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2015 | OriginalPaper | Chapter

11. Computing Manifolds

Author : Christian Kuehn

Published in: Multiple Time Scale Dynamics

Publisher: Springer International Publishing

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Abstract

We have extensively discussed the properties of invariant manifolds and their relevance for fast–slow systems in previous chapters. However, we usually used explicit algebraic expressions or asymptotic expansions to deal with critical and slow manifolds. For a general multiple time scale system, there are several complications. They may not be in standard form, and even if they are, then calculating a slow manifold analytically may be intractable. This chapter deals with algorithms to find and compute invariant manifolds for fast–slow systems numerically.

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Literature
[Abr13b]
go back to reference R.V. Abramov. A simple stochastic parameterization for reduced models of multiscale dynamics. arXiv:1302.4132v1, pages 1–23, 2013. R.V. Abramov. A simple stochastic parameterization for reduced models of multiscale dynamics. arXiv:1302.4132v1, pages 1–23, 2013.
[ACC+07]
go back to reference A. Adrover, F. Creta, S. Cerbelli, M. Valorani, and M. Giona. The structure of slow invariant manifolds and their bifurcational routes in chemical kinetic models. Comput. Chem. Eng., 31(11): 1456–1474, 2007.CrossRef A. Adrover, F. Creta, S. Cerbelli, M. Valorani, and M. Giona. The structure of slow invariant manifolds and their bifurcational routes in chemical kinetic models. Comput. Chem. Eng., 31(11): 1456–1474, 2007.CrossRef
[ACGV07]
go back to reference A. Adrover, F. Creta, M. Giona, and M. Valorani. Stretching-based diagnostics and reduction of chemical kinetic models with diffusion. J. Comp. Phys., 225(2):1442–1471, 2007.CrossRefMATHMathSciNet A. Adrover, F. Creta, M. Giona, and M. Valorani. Stretching-based diagnostics and reduction of chemical kinetic models with diffusion. J. Comp. Phys., 225(2):1442–1471, 2007.CrossRefMATHMathSciNet
[ASST12]
go back to reference G. Ariel, J.M. Sanz-Serna, and R. Tsai. A multiscale technique for finding slow manifolds of stiff mechanical systems. Multiscale Model. Simul., 10(4):1180–1203, 2012.CrossRefMATHMathSciNet G. Ariel, J.M. Sanz-Serna, and R. Tsai. A multiscale technique for finding slow manifolds of stiff mechanical systems. Multiscale Model. Simul., 10(4):1180–1203, 2012.CrossRefMATHMathSciNet
[BBS96]
go back to reference J.A. Borghans, R.J. De Boer, and L.A. Segel. Extending the quasi-steady state approximation by changing variables. Bull. Math. Biol., 58(1):43–63, 1996.CrossRefMATH J.A. Borghans, R.J. De Boer, and L.A. Segel. Extending the quasi-steady state approximation by changing variables. Bull. Math. Biol., 58(1):43–63, 1996.CrossRefMATH
[BCGFS13]
go back to reference T. Berry, J.R. Cressman, Z. Greguric-Ferencek, and T. Sauer. Time-scale separation from diffusion-mapped delay coordinates. SIAM J. Appl. Dyn. Syst., 12(2):618–649, 2013.CrossRefMATHMathSciNet T. Berry, J.R. Cressman, Z. Greguric-Ferencek, and T. Sauer. Time-scale separation from diffusion-mapped delay coordinates. SIAM J. Appl. Dyn. Syst., 12(2):618–649, 2013.CrossRefMATHMathSciNet
[BG13c]
go back to reference V. Bykov and V. Gol’dshtein. Fast and slow invariant manifolds in chemical kinetics. Comput. Math. Appl., 65(10):1502–1515, 2013. V. Bykov and V. Gol’dshtein. Fast and slow invariant manifolds in chemical kinetics. Comput. Math. Appl., 65(10):1502–1515, 2013.
[BGG08]
go back to reference S. Borok, I. Goldfarb, and V. Gol’dshtein. About non-coincidence of invariant manifolds and intrinsic low dimensional manifolds (ILDM). Comm. Nonl. Sci. Numer. Simul., 13(6):1029–1038, 2008. S. Borok, I. Goldfarb, and V. Gol’dshtein. About non-coincidence of invariant manifolds and intrinsic low dimensional manifolds (ILDM). Comm. Nonl. Sci. Numer. Simul., 13(6):1029–1038, 2008.
[BGGM06]
go back to reference V. Bykov, I. Goldfarb, V. Gol’dshtein, and U. Maas. On a modified version of ILDM approach: asymptotic analysis based on integral manifolds. IMA J. Appl. Math., 71(3):359–382, 2006. V. Bykov, I. Goldfarb, V. Gol’dshtein, and U. Maas. On a modified version of ILDM approach: asymptotic analysis based on integral manifolds. IMA J. Appl. Math., 71(3):359–382, 2006.
[BGM08]
go back to reference V. Bykov, V. Gol’dshtein, and U. Maas. Simple global reduction technique based on decomposition approach. Combust. Theor. Model., 12(2):389–405, 2008. V. Bykov, V. Gol’dshtein, and U. Maas. Simple global reduction technique based on decomposition approach. Combust. Theor. Model., 12(2):389–405, 2008.
[BH25]
go back to reference G.E. Briggs and J.B.S. Haldane. A note on the kinetics of enzyme action. Biochem. J., 19(2):338–339, 1925. G.E. Briggs and J.B.S. Haldane. A note on the kinetics of enzyme action. Biochem. J., 19(2):338–339, 1925.
