1-1}+\sum _{i=0}^n(h_i+1){d_1-m_i-1+L_1+L_2\atopwithdelims ()L_1+L_2}\) variables and \(W_2={d_1+L_1+L_2\atopwithdelims ()L_1+L_2}\) equations. To solve it, we need at most \((\mathrm{max}\{W_1, W_2\})^{\omega }\) arithmetic operations over \({\mathbb Q}\), where \(\omega \) is the matrix multiplication exponent and the currently best known \(\omega \) is 2.376.
The iteration in Step 3.1.2 may go through \(1\) to \(\prod _{i=0}^n(m_i+1)^{h_i+1}\le (m+1)^{\sum _{i=0}^n(\text { J}_i+1)}\), and the iteration in Step 3.1 at most will repeat \(\prod _{i=0}^n(\text { J}_i+1)\) times. And by Theorem 6.16, Step 3 may loop from \(o=0\) to \(\sum _{i=0}^n\text { J}_i\). In the whole algorithm, \(L_1\le \sum \limits _{i=0}^n (\text { J}_i+1)(l_i+1)\le l\text { J}+l\), \(L_2=|{\mathbb {Y}}^{[\mathbf t ]}|\le \sum \limits _{j=1}^n(\mathrm{max}_{i}\{\text { J}_i+e_{ij}\}+1)=\text { J}+n\) by Lemma 6.2, and \(d_1\le [m+1+\sum _{i=0}^n(\text { J}_i+1)m_{i0}]D=\big (m(\text { J}+n+2)+1\big )D\). Thus, \(W_1\le {D+l\text { J}+l-1\atopwithdelims ()l\text { J}+l-1}+\sum _{i=0}^n(\text { J}_i+1){ (m(\text { J}+n+2)+1)D-m_i-1+l\text { J}+l+\text { J}+n \atopwithdelims ()l\text { J}+l+\text { J}+n}\) and \(\mathrm{max}\{W_1,W_2\}\le (\text { J}+n+2){[m(\text { J}+n+2)+1]D+l\text { J}+l+\text { J}+n \atopwithdelims ()l\text { J}+l+\text { J}+n}\).
Since \(l\ge 2(n+1)\), the complexity bound is \(O\big ({\big [(m(\text { J}+n+2)+1)D\big ]^{O(l\text { J}+l)}}/{n^{n}}\big )\). Our complexity assumes an \(O(1)\)-complexity cost for all field operations over \(\mathbb {Q}\). Thus, the complexity follows. Now 1) is proved. To prove 2), we just need to replace \(D\) by the degree bound for \({\mathbf {R}}\) in Theorem 6.16 in the complexity bound in 1). \(\square \)
Example 6.19
Let \(n=1\), \({\mathbb {P}}_0=u_{00}+u_{01}y' \), and \( {\mathbb {P}}_1=u_{10}+u_{11}y'\). We use this simple example to illustrate Algorithm SDResultant. Here, \(m_{i0}=0, m=1\), \(J_0=J_1=1\). In step 3.1, \(o=0\) and \((h_0,h_1)=(0,0)\). So \(U=\{u_{00},u_{01},u_{10},u_{11}\}\) and \({\mathbb {Y}}^{[\mathbf t ]}=\{y,y'\}\). We first execute steps 3.1.2.1 to 3.1.2.7 for \(d=1\). Set \({\mathbf {R}}_0=c_{01}u_{00}+c_{02}u_{01}+c_{03}u_{10}+c_{04}u_{11}\) and \({\mathbf {c}}_0=(c_{01},c_{02},c_{03},c_{04})\). Set \(G_{i0}=c_{i01}\) and \({\mathbf {c}}_{i0}=(c_{i01})\) for \(i=0, 1\). In step 3.1.2.5, since \({\mathbf {R}}_0-G_{00}{\mathbb {P}}_0-G_{10}{\mathbb {P}}_1=(c_{01}-c_{001})u_{00} +c_{02}u_{01}+(c_{03}-c_{101})u_{10}+c_{04}u_{11}-c_{001}u_{01}y' -c_{101}u_{11}y'\), \(\mathcal {P}=0\) consists of equations \(\{c_{01}-c_{001}=0, c_{02}=0, c_{03}-c_{101}=0, c_{04}=0, c_{001}=0, c_{101}=0\}\). \(\mathcal {P}=0\) has a unique solution \({\mathbf {c}}=(0,0,0,0)\) and \(c_{i01}=0\). Then \({\mathbf {R}}=0\).
