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Automatic Differentiation in the Optimization of Imaging Optical Systems

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Języki publikacji
EN
Abstrakty
EN
Automatic differentiation is an often superior alternative to numerical differentiation that is yet unregarded for calculating derivatives in the optimization of imaging optical systems. We show that it is between 8% and 34% faster than numerical differentiation with central difference when optimizing various optical systems.
Słowa kluczowe
Rocznik
Tom
Strony
169--175
Opis fizyczny
Bibliogr. 15 poz., tab.
Twórcy
autor
  • Fachgebiet Technische Optik, Institut für Mikro- und Nanotechnologien, Technische Universität Ilmenau, PF 10 05 65, 98684 Ilmenau, Germany
  • Fachgebiet Technische Optik, Institut für Mikro- und Nanotechnologien, Technische Universität Ilmenau, PF 10 05 65, 98684 Ilmenau, Germany
autor
  • Institut für Mathematik, Technische Universität Ilmenau, PF 10 05 65, 98684 Ilmenau, Germany
autor
  • Fachgebiet Technische Optik, Institut für Mikro- und Nanotechnologien, Technische Universität Ilmenau, PF 10 05 65, 98684 Ilmenau, Germany
Bibliografia
  • [1] Shannon R.R. The Art and Science of Optical Design. Cambridge University Press, 1997.
  • [2] Gross H., editor. Aberration Theory and Correction of Optical Systems, volume 3 of Handbook of Optical Systems. Wiley-VCH, 2007.
  • [3] Kidger M.J. Use of the levenberg–marquardt (damped least-squares) optimization method in lens design. Optical Engineering, 32(8):1731–1739, 1993.
  • [4] Vasiljevic D. Classical and Evolutionary Algorithms in the Optimization of Optical Systems. Kluwer Academic Publishers, 2002.
  • [5] Wengert R. A simple automatic derivative evaluation program. Communications of the ACM, 7(8):463–464, 1964.
  • [6] Rall L.B. Automatic Differentiation: Techniques and Applications, volume 120 of Lecture Notes in Computer Science. Springer, 1981.
  • [7] Griewank A. and Walther A. Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. SIAM, 2nd edition, 2008.
  • [8] Rall L.B. and Corliss G.F. An introduction to automatic differentiation. In Computational Differentiation: Techniques, Applications, and Tools, pages 1–17. SIAM, 1996.
  • [9] Werner J. Optimization of imaging optical systems. Bachelor’s thesis, Ilmenau University of Technology, 2011.
  • [10] Devernay F. C/C++ Minpack.
  • [11] Johnson S.G. The NLopt nonlinear-optimization package.
  • [12] Walther A. and Griewank A. ADOL-C: A Package for the Automatic Differentiation of Algorithms Written in C/C++, Nov 2010.
  • [13] Press W.H., Teukolsky S.A., Vetterling W.T., and Flannery B.P. Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, 3rd edition, 2007.
  • [14] Kidger M.J. Intermediate Optical Design. SPIE Publications, 2004.
  • [15] van Turnhout M. and Bociort F. Instabilities and fractal basins of attraction in optical system optimization. Optics Express, 17(1):314–328, 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e98634b4-c6ca-4666-9dca-766fc6fbe85d
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