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Quadrature Strategies for Constructing Polynomial Approximations

  • Pranay Seshadri
  • Gianluca IaccarinoEmail author
  • Tiziano Ghisu
Chapter
Part of the PoliTO Springer Series book series (PTSS)

Abstract

Finding suitable points for multivariate polynomial interpolation and approximation is a challenging task. Yet, despite this challenge, there has been tremendous research dedicated to this singular cause. In this paper, we begin by reviewing classical methods for finding suitable quadrature points for polynomial approximation in both the univariate and multivariate setting. Then, we categorize recent advances into those that propose a new sampling approach, and those centered on an optimization strategy. The sampling approaches yield a favorable discretization of the domain, while the optimization methods pick a subset of the discretized samples that minimize certain objectives. While not all strategies follow this two-stage approach, most do. Sampling techniques covered include subsampling quadratures, Christoffel, induced and Monte Carlo methods. Optimization methods discussed range from linear programming ideas and Newton’s method to greedy procedures from numerical linear algebra. Our exposition is aided by examples that implement some of the aforementioned strategies.

Keywords

Polynomial approximation Numerical integration Optimization Gauss quadrature 

Notes

Acknowledgements

This work was carried out while PS was visiting the Department of Mechanical, Chemical and Materials Engineering at Universitá di Cagliari in Cagliari, Sardinia; the financial support of the University’s Visiting Professor Program is gratefully acknowledged. The authors are also grateful to Akil Narayan for numerous discussions on polynomial approximations and quadratures.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Pranay Seshadri
    • 1
    • 2
  • Gianluca Iaccarino
    • 3
    Email author
  • Tiziano Ghisu
    • 4
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK
  2. 2.The Alan Turing InstituteLondonUK
  3. 3.Department of Mechanical EngineeringInstitute for Computational and Mathematical Engineering, Stanford UniversityStanfordUSA
  4. 4.Department of Mechanical, Chemical and Materials EngineeringUniversitá di CagliariCagliariItaly

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