[BHV07]
go back to reference H.W. Broer, A. Hagen, and G. Vegter. Numerical continuation of normally hyperbolic invariant manifolds. Nonlinearity, 20(6):1499–1534, 2007.CrossRefMATHMathSciNet H.W. Broer, A. Hagen, and G. Vegter. Numerical continuation of normally hyperbolic invariant manifolds. Nonlinearity, 20(6):1499–1534, 2007.CrossRefMATHMathSciNet
[BM07a]
go back to reference V. Bykov and U. Maas. The extension of the ILDM concept to reaction–diffusion manifolds. Comust. Theor. Model., 11(6):839–862, 2007.CrossRefMATH V. Bykov and U. Maas. The extension of the ILDM concept to reaction–diffusion manifolds. Comust. Theor. Model., 11(6):839–862, 2007.CrossRefMATH
[BM07b]
go back to reference V. Bykov and U. Maas. Extension of the ILDM method to the domain of slow chemistry. Proceed. Comust. Inst., 31(1):465–472, 2007.CrossRef V. Bykov and U. Maas. Extension of the ILDM method to the domain of slow chemistry. Proceed. Comust. Inst., 31(1):465–472, 2007.CrossRef
[BYS10]
go back to reference E.M. Bollt, C. Yao, and I.B. Schwartz. Dimensional implications of dynamical data on manifolds to empirical KL analysis. Physica D, 239(23):2039–2049, 2010.CrossRefMATHMathSciNet E.M. Bollt, C. Yao, and I.B. Schwartz. Dimensional implications of dynamical data on manifolds to empirical KL analysis. Physica D, 239(23):2039–2049, 2010.CrossRefMATHMathSciNet
[Chi12]
go back to reference E. Chiavazzo. Approximation of slow and fast dynamics in multiscale dynamical systems by the linearized relaxation redistribution method. J. Comp. Phys., 231(4):1751–1765, 2012.CrossRefMATHMathSciNet E. Chiavazzo. Approximation of slow and fast dynamics in multiscale dynamical systems by the linearized relaxation redistribution method. J. Comp. Phys., 231(4):1751–1765, 2012.CrossRefMATHMathSciNet
[CRK05]
go back to reference R. Clewley, H.G. Rotstein, and N. Kopell. A computational tool for the reduction of nonlinear ODE systems possessing mutltiple scales. Multiscale Model. Simul., 4(3):732–759, 2005.CrossRefMATHMathSciNet R. Clewley, H.G. Rotstein, and N. Kopell. A computational tool for the reduction of nonlinear ODE systems possessing mutltiple scales. Multiscale Model. Simul., 4(3):732–759, 2005.CrossRefMATHMathSciNet
[CS11]
go back to reference M.S. Calder and D. Siegel. Properties of the Lindemann mechanism in phase space. Electron. J. Differential Equat., 2011(8):1–31, 2011. M.S. Calder and D. Siegel. Properties of the Lindemann mechanism in phase space. Electron. J. Differential Equat., 2011(8):1–31, 2011.
[CS12]
go back to reference M.J. Capinski and C. Simo. Computer assisted proof for normally hyperbolic invariant manifolds. Nonlinearity, 25:1997–2026, 2012.CrossRefMATHMathSciNet M.J. Capinski and C. Simo. Computer assisted proof for normally hyperbolic invariant manifolds. Nonlinearity, 25:1997–2026, 2012.CrossRefMATHMathSciNet
[CTS12]
go back to reference R. Chachra, M.K. Transtrum, and J.P. Sethna. Structural susceptibility and separation of time scales in the van der Pol oscillator. Phys. Rev. E, 86:026712, 2012.CrossRef R. Chachra, M.K. Transtrum, and J.P. Sethna. Structural susceptibility and separation of time scales in the van der Pol oscillator. Phys. Rev. E, 86:026712, 2012.CrossRef
[DCD+07]
go back to reference E.J. Doedel, A. Champneys, F. Dercole, T. Fairgrieve, Y. Kuznetsov, B. Oldeman, R. Paffenroth, B. Sandstede, X. Wang, and C. Zhang. Auto 2007p: Continuation and bifurcation software for ordinary differential equations (with homcont). http://cmvl.cs.concordia.ca/auto, 2007. E.J. Doedel, A. Champneys, F. Dercole, T. Fairgrieve, Y. Kuznetsov, B. Oldeman, R. Paffenroth, B. Sandstede, X. Wang, and C. Zhang. Auto 2007p: Continuation and bifurcation software for ordinary differential equations (with homcont). http://​cmvl.​cs.​concordia.​ca/​auto, 2007.
[DH96]
go back to reference M. Dellnitz and A. Hohmann. The computation of unstable manifolds using subdivision and continuation. In H.W. Broer, S.A. Van Gils, I. Hoveijn, and F. Takens, editors, Nonlinear Dynamical Systems and Chaos PNLDE 19, pages 449–459. Birkhäuser, 1996. M. Dellnitz and A. Hohmann. The computation of unstable manifolds using subdivision and continuation. In H.W. Broer, S.A. Van Gils, I. Hoveijn, and F. Takens, editors, Nonlinear Dynamical Systems and Chaos PNLDE 19, pages 449–459. Birkhäuser, 1996.