Next, we execute steps 3.1.2.1 to 3.1.2.7 for \(d=2\). Set \({\mathbf {R}}_0=c_{01}u_{00}u_{10}+c_{02}u_{00}u_{11} +c_{03}u_{01}u_{10}+c_{04}u_{01}u_{11}+ c_{05}u_{00}^2+c_{06}u_{00}u_{01}+c_{07}u_{01}^2 +c_{08}u_{10}^2+c_{09}u_{10}u_{11}+ c_{0,10}u_{11}^2\), and \({\mathbf {c}}_0=(c_{01},\ldots ,c_{0,10})\). Set \(\{M_1,\ldots ,M_{28}\} \) to be the set of monomials in \(U\) and \({\mathbb {Y}}^{[\mathbf t ]}\) of degree not greater than 2. Let \(G_{i0}=\sum _{j=1}^{28}c_{i0j}M_{j}\) and \({\mathbf {c}}_{i0}=(c_{i01},\ldots ,c_{i0,28})\) for \(i=0, 1\). Regarding \(T={\mathbf {R}}_0-G_{00}{\mathbb {P}}_0-G_{10}{\mathbb {P}}_1\) as polynomials in \(U\) and \({\mathbb {Y}}^{[\mathbf t ]}\), let \(\mathcal {P}\) be the set of coefficients of \(T\), which are linear polynomials in \({\mathbb Q}[{\mathbf {c}}_{0},{\mathbf {c}}_{00},{\mathbf {c}}_{10}]\). Then \(\mathcal {P}=0\) consists of at most \({10 \atopwithdelims ()4}\) linear equations in \(66\) variables \({\mathbf {c}}_{0},{\mathbf {c}}_{00}\), and \({\mathbf {c}}_{10}\) with integral coefficients. Solving \(\mathcal {P}=0\), we obtain \({\mathbf {c}}_0=(0,q,-q,0,0,0,0,0,0,0)\), where \(q\in {\mathbb Q}\). Thus, the algorithm returns \({\mathbf {R}}=u_{00}u_{11}-u_{01}u_{10}\).
Remark 6.20
By Remark 4.21, we can compute a rank essential set \(I\) and the algorithm can be improved by only considering the Laurent differential polynomials \({\mathbb {P}}_i\,(i\in I)\) in the linear combination of the sparse differential resultant.
6.4 Degree Bounds of Differential Resultants in Terms of Mixed Volumes
The degree bound given in Theorem 6.16 is essentially a Bézout type bound. In this section, a BKK style degree bound for the differential resultant will be given, which is the sum of the mixed volumes of certain polytopes generated by the supports of certain differential polynomials and their derivatives.
Definition 6.22
-
A collection of \(\{\mathcal {B}_i\}_{i\in \text { I}}\), or \(\{{\mathbb {F}}_i\}_{i\in \text {I}}\), is said to be algebraically independent if \(\hbox {{tr.deg}}\,\mathbb {Q}({\mathbf {c}})({\mathbb {F}}_i-c_{i0}\,|\,i\in \text { I})/\mathbb {Q}({\mathbf {c}})=|\text {I}|\). Otherwise, they are said to be algebraically dependent.
-
A collection of \(\{\mathcal {B}_i\}_{i\in \text { I}}\) is said to be essential if \(\{\mathcal {B}_i\}_{i\in \text {I}}\) is algebraically dependent and for each proper subset \(\text {J}\) of I, \(\{\mathcal {B}_i\}_{i\in J}\) are algebraically independent.
In the case that \(\{\mathcal {B}_0,\ldots ,\mathcal {B}_n\}\) is essential, the degree of the sparse resultant can be described by mixed volumes.
