Related Experiment Video
Updated: Jul 2, 2026

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
Published on: December 15, 2017
Estimation of physically realizable Mueller matrices from experiments using global constrained optimization
Jawad Elsayed Ahmad