[DH97]
go back to reference M. Dellnitz and A. Hohmann. A subdivision algorithm for the computation of unstable manifolds and global attractors. Numer. Math., 75:293–317, 1997.CrossRefMATHMathSciNet M. Dellnitz and A. Hohmann. A subdivision algorithm for the computation of unstable manifolds and global attractors. Numer. Math., 75:293–317, 1997.CrossRefMATHMathSciNet
[DGK+12]
go back to reference M. Desroches, J. Guckenheimer, C. Kuehn, B. Krauskopf, H. Osinga, and M. Wechselberger. Mixed-mode oscillations with multiple time scales. SIAM Rev., 54(2):211–288, 2012.CrossRefMATHMathSciNet M. Desroches, J. Guckenheimer, C. Kuehn, B. Krauskopf, H. Osinga, and M. Wechselberger. Mixed-mode oscillations with multiple time scales. SIAM Rev., 54(2):211–288, 2012.CrossRefMATHMathSciNet
[DKO08a]
go back to reference M. Desroches, B. Krauskopf, and H.M. Osinga. The geometry of slow manifolds near a folded node. SIAM J. Appl. Dyn. Syst., 7(4):1131–1162, 2008.CrossRefMATHMathSciNet M. Desroches, B. Krauskopf, and H.M. Osinga. The geometry of slow manifolds near a folded node. SIAM J. Appl. Dyn. Syst., 7(4):1131–1162, 2008.CrossRefMATHMathSciNet
[DKO10]
go back to reference M. Desroches, B. Krauskopf, and H.M. Osinga. Numerical continuation of canard orbits in slow–fast dynamical systems. Nonlinearity, 23(3):739–765, 2010.CrossRefMATHMathSciNet M. Desroches, B. Krauskopf, and H.M. Osinga. Numerical continuation of canard orbits in slow–fast dynamical systems. Nonlinearity, 23(3):739–765, 2010.CrossRefMATHMathSciNet
[DR96a]
go back to reference P. Duchene and P. Rouchon. Kinetic scheme reduction via geometric singular perturbation techniques. Chem. Engineer. Sci., 51(20):4661–4672, 1996.CrossRef P. Duchene and P. Rouchon. Kinetic scheme reduction via geometric singular perturbation techniques. Chem. Engineer. Sci., 51(20):4661–4672, 1996.CrossRef
[DS99b]
go back to reference M.J. Davis and R.T. Skodje. Geometric investigation of low-dimensional manifolds in systems approaching equilibrium. J. Chem. Phys., 111:859–874, 1999.CrossRef M.J. Davis and R.T. Skodje. Geometric investigation of low-dimensional manifolds in systems approaching equilibrium. J. Chem. Phys., 111:859–874, 1999.CrossRef
[EKO07]
go back to reference J.P. England, B. Krauskopf, and H.M. Osinga. Computing two-dimensional global invariant manifolds in slow–fast systems. Int. J. Bif. Chaos, 17(3):805–822, 2007.CrossRefMATHMathSciNet J.P. England, B. Krauskopf, and H.M. Osinga. Computing two-dimensional global invariant manifolds in slow–fast systems. Int. J. Bif. Chaos, 17(3):805–822, 2007.CrossRefMATHMathSciNet
[Fen79]
go back to reference N. Fenichel. Geometric singular perturbation theory for ordinary differential equations. J. Differential Equat., 31:53–98, 1979.CrossRefMATHMathSciNet N. Fenichel. Geometric singular perturbation theory for ordinary differential equations. J. Differential Equat., 31:53–98, 1979.CrossRefMATHMathSciNet
[FH06]
go back to reference D. Flockerzi and W. Heineken. Comment on: Chaos 9, 108–123 (1999). Identification of low order manifolds: validating the algorithm of Maas and Pope. Chaos, 16(4):048101, 2006. D. Flockerzi and W. Heineken. Comment on: Chaos 9, 108–123 (1999). Identification of low order manifolds: validating the algorithm of Maas and Pope. Chaos, 16(4):048101, 2006.
[Fra88b]
go back to reference S.J. Fraser. The steady state and equilibrium approximations: a geometrical picture. J. Chem. Phys., 88:4732–4738, 1988.CrossRef S.J. Fraser. The steady state and equilibrium approximations: a geometrical picture. J. Chem. Phys., 88:4732–4738, 1988.CrossRef
[GDH04]
go back to reference Z.P. Gerdtzen, P. Daoutidis, and W.S. Hu. Non-linear reduction for kinetic models of metabolic reaction networks. Metabolic Engineering, 6(2):140–154, 2004.CrossRef Z.P. Gerdtzen, P. Daoutidis, and W.S. Hu. Non-linear reduction for kinetic models of metabolic reaction networks. Metabolic Engineering, 6(2):140–154, 2004.CrossRef
[GGM04]
go back to reference I. Goldfarb, V. Gol’dshtein, and U. Maas. Comparative analysis of two asymptotic approaches based on integral manifolds. IMA J. Appl. Math., 69(4):353–374, 2004. I. Goldfarb, V. Gol’dshtein, and U. Maas. Comparative analysis of two asymptotic approaches based on integral manifolds. IMA J. Appl. Math., 69(4):353–374, 2004.