Theorem 6.23
The mixed volume of the Newton polytopes of a polynomial system is important in that it relates to the number of solutions of these polynomial equations contained in \((\mathbb {C}^*)^n \), which is the famous BKK bound [2].
The following lemma shows that the BKK bound is always smaller than the Bézout bound.
Lemma 6.24
Let \(f_1,\ldots ,f_n\) be polynomials in \(\mathbb {C}[x_1,\ldots ,x_n]\) and \(\mathcal {Q}_i\) be the Newton polytope of \(f_i\) in \(\mathbb {R}^n\). Then \(\mathcal {M}(\mathcal {Q}_1,\ldots ,\mathcal {Q}_n)\le \prod _{i=1}^n\mathrm{deg}(f_i)\).
Proof
Let \(\Delta \) be the standard unitary simplex of \(\mathbb {R}^n\). Then for each \(i\), \(\mathcal {Q}_i\subset d_i\Delta \), where \(d_i=\mathrm{deg}(f_i)\). By the monotonicity of the mixed volume, \(\mathcal {M}(\mathcal {Q}_1,\ldots ,\mathcal {Q}_n)\le \mathcal {M}(d_1\Delta ,\ldots ,d_n\Delta )=\prod _{i=1}^nd_i\cdot \mathcal {M}(\Delta ,\ldots ,\Delta )=\prod _{i=1}^nd_i\). \(\square \)
The following theorem gives a BKK style upper bound for degrees of differential resultants, the proof of which is not valid for sparse differential resultants.
Theorem 6.25
Proof
By [17, Theorem6.8], \({\mathrm{ord}}({\mathbf {R}},{\mathbf {u}}_i)=s-s_i\,(i=0,\ldots ,n)\) and \(({\mathbf {R}})=({\mathbb {P}}_0^{[s-s_0]},\) \(\ldots ,\) \({\mathbb {P}}_n^{[s-s_n]})\cap {\mathbb Q}[{\mathbf {u}}_0^{[s-s_0]},\) \(\ldots ,{\mathbf {u}}_n^{[s-s_n]}]\). Regard each \({\mathbb {P}}_i^{(k)}~(i=0,\ldots ,n,k=0,\ldots ,s-s_i)\) as a polynomial in the \(n(s+1)\) variables \({\mathbb {Y}}^{[s]}=\{y_1,\ldots ,y_n,y'_1,\ldots ,y'_n,\ldots ,y^{(s)}_1,\) \(\ldots ,y^{(s)}_n\}\), and we denote its support by \(\mathcal {B}_{ik}\). Let \({\mathbb {F}}_{ik}\) be a generic sparse polynomial with support \(\mathcal {B}_{ik}\). Denote \({\mathbf {c}}_{ik}\) to be the set of coefficients of \({\mathbb {F}}_{ik}\), and in particular, suppose \(c_{ik0}\) is the coefficient of the monomial \(1\) in \({\mathbb {F}}_{ik}\). Now we claim that
C1) \(\overline{\mathcal {B}}=\{\mathcal {B}_{ik}\,|\,0\le i\le n; 0\le k \le s-s_i\}\) is an essential set.
C2) \(\overline{\mathcal {B}}=\{\mathcal {B}_{ik}\,|\,0\le i\le n; 0\le k \le s-s_i\}\) jointly span the affine lattice \(\mathbb {Z}^{n(s+1)}\).
Claim C2) follows from the fact that \(\{1,y_j^{[s]}\,|\,1\le j\le n\}\) is contained in the support of \({\mathbb {F}}_{0,s-s_0}\). From C1) and C2), the sparse resultant of \(({\mathbb {F}}_{ik})_{0\le i\le n; 0\le k\le s-s_i}\) exists and we denote it by \(G\). Then \((G)=\big (({\mathbb {F}}_{ik})_{0\le i\le n; 0\le k\le s-s_i}\big )\bigcap \) \(\mathbb {Q}[({\mathbf {c}}_{ik})_{0\le i\le n; 0\le k\le s-s_i}]\), and by Theorem 6.23, \(\mathrm{deg}(G,{\mathbf {c}}_{ik})=\mathcal {M}\big ((\mathcal {Q}_{jl})_{j\ne i,0\le l\le s-s_j},\mathcal {Q}_{i0},\ldots ,\) \(\mathcal {Q}_{i,k-1},\mathcal {Q}_{i,k+1},\ldots ,\mathcal {Q}_{i,s-s_i}\big )\).
