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2. Polynomial Approximations

  • 2026
  • OriginalPaper
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Abstract

This chapter delves into the essential role of polynomial approximations in the development and analysis of quantum algorithms. It begins by introducing two primary categories of approximation techniques: pointwise approximations, exemplified by Taylor expansions, and uniform approximations over an interval, illustrated by Chebyshev polynomial expansions. The Taylor series is explored for approximating functions around a point, with a focus on the approximation error and the radius of convergence. The chapter then shifts to Chebyshev polynomials, detailing their properties, recurrence relations, and the significance of Chebyshev nodes in achieving uniform approximations. The concept of evaluating analytic functions of matrices using Taylor series is also discussed, highlighting the challenges and solutions in matrix exponentiation, particularly in quantum computing. The chapter touches on the Hamiltonian simulation problem and the use of Trotter–Suzuki formulas for approximating matrix exponentials. It concludes by mentioning the Baker–Campbell–Hausdorff formula and the Lie–Trotter approximation, setting the stage for further exploration in subsequent chapters.

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Title
Polynomial Approximations
Authors
Osama M. Raisuddin
Suvranu De
Copyright Year
2026
DOI
https://doi.org/10.1007/978-3-032-03325-3_2
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