[GH83]
go back to reference J. Guckenheimer and P. Holmes. Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Springer, New York, NY, 1983.CrossRefMATH J. Guckenheimer and P. Holmes. Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Springer, New York, NY, 1983.CrossRefMATH
[GJM12]
go back to reference J. Guckenheimer, T. Johnson, and P. Meerkamp. Rigorous enclosures of a slow manifold. SIAM J. Appl. Dyn. Syst., 11(3):831–863, 2012.CrossRefMATHMathSciNet J. Guckenheimer, T. Johnson, and P. Meerkamp. Rigorous enclosures of a slow manifold. SIAM J. Appl. Dyn. Syst., 11(3):831–863, 2012.CrossRefMATHMathSciNet
[GK09a]
[GK10b]
go back to reference J. Guckenheimer and C. Kuehn. Homoclinic orbits of the FitzHugh–Nagumo equation: Bifurcations in the full system. SIAM J. Appl. Dyn. Syst., 9:138–153, 2010.CrossRefMATHMathSciNet J. Guckenheimer and C. Kuehn. Homoclinic orbits of the FitzHugh–Nagumo equation: Bifurcations in the full system. SIAM J. Appl. Dyn. Syst., 9:138–153, 2010.CrossRefMATHMathSciNet
[GKKZ05]
go back to reference C.W. Gear, T.J. Kaper, I.G. Kevrikidis, and A. Zagaris. Projecting to a slow manifold: singularly perturbed systems and legacy codes. SIAM J. Appl. Dyn. Syst., 4(3):711–732, 2005.CrossRefMATHMathSciNet C.W. Gear, T.J. Kaper, I.G. Kevrikidis, and A. Zagaris. Projecting to a slow manifold: singularly perturbed systems and legacy codes. SIAM J. Appl. Dyn. Syst., 4(3):711–732, 2005.CrossRefMATHMathSciNet
[GKS04]
go back to reference D. Givon, R. Kupferman, and A.M. Stuart. Extracting macroscopic dynamics: model problems and algorithms. Nonlinearity, 17:55–127, 2004.CrossRefMathSciNet D. Givon, R. Kupferman, and A.M. Stuart. Extracting macroscopic dynamics: model problems and algorithms. Nonlinearity, 17:55–127, 2004.CrossRefMathSciNet
[GKZ04]
go back to reference A.N. Gorban, I.V. Karlin, and A.Yu. Zinovyev. Constructive methods of invariant manifolds for kinetic problems. Physics Reports, 396:197–403, 2004.CrossRefMathSciNet A.N. Gorban, I.V. Karlin, and A.Yu. Zinovyev. Constructive methods of invariant manifolds for kinetic problems. Physics Reports, 396:197–403, 2004.CrossRefMathSciNet
[GV04]
go back to reference J. Guckenheimer and A. Vladimirsky. A fast method for approximating invariant manifolds. SIAM J. Appl. Dyn. Syst., 3(3):232–260, 2004.CrossRefMATHMathSciNet J. Guckenheimer and A. Vladimirsky. A fast method for approximating invariant manifolds. SIAM J. Appl. Dyn. Syst., 3(3):232–260, 2004.CrossRefMATHMathSciNet
[GV06]
go back to reference D.A. Goussis and M. Valorani. An efficient iterative algorithm for the approximation of the fast and slow dynamics of stiff systems. J. Comp. Phys., 214:316–346, 2006.CrossRefMATHMathSciNet D.A. Goussis and M. Valorani. An efficient iterative algorithm for the approximation of the fast and slow dynamics of stiff systems. J. Comp. Phys., 214:316–346, 2006.CrossRefMATHMathSciNet
[GvL96]
go back to reference G.H. Golub and C. van Loan. Matrix Computations. Johns Hopkins University Press, Baltimore, MD, 1996.MATH G.H. Golub and C. van Loan. Matrix Computations. Johns Hopkins University Press, Baltimore, MD, 1996.MATH
[GW93]
go back to reference J. Guckenheimer and P. Worfolk. Dynamical systems: some computational problems. In D. Schlomiuk, editor, Bifurcations and Periodic Orbits of Vector Fields, pages 241–277. Kluwer, 1993. J. Guckenheimer and P. Worfolk. Dynamical systems: some computational problems. In D. Schlomiuk, editor, Bifurcations and Periodic Orbits of Vector Fields, pages 241–277. Kluwer, 1993.
[Hal03]
go back to reference B.C. Hall. Lie Groups, Lie Algebras, and Representations. Springer, 2003. B.C. Hall. Lie Groups, Lie Algebras, and Representations. Springer, 2003.
[Hen03]
go back to reference M.E. Henderson. Computing invariant manifolds by integrating fat trajectories. Technical Report RC22944, IBM Research, 2003. M.E. Henderson. Computing invariant manifolds by integrating fat trajectories. Technical Report RC22944, IBM Research, 2003.
[HMKS01]
go back to reference S. Handrock-Meyer, L.V. Kalachev, and K.R. Schneider. A method to determine the dimension of long-time dynamics in multi-scale systems. J. Math. Chem., 30(2):133–160, 2001.CrossRefMATHMathSciNet S. Handrock-Meyer, L.V. Kalachev, and K.R. Schneider. A method to determine the dimension of long-time dynamics in multi-scale systems. J. Math. Chem., 30(2):133–160, 2001.CrossRefMATHMathSciNet
[HR02]
go back to reference E.L. Haseltine and Rawlings. Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. J. Chem. Phys., 117(15):6959–6969, 2002. E.L. Haseltine and Rawlings. Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. J. Chem. Phys., 117(15):6959–6969, 2002.
[HZKW09]
go back to reference H.M. Hädin, A. Zagaris, K. Krab, and H.V. Westerhoff. Simplified yet highly accurate enzyme kinetics for cases of low substrate concentrations. FEBS J., 276(19):5491–5506, 2009.CrossRef H.M. Hädin, A. Zagaris, K. Krab, and H.V. Westerhoff. Simplified yet highly accurate enzyme kinetics for cases of low substrate concentrations. FEBS J., 276(19):5491–5506, 2009.CrossRef
[Jan89]
go back to reference J.A.M. Janssen. The elimination of fast variables in complex chemical reactions. I. Macroscopic level. J. Stat. Phys., 57(1):157–169, 1989. J.A.M. Janssen. The elimination of fast variables in complex chemical reactions. I. Macroscopic level. J. Stat. Phys., 57(1):157–169, 1989.