Now suppose \(\xi \) is a generic point of the zero ideal \((0)_{\mathbb {Q}({\mathbf {c}})[{\mathbb {Y}}^{[s]}]}\). Let \(\zeta _{ik}=-{\mathbb {F}}_{ik}(\xi )+c_{ik0}\) and \(\overline{\zeta }_{ik}=-{\mathbb {P}}_i^{(k)}(\xi )+u_{i0}^{(k)}\) (\(i=0,\ldots ,n;k=0,\ldots ,s-s_i\)). Clearly, \(\zeta _{ik}\) and \(\overline{\zeta }_{ik}\) are free of \(c_{ik0}\) and \(u_{i0}^{(k)}\), respectively. It is easy to see that \((\xi ;{\mathbf {c}},\zeta _{00},\ldots ,\zeta _{0,s-s_0},\ldots ,\zeta _{n0},\ldots ,\zeta _{n,s-s_n})\) is a generic point of the algebraic prime ideal \(\big (({\mathbb {F}}_{ik})_{0\le i\le n; 0\le k\le s-s_i}\big )_{{\mathbb Q}[{\mathbb {Y}}^{[s]},({\mathbf {c}}_{ik})_{0\le i\le n; 0\le k\le s-s_i}]}\), while \((\xi ;\cup _{i=0}^n({\mathbf {u}}_i\backslash \{u_{i0}\})^{[s-s_i]},\) \(\overline{\zeta }_{00},\ldots ,\overline{\zeta }_{0,s-s_0},\) \(\ldots , \overline{\zeta }_{n0},\) \(\ldots ,\overline{\zeta }_{n,s-s_n})\) is a generic point of the algebraic prime ideal \(\big (({\mathbb {P}}_{i}^{(k)})_{0\le i\le n; 0\le k\le s-s_i}\big )_{{\mathbb Q}[{\mathbb {Y}}^{[s]},{\mathbf {u}}_0^{[s-s_0]},\ldots ,{\mathbf {u}}_n^{[s-s_n]}]}\). If we regard \(G\) as a polynomial in \(c_{ik0}\) over \(\mathbb {Q}({\mathbf {c}})\), then \(G\) is the vanishing polynomial of \((\zeta _{00},\ldots ,\zeta _{0,s-s_0},\ldots ,\zeta _{n0},\) \(\ldots ,\zeta _{n,s-s_n})\) over \({\mathbb Q}({\mathbf {c}})\). Now specialize the coefficients \({\mathbf {c}}_{ik}\) of \({\mathbb {F}}_{ik}\) to the corresponding coefficients of \({\mathbb {P}}_i^{(k)}\). Then each \(\zeta _{ik}\) is specialized to \(\overline{\zeta }_{ik}\). In particular, \(c_{ik0}\) are specialized to \(u_{i0}^{(k)}\) which are algebraically independent over the field \({\mathbb Q}(\xi ,\cup _{i=0}^n{\mathbf {u}}_i^{[s-s_i]}\backslash u_{i0}^{[s-s_i]})\). We claim that there exists a nonzero polynomial \(H(\cup _{i=0}^n{\mathbf {u}}_i^{[s-s_i]}\backslash u_{i0}^{[s-s_i]};\) \(u_{00},\ldots ,u_{00}^{(s-s_0)},\ldots ,\) \(u_{n0},\ldots ,u_{n0}^{(s-s_n)})\in {\mathbb Q}[{\mathbf {u}}_0^{[s-s_0]},\ldots ,\) \({\mathbf {u}}_n^{[s-s_n]}]\) such that
C3) \(H(\cup _{i=0}^n{\mathbf {u}}_i^{[s-s_i]}\backslash u_{i0}^{[s-s_i]};\overline{\zeta }_{00},\ldots ,\overline{\zeta }_{0,s-s_0},\ldots ,\overline{\zeta }_{n0},\ldots ,\overline{\zeta }_{n,s-s_n})=0\) and
C4) For each \(i\), \(\mathrm{deg}(H,{\mathbf {u}}_i^{[s-s_i]})\le \mathrm{deg}(G,\cup _{k=0}^{s-s_i}{\mathbf {c}}_{ik})\).
