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Applied Optics

Applied Optics


  • Vol. 43, Iss. 13 — May. 1, 2004
  • pp: 2651–2660

Markov-chain Monte Carlo approach to the design of multilayer thin-film optical coatings

Michael P. Hobson and John E. Baldwin  »View Author Affiliations

Applied Optics, Vol. 43, Issue 13, pp. 2651-2660 (2004)

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We reconsider the problem of locating the globally optimal solution of a multilayer-optical-coating design problem, within some predetermined space of parameters, with the aim of obtaining a robust technique that requires a minimum of user intervention. The approach we adopt centers on exploring the space of the parameters of interest by using a Markov-chain Monte Carlo sampling algorithm. This technique enables one to locate the global optimum automatically with high confidence and without the need for a good starting design. It also allows the trivial inclusion of prior constraints on the variables and provides a natural means for investigating the robustness of the optimal solution.

© 2004 Optical Society of America

OCIS Codes
(310.0310) Thin films : Thin films
(310.1210) Thin films : Antireflection coatings
(310.1620) Thin films : Interference coatings
(310.6860) Thin films : Thin films, optical properties

Original Manuscript: July 29, 2003
Revised Manuscript: January 14, 2004
Published: May 1, 2004

Michael P. Hobson and John E. Baldwin, "Markov-chain Monte Carlo approach to the design of multilayer thin-film optical coatings," Appl. Opt. 43, 2651-2660 (2004)

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