[JJK97]
go back to reference M.E. Johnson, M.S. Jolly, and I.G. Kevrekidis. Two-dimensional invariant manifolds and global bifurcations: some approximation and visualization studies. Num. Alg., 14(1):125–140, 1997.CrossRefMATHMathSciNet M.E. Johnson, M.S. Jolly, and I.G. Kevrekidis. Two-dimensional invariant manifolds and global bifurcations: some approximation and visualization studies. Num. Alg., 14(1):125–140, 1997.CrossRefMATHMathSciNet
[KAWC80]
go back to reference P.V. Kokotovic, J.J. Allemong, J.R. Winkleman, and J.H. Chow. Singular perturbation and iterative separation of time scales. Automatica, 16:23–33, 1980.CrossRefMATH P.V. Kokotovic, J.J. Allemong, J.R. Winkleman, and J.H. Chow. Singular perturbation and iterative separation of time scales. Automatica, 16:23–33, 1980.CrossRefMATH
[Kaz00a]
go back to reference N. Kazantzis. Singular PDEs and the problem of finding invariant manifolds for nonlinear dynamical systems. Phys. Lett. A, 272(4):257–263, 2000.CrossRefMATHMathSciNet N. Kazantzis. Singular PDEs and the problem of finding invariant manifolds for nonlinear dynamical systems. Phys. Lett. A, 272(4):257–263, 2000.CrossRefMATHMathSciNet
[KBS12]
go back to reference K.U. Kristiansen, M. Brøns, and J. Starke. An iterative method for the approximation of fibers in slow–fast systems. arXiv:1208.6420, pages 1–28, 2012. K.U. Kristiansen, M. Brøns, and J. Starke. An iterative method for the approximation of fibers in slow–fast systems. arXiv:1208.6420, pages 1–28, 2012.
[KG02]
go back to reference N. Kazantzis and T. Good. Invariant manifolds and the calculation of the long-term asymptotic response of nonlinear processes using singular PDEs. Comput. Chem. Engineer., 26(7):999–1012, 2002.CrossRef N. Kazantzis and T. Good. Invariant manifolds and the calculation of the long-term asymptotic response of nonlinear processes using singular PDEs. Comput. Chem. Engineer., 26(7):999–1012, 2002.CrossRef
[KJ11]
go back to reference A. Kumar and K. Josić. Reduced models of networks of coupled enzymatic reactions. J. Theor. Biol., pages 87–106, 2011. A. Kumar and K. Josić. Reduced models of networks of coupled enzymatic reactions. J. Theor. Biol., pages 87–106, 2011.
[KK02]
go back to reference H.G. Kaper and T.J. Kaper. Asymptotic analysis of two reduction methods for systems of chemical reactions. Physica D, 165:66–93, 2002.CrossRefMATHMathSciNet H.G. Kaper and T.J. Kaper. Asymptotic analysis of two reduction methods for systems of chemical reactions. Physica D, 165:66–93, 2002.CrossRefMATHMathSciNet
[KK13]
go back to reference H.-W. Kang and T.G. Kurtz. Separation of time scales and model reduction for stochastic reaction networks. Ann. Appl. Prob., 23(2):529–583, 2013.CrossRefMATHMathSciNet H.-W. Kang and T.G. Kurtz. Separation of time scales and model reduction for stochastic reaction networks. Ann. Appl. Prob., 23(2):529–583, 2013.CrossRefMATHMathSciNet
[KKK+07]
go back to reference L.V. Kalachev, H.G. Kaper, T.J. Kaper, N. Popovic, and A. Zagaris. Reduction for Michaelis–Menten–Henri kinetics in the presence of diffusion. Electronic J. Diff. Eq., 16:155–184, 2007.MathSciNet L.V. Kalachev, H.G. Kaper, T.J. Kaper, N. Popovic, and A. Zagaris. Reduction for Michaelis–Menten–Henri kinetics in the presence of diffusion. Electronic J. Diff. Eq., 16:155–184, 2007.MathSciNet
[KKS10]
go back to reference N. Kazantzis, C. Kravaris, and L. Syrou. A new model reduction method for nonlinear dynamical systems. Nonlinear Dyn., 59(1):183–194, 2010.CrossRefMATHMathSciNet N. Kazantzis, C. Kravaris, and L. Syrou. A new model reduction method for nonlinear dynamical systems. Nonlinear Dyn., 59(1):183–194, 2010.CrossRefMATHMathSciNet
[Kna04]
go back to reference A.W. Knapp. Lie Groups Beyond an Introduction. Birkhäuser, 2004. A.W. Knapp. Lie Groups Beyond an Introduction. Birkhäuser, 2004.
[KO99]
[KO03]
go back to reference B. Krauskopf and H.M. Osinga. Computing geodesic level sets on global (un)stable manifolds of vector fields. SIAM J. Appl. Dyn. Syst., 4(2):546–569, 2003.CrossRefMathSciNet B. Krauskopf and H.M. Osinga. Computing geodesic level sets on global (un)stable manifolds of vector fields. SIAM J. Appl. Dyn. Syst., 4(2):546–569, 2003.CrossRefMathSciNet
[KOD+05]
go back to reference B. Krauskopf, H.M. Osinga, E.J. Doedel, M.E. Henderson, J. Guckenheimer, A. Vladimirsky, M. Dellnitz, and O. Junge. A survey of methods for computing (un)stable manifolds of vector fields. Int. J. Bif. Chaos, 15(3):763–791, 2005.CrossRefMATHMathSciNet B. Krauskopf, H.M. Osinga, E.J. Doedel, M.E. Henderson, J. Guckenheimer, A. Vladimirsky, M. Dellnitz, and O. Junge. A survey of methods for computing (un)stable manifolds of vector fields. Int. J. Bif. Chaos, 15(3):763–791, 2005.CrossRefMATHMathSciNet
[KSG+98]
go back to reference B.N. Kholdenko, S. Schuster, J. Garcia, H.V. Westerhoff, and M. Cascante. Control analysis of metabolic systems involving quasi-equilibrium reactions. Biochimica et Biophysica Acta, 1379(3): 337–352, 1998.CrossRef B.N. Kholdenko, S. Schuster, J. Garcia, H.V. Westerhoff, and M. Cascante. Control analysis of metabolic systems involving quasi-equilibrium reactions. Biochimica et Biophysica Acta, 1379(3): 337–352, 1998.CrossRef
[KSG10]
go back to reference P.D. Kourdis, R. Steuer, and D.A. Goussis. Physical understanding of complex multiscale biochemical models via algorithmic simplification: glycolysis in Saccharomyces cerevisiae. Physica D, 239(18):1798–1817, 2010. P.D. Kourdis, R. Steuer, and D.A. Goussis. Physical understanding of complex multiscale biochemical models via algorithmic simplification: glycolysis in Saccharomyces cerevisiae. Physica D, 239(18):1798–1817, 2010.