In the following, we construct \(H\) by specializing elements of \({\mathbf {c}}\) one by one in \(G\). For each \(v\in {\mathbf {c}}\), denote \(u\) to be its corresponding coefficient in \({\mathbb {P}}_i^{(k)}\). First specialize \(v \) to \(u \) and suppose \(\zeta _{ik}\) is specialized to \(\tilde{\zeta }_{ik}\) correspondingly. Clearly, \(G({\mathbf {c}}\backslash \{v\},u;\tilde{\zeta }_{00},\ldots ,\tilde{\zeta }_{0,s-s_0},\tilde{\zeta }_{n0},\ldots ,\tilde{\zeta }_{n,s-s_n})=0.\) If \(\bar{G}=G({\mathbf {c}}\backslash \{v\},u;c_{000},c_{010},\ldots ,c_{0,s-s_0,0},\ldots ,c_{n00},c_{n10}\ldots ,c_{n,s-s_n,0})\ne 0\), denote \(\bar{G}\) by \(H_1\). Otherwise, there exists some \(a\in \mathbb {N}\) such that \(G=(v-u)^aG_1\) with \(G_1|_{v=u}\ne 0\). But \(G({\mathbf {c}}\backslash \{v\},u;\tilde{\zeta }_{00},\) \(\ldots ,\tilde{\zeta }_{0,s-s_0},\tilde{\zeta }_{n0},\) \(\ldots ,\tilde{\zeta }_{n,s-s_n})=0= (v-u)^aG_1({\mathbf {c}}\backslash \{v\},u;\tilde{\zeta }_{00},\ldots ,\tilde{\zeta }_{0,s-s_0},\tilde{\zeta }_{n0},\) \(\ldots ,\tilde{\zeta }_{n,s-s_n})\), so \(G_1({\mathbf {c}}\backslash \{v\},\) \(u;\tilde{\zeta }_{00},\ldots ,\tilde{\zeta }_{0,s-s_0},\tilde{\zeta }_{n0},\ldots ,\tilde{\zeta }_{n,s-s_n})=0\). Denote \(G_1|_{v=u}\) by \(H_1\). Clearly, \(\mathrm{deg}(H_1,{\mathbf {u}}_i^{[s-s_i]}\bigcup \cup _{k}{\mathbf {c}}_{ik})\le \mathrm{deg}(G,\cup _{k}{\mathbf {c}}_{ik})\) for each \(i\). Continuing this process for \(|{\mathbf {c}}|\) times until each \(v\in {\mathbf {c}}\) is specialized to its corresponding element \(u\), we will obtain a nonzero polynomial \(H_{|{\mathbf {c}}|}(\cup _{i=0}^n({\mathbf {u}}_i\backslash \{u_{i0}\})^{[s-s_i]};c_{000},c_{010},\) \(\ldots ,c_{0,s-s_0,0},\ldots ,c_{n00},c_{n10},\) \(\ldots ,c_{n,s-s_n,0})\) satisfying \(H_{|{\mathbf {c}}|}(\cup _{i=0}^n({\mathbf {u}}_i\backslash \{u_{i0}\})^{[s-s_i]};\overline{\zeta }_{00},\ldots ,\overline{\zeta }_{0,s-s_0},\) \(\overline{\zeta }_{n0},\) \(\ldots ,\overline{\zeta }_{n,s-s_n})=0\) and moreover, for each \(i\), \(\mathrm{deg}(H_{|{\mathbf {c}}|},\) \({\mathbf {u}}_i^{[s-s_i]}\bigcup \cup _{k}\{c_{ik0}\})\le \mathrm{deg}(G,\cup _{k}{\mathbf {c}}_{ik})\). Since the \(u_{i0}^{(k)}\) are algebraically independent over the field \({\mathbb Q}(\xi ,\cup _{i=0}^n({\mathbf {u}}_i\backslash \{u_{i0}\})^{[s-s_i]})\), \(H=H_{|{\mathbf {c}}|}\big |_{c_{ik0}=u_{i0}^{(k)}}\in {\mathbb Q}[{\mathbf {u}}_0^{[s-s_0]},\ldots ,\) \({\mathbf {u}}_n^{[s-s_n]}]\) is a polynomial satisfying C3) and C4).