[Leb04]
go back to reference D. Lebiedz. Computing minimal entropy production trajectories: an approach to model reduction in chemical kinetics. J. Chem. Phys., 120:6890–6897, 2004.CrossRef D. Lebiedz. Computing minimal entropy production trajectories: an approach to model reduction in chemical kinetics. J. Chem. Phys., 120:6890–6897, 2004.CrossRef
[Lee06]
go back to reference J.M. Lee. Introduction to Smooth Manifolds. Springer, 2006. J.M. Lee. Introduction to Smooth Manifolds. Springer, 2006.
[LL09b]
go back to reference C.H. Lee and R. Lui. A reduction method for multiple time scale stochastic reaction networks. J. Math. Chem., 46(4):1292–1321, 2009.CrossRefMATHMathSciNet C.H. Lee and R. Lui. A reduction method for multiple time scale stochastic reaction networks. J. Math. Chem., 46(4):1292–1321, 2009.CrossRefMATHMathSciNet
[LL10]
go back to reference C.H. Lee and R. Lui. A reduction method for multiple time scale stochastic reaction networks with non-unique equilibrium probability. J. Math. Chem., 47(2):750–770, 2010.CrossRefMATHMathSciNet C.H. Lee and R. Lui. A reduction method for multiple time scale stochastic reaction networks with non-unique equilibrium probability. J. Math. Chem., 47(2):750–770, 2010.CrossRefMATHMathSciNet
[LO10]
go back to reference C.H. Lee and H.G. Othmer. A multi-time-scale analysis of chemical reaction networks: I. Deterministic systems. J. Math. Biol., 60:387–450, 2010. C.H. Lee and H.G. Othmer. A multi-time-scale analysis of chemical reaction networks: I. Deterministic systems. J. Math. Biol., 60:387–450, 2010.
[LS13]
go back to reference D. Lebiedz and J. Siehr. A continuation method for the efficient solution of parametric optimization problems in kinetic model reduction. arXiv:1301.5815, pages 1–19, 2013. D. Lebiedz and J. Siehr. A continuation method for the efficient solution of parametric optimization problems in kinetic model reduction. arXiv:1301.5815, pages 1–19, 2013.
[LSU11]
go back to reference D. Lebiedz, J. Siehr, and J. Unger. A variational principle for computing slow invariant manifolds in dissipative dynamical systems. SIAM J. Sci. Comput., 33(2):703–720, 2011.CrossRefMATHMathSciNet D. Lebiedz, J. Siehr, and J. Unger. A variational principle for computing slow invariant manifolds in dissipative dynamical systems. SIAM J. Sci. Comput., 33(2):703–720, 2011.CrossRefMATHMathSciNet
[Maa98]
go back to reference U. Maas. Efficient calculation of intrinsic low-dimensional manifolds for simplification of chemical kinetics. Comp. Vis. Sci., 1:69–82, 1998.CrossRefMATH U. Maas. Efficient calculation of intrinsic low-dimensional manifolds for simplification of chemical kinetics. Comp. Vis. Sci., 1:69–82, 1998.CrossRefMATH
[Mas02]
go back to reference M. Massot. Singular perturbation analysis for the reduction of complex chemistry in gaseous mixtures using the entropic structure. Comptes Rendus Math., 335:93–98, 2002.CrossRefMATHMathSciNet M. Massot. Singular perturbation analysis for the reduction of complex chemistry in gaseous mixtures using the entropic structure. Comptes Rendus Math., 335:93–98, 2002.CrossRefMATHMathSciNet
[Mea95]
go back to reference K.D. Mease. Geometry of computational singular perturbations. Nonlinear Contr. Syst. Design, 2: 855–861, 1995. K.D. Mease. Geometry of computational singular perturbations. Nonlinear Contr. Syst. Design, 2: 855–861, 1995.
[Mei78]
go back to reference W. Meiske. An approximate solution of the Michaelis–Menten mechanism for quasi-steady and state quasi-equilibrium. Math. Biosci., 42:63–71, 1978.CrossRefMATHMathSciNet W. Meiske. An approximate solution of the Michaelis–Menten mechanism for quasi-steady and state quasi-equilibrium. Math. Biosci., 42:63–71, 1978.CrossRefMATHMathSciNet
[MP92a]
go back to reference U. Maas and S.B. Pope. Implementation of simplified chemical kinetics based on intrinsic low-dimensional manifolds. In Proceedings of the 24th International Symposium on Combustion, pages 103–112. The Combustion Institute, 1992. U. Maas and S.B. Pope. Implementation of simplified chemical kinetics based on intrinsic low-dimensional manifolds. In Proceedings of the 24th International Symposium on Combustion, pages 103–112. The Combustion Institute, 1992.
[MP92b]
go back to reference U. Maas and S.B. Pope. Simplifying chemical kinetics: intrinsic low-dimensional manifolds in composition space. Combust. Flame, 88:239–264, 1992.CrossRef U. Maas and S.B. Pope. Simplifying chemical kinetics: intrinsic low-dimensional manifolds in composition space. Combust. Flame, 88:239–264, 1992.CrossRef
[MP13]
go back to reference J.D. Mengers and J.M. Powers. One-dimensional slow invariant manifolds for fully coupled reaction and micro-scale diffusion. SIAM J. Appl. Dyn. Syst., 12(2):560–595, 2013.CrossRefMATHMathSciNet J.D. Mengers and J.M. Powers. One-dimensional slow invariant manifolds for fully coupled reaction and micro-scale diffusion. SIAM J. Appl. Dyn. Syst., 12(2):560–595, 2013.CrossRefMATHMathSciNet
[NF89]
go back to reference A.H. Nguyen and S.J. Fraser. Geometrical picture of reaction in enzyme kinetics. J. Chem. Phys., 91:186, 1989.CrossRef A.H. Nguyen and S.J. Fraser. Geometrical picture of reaction in enzyme kinetics. J. Chem. Phys., 91:186, 1989.CrossRef
[NF13]
go back to reference P. Nicolini and D. Frezzato. Features in chemical kinetics. II. A self-emerging definition of slow manifolds. J. Chem. Phys., 138:234102, 2013. P. Nicolini and D. Frezzato. Features in chemical kinetics. II. A self-emerging definition of slow manifolds. J. Chem. Phys., 138:234102, 2013.
[NLCK06]
go back to reference B. Nadler, S. Lafon, R.R. Coifman, and I.G. Kevrekidis. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems. Appl. Comput. Harmonic Anal., 21(1):113–127, 2006.CrossRefMATHMathSciNet B. Nadler, S. Lafon, R.R. Coifman, and I.G. Kevrekidis. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems. Appl. Comput. Harmonic Anal., 21(1):113–127, 2006.CrossRefMATHMathSciNet
[RA03]
go back to reference C.V. Rao and A.P. Arkin. Stochastic chemical kinetics and the quasi-steady-state assumption: application to the Gillespie algorithm. J. Chem. Phys., 118(11):4999–5010, 2003.CrossRef C.V. Rao and A.P. Arkin. Stochastic chemical kinetics and the quasi-steady-state assumption: application to the Gillespie algorithm. J. Chem. Phys., 118(11):4999–5010, 2003.CrossRef
[RF91a]
go back to reference M.R. Roussel and S.J. Fraser. Accurate steady-state approximations: implications for kinetics experiments and mechanism. J. Phys. Chem., 95(22):8762–8770, 1991.CrossRef M.R. Roussel and S.J. Fraser. Accurate steady-state approximations: implications for kinetics experiments and mechanism. J. Phys. Chem., 95(22):8762–8770, 1991.CrossRef
[RF91b]
go back to reference M.R. Roussel and S.J. Fraser. Geometry of steady-state approximation: perturbation and accelerated convergence methods. J. Chem. Phys., 95:8762–8770, 1991.CrossRef M.R. Roussel and S.J. Fraser. Geometry of steady-state approximation: perturbation and accelerated convergence methods. J. Chem. Phys., 95:8762–8770, 1991.CrossRef
[RF91c]
go back to reference M.R. Roussel and S.J. Fraser. On the geometry of transient relaxation. J. Chem. Phys., 94:7106, 1991.CrossRef M.R. Roussel and S.J. Fraser. On the geometry of transient relaxation. J. Chem. Phys., 94:7106, 1991.CrossRef
[RF01]
go back to reference M.R. Roussel and S.J. Fraser. Invariant manifold methods for metabolic model reduction. Chaos, 11(1):196–206, 2001.CrossRefMATH M.R. Roussel and S.J. Fraser. Invariant manifold methods for metabolic model reduction. Chaos, 11(1):196–206, 2001.CrossRefMATH
[RGZL08]
go back to reference O. Radulescu, A.N. Gorban, A. Zinovyev, and A. Lilienbaum. Robust simplifications of multiscale biochemical networks. BMC Syst. Biol., 2(1):86, 2008. O. Radulescu, A.N. Gorban, A. Zinovyev, and A. Lilienbaum. Robust simplifications of multiscale biochemical networks. BMC Syst. Biol., 2(1):86, 2008.
[RMW99]
go back to reference C. Rhodes, M. Morari, and S. Wiggins. Identification of low order manifolds: validating the algorithm of Maas and Pope. Chaos, 9(1):108–123, 1999.CrossRefMATHMathSciNet C. Rhodes, M. Morari, and S. Wiggins. Identification of low order manifolds: validating the algorithm of Maas and Pope. Chaos, 9(1):108–123, 1999.CrossRefMATHMathSciNet
[RPVG07]
go back to reference Z. Ren, S.B. Pope, A. Vladimirsky, and J.M. Guckenheimer. Application of the ICE-PIC method for the dimension reduction of chemical kinetics coupled with transport. Proceed. Combust. Inst., 31: 473–481, 2007.CrossRef Z. Ren, S.B. Pope, A. Vladimirsky, and J.M. Guckenheimer. Application of the ICE-PIC method for the dimension reduction of chemical kinetics coupled with transport. Proceed. Combust. Inst., 31: 473–481, 2007.CrossRef
[RSS11]
go back to reference E. Reznik, D. Segré, and W.E. Sherwood. The quasi-steady state assumption in an enzymatically open system. arXiv:1103.1200v1, pages 1–28, 2011. E. Reznik, D. Segré, and W.E. Sherwood. The quasi-steady state assumption in an enzymatically open system. arXiv:1103.1200v1, pages 1–28, 2011.