From C3), \(H\in ({\mathbb {P}}_0^{[s-s_0]},\ldots ,\) \({\mathbb {P}}_n^{[s-s_n]}).\) Since \(({\mathbb {P}}_0^{[s-s_0]},\ldots ,{\mathbb {P}}_n^{[s-s_n]})\cap {\mathbb Q}[{\mathbf {u}}_0^{[s-s_0]},\ldots ,{\mathbf {u}}_n^{[s-s_n]}]=({\mathbf {R}})\) and \({\mathbf {R}}\) is irreducible, \({\mathbf {R}}\) divides \(H\). Then \(\mathrm{deg}({\mathbf {R}},{\mathbf {u}}_i^{[s-s_i]})\le \mathrm{deg}(H,{\mathbf {u}}_i^{[s-s_i]})\) \(\le \mathrm{deg}(G,\cup _{k}{\mathbf {c}}_{ik})=\sum \limits _{k=0}^{s-s_i}\mathrm{deg}(G,{\mathbf {c}}_{ik})=\sum \limits _{k=0}^{s-s_i}\mathcal {M}\big ((\mathcal {Q}_{jl})_{j\ne i,0\le l\le s-s_j},\mathcal {Q}_{i0},\ldots ,\mathcal {Q}_{i,k-1},\mathcal {Q}_{i,k+1},\ldots ,\) \(\mathcal {Q}_{i,s-s_i}\big )\). \(\square \)
As a corollary, we give another Bézout type degree bound for the differential resultant, which is better than the bound given in Theorem 6.16 in that only the degrees of \({\mathbb {P}}_i\) in \({\mathbb {Y}}\) are involved.
Corollary 6.26
Let \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) be defined in (29) and \(s=\sum _{i=0}^n s_i\). Then for each \(i\in \{0,1,\ldots ,n\}\), \(\mathrm{deg}({\mathbf {R}},{\mathbf {u}}_i)\le \frac{s-s_i+1}{m_i}\prod _{j=0}^n m_j^{s-s_j+1}\).
Proof
Example 6.27
7 Conclusion
In this paper, we first introduce the concepts of Laurent differential polynomials and Laurent differentially essential systems and give a criterion for a set of Laurent differential polynomials to be differentially essential in terms of their supports. Then the sparse differential resultant for a Laurent differentially essential system is defined and its basic properties are proved, such as the differential homogeneity, necessary and sufficient conditions for the existence of solutions, differential toric variety, and Poisson product formulas. Furthermore, order and degree bounds for the sparse differential resultant are given. Based on these bounds, an algorithm to compute the sparse differential resultant is proposed, which is single exponential in terms of the Jacobi number and the size of the Laurent differentially essential system.
In the rest of this section, we propose several questions for further study.
It is useful to represent the sparse differential resultant as the quotient of two determinants, as done in [11, 15] in the algebraic case. In the differential case, we do not have such formulas, even in the simplest case of the resultant for two generic differential polynomials in one variable [49] or a system of linear sparse differential polynomials [43]. In [43], for a sparse linear differential system \(S\), Rueda gave an enlarged system \(S_1\) of \(S\) such that \(S_1\) has a matrix representation and the sparse differential resultant of \(S\) can be obtained from the determinant of \(S_1\). The treatment in [6] is far from complete. For instance, let \({\mathbb {P}}_0\) and \({\mathbb {P}}_1\) be two generic differential polynomials given in Example 6.27. Then, the differential resultant for \({\mathbb {P}}_0\) and \({\mathbb {P}}_1\) defined in [6] is zero, because all elements in the first column of the matrix \(M(\delta ,n,m)\) in [6, p. 543] are zero. Although using the idea of Dixon resultants, the algorithm in [48] does not give a matrix representation for the differential resultant.