[SFMH05]
go back to reference R. Straube, D. Flockerzi, S.C. Müller, and M.J. Hauser. Reduction of chemical reaction networks using quasi-integrals. J. Phys. Chem. A, 109(3):441–450, 2005.CrossRef R. Straube, D. Flockerzi, S.C. Müller, and M.J. Hauser. Reduction of chemical reaction networks using quasi-integrals. J. Phys. Chem. A, 109(3):441–450, 2005.CrossRef
[SK93a]
go back to reference G.M. Shroff and H.B. Keller. Stabilization of unstable procedures: a recursive projection method. SIAM J. Numer. Anal., 30:1099–1120, 1993.CrossRefMATHMathSciNet G.M. Shroff and H.B. Keller. Stabilization of unstable procedures: a recursive projection method. SIAM J. Numer. Anal., 30:1099–1120, 1993.CrossRefMATHMathSciNet
[SS89]
[Ste73]
go back to reference G.W. Stewart. Introduction to Matrix Computations. Academic Press, 1973. G.W. Stewart. Introduction to Matrix Computations. Academic Press, 1973.
[Sti98a]
[VCG+06]
go back to reference M. Valorani, F. Creta, D.A. Goussis, J.C. Lee, and H.N. Najm. An automatic procedure for the simplification of chemical kinetic mechanisms based on CSP. Combustion and Flame, 146(1):29–51, 2006.CrossRef M. Valorani, F. Creta, D.A. Goussis, J.C. Lee, and H.N. Najm. An automatic procedure for the simplification of chemical kinetic mechanisms based on CSP. Combustion and Flame, 146(1):29–51, 2006.CrossRef
[VGCN05]
go back to reference M. Valorani, D.A. Goussis, F. Creta, and H.N. Najm. Higher order corrections in the approximation of low-dimensional manifolds and the construction of simplified problems with the CSP method. J. Comp. Phys., 209(2):754–786, 2005.CrossRefMATHMathSciNet M. Valorani, D.A. Goussis, F. Creta, and H.N. Najm. Higher order corrections in the approximation of low-dimensional manifolds and the construction of simplified problems with the CSP method. J. Comp. Phys., 209(2):754–786, 2005.CrossRefMATHMathSciNet
[VP09]
go back to reference M. Valorani and S. Paolucci. The G-scheme: a framework for multi-scale adaptive model reduction. J. Comp. Phys., 228(13):4665–4701, 2009.CrossRefMATHMathSciNet M. Valorani and S. Paolucci. The G-scheme: a framework for multi-scale adaptive model reduction. J. Comp. Phys., 228(13):4665–4701, 2009.CrossRefMATHMathSciNet
[ZGKK09]
go back to reference A. Zagaris, C.W. Gear, T.J. Kaper, and I.G. Kevrikidis. Analysis of the accuracy and convergence of equation-free projection to a slow manifold. ESAIM: Math. Model. Numer. Anal., 43(4):754–784, 2009.CrossRef A. Zagaris, C.W. Gear, T.J. Kaper, and I.G. Kevrikidis. Analysis of the accuracy and convergence of equation-free projection to a slow manifold. ESAIM: Math. Model. Numer. Anal., 43(4):754–784, 2009.CrossRef
[ZKK04a]
go back to reference A. Zagaris, H.G. Kaper, and T.J. Kaper. Analysis of the computational singular perturbation method for chemical kinetics. J. Nonlinear Sci., 14:59–91, 2004.CrossRefMATHMathSciNet A. Zagaris, H.G. Kaper, and T.J. Kaper. Analysis of the computational singular perturbation method for chemical kinetics. J. Nonlinear Sci., 14:59–91, 2004.CrossRefMATHMathSciNet
[ZKK04b]
go back to reference A. Zagaris, H.G. Kaper, and T.J. Kaper. Fast and slow dynamics for the computational singular perturbation method. Multiscale Model. Simul., 2(4):613–638, 2004.CrossRefMATHMathSciNet A. Zagaris, H.G. Kaper, and T.J. Kaper. Fast and slow dynamics for the computational singular perturbation method. Multiscale Model. Simul., 2(4):613–638, 2004.CrossRefMATHMathSciNet
[ZKK05]
go back to reference A. Zagaris, H.G. Kaper, and T.J. Kaper. Two perspectives on reduction of ordinary differential equations. Math. Nachr., 278(12):1629–1642, 2005.CrossRefMATHMathSciNet A. Zagaris, H.G. Kaper, and T.J. Kaper. Two perspectives on reduction of ordinary differential equations. Math. Nachr., 278(12):1629–1642, 2005.CrossRefMATHMathSciNet
[ZNK13]
go back to reference A. Zakharova, Z. Nikoloski, and A. Koseka. Dimensionality reduction of bistable biological systems. Bull. Math. Biol., 75:373–392, 2013.CrossRefMATHMathSciNet A. Zakharova, Z. Nikoloski, and A. Koseka. Dimensionality reduction of bistable biological systems. Bull. Math. Biol., 75:373–392, 2013.CrossRefMATHMathSciNet
[ZVG+12]
go back to reference A. Zagaris, C. Vanderkerckhove, C.W. Gear, T.J. Kaper, and I.G. Kevrekidis. Stability and stabilization of the constrained runs schemes for equation-free projection to a slow manifold. Discr. Cont. Dyn. Syst. A, 32(8):2759–2803, 2012.CrossRefMATH A. Zagaris, C. Vanderkerckhove, C.W. Gear, T.J. Kaper, and I.G. Kevrekidis. Stability and stabilization of the constrained runs schemes for equation-free projection to a slow manifold. Discr. Cont. Dyn. Syst. A, 32(8):2759–2803, 2012.CrossRefMATH
Metadata
Title
Computing Manifolds
Author
Christian Kuehn
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-12316-5_11

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