There exist very efficient algorithms to compute algebraic sparse resultants [14–16], which are based on matrix representations for the resultant. How to apply the principles behind these algorithms to compute sparse differential resultants is an important problem. A reasonable goal is to find an algorithm whose complexity depends on \(\mathrm{deg}({\mathbf {R}})\), but not on its degree bound in the worst case.
Let \(A\) be the factor in the Poisson formula (16). In the algebraic case, the corresponding \(A\) is a product of sparse resultants associated to the faces of the system supports [37]. It would be interesting for future work to analyze whether an analogous expression could be given in the differential case. On the other hand, to obtain Poisson product formulas in Theorem 5.18, we assume the Laurent differential polynomial system is normal rank essential. In the algebraic case, a Poisson product formula valid for arbitrary supports has been proved recently in [12]. It is desirable to see whether the assumption on the input supports can be weakened to derive similar Poisson formulas.
The degree of the algebraic sparse resultant is equal to the mixed volume of certain polytopes generated by the supports of the polynomials [37] or [19, p. 255]. A similar degree bound is given in Theorem 1.3 for the differential resultant. We conjecture that the bound given in Theorem 1.3 is also valid for the sparse differential resultant. Precisely, let \(\widetilde{{\mathbb {P}}}=\{\widetilde{{\mathbb {P}}}_0,\ldots ,\widetilde{{\mathbb {P}}}_n\}\) be a Laurent differentially essential system obtained from (29) by setting certain coefficients \(u_{i\alpha }\) to zero. Then, the degree bound given in Theorem 1.3 is also a degree bound for the sparse differential resultant of \(\widetilde{{\mathbb {P}}}\).
In the algebraic case, it is shown that the sparse polynomials \({\mathbb {P}}_i\,(i=0,\ldots ,n)\) can be re-parameterized to a new system \({\mathbb {S}}_i\,(i=0,\ldots ,n)\) with the help of the Newton polytope associated with \({\mathbb {P}}_i\) such that the vanishing of the sparse resultant gives a sufficient and necessary condition for \({\mathbb {S}}_i\,(i=0,\ldots ,n)\) to have solutions in \({\mathbb C}^N\), where \({\mathbb C}\) is the field of complex numbers [10, page 312]. It is interesting to extend this result to the differential case. To do that we need a deeper study of differential toric variety introduced in Sect. 5.4.
In the algebraic case, it is well known that the resultant vanishes if and only if the corresponding system of homogenous polynomials has common solutions in the projective space [22]. To extend this result to the differential case, several issues should be considered. First, the basis of differentially homogenous polynomials in \(\mathcal {F}\{{\mathbb {Y}}\}\) of degree \(d\), regarded as a vector space \(V(n,d)\) over \(\mathcal {F}\), is generally not differential monomials. For instance, the vector space \(V(1,2)\) is of dimension \(4\) and has a basis \(y_0^2,y_1^2,y_0y_1, y_0y_1'-y_1y_0'\), and it can easily be verified that this vector space has no basis consisting of purely differential monomials. Furthermore, the structure of \(V(n,d)\) is still unknown for \(n>1\) [39]. As a consequence, the sparse differential resultant for a generic differentially homogenous polynomial system cannot be defined properly. Second, in the differential case, the corresponding result might not be valid due to the reason that the projective differential space is not differentially complete [31]. In algebraic geometry, the fact that the projective space is complete plays a crucial role in the proof.
Finally, as mentioned in Sect. 1, the algebraic multivariate resultant has many applications. It is interesting to see whether sparse difference resultant can be used to achieve similar goals in the differential case.
Acknowledgments
Partially supported by a National Key Basic Research Project of China (2011CB302400) and by Grants from NSFC (60821002, 11101411, 11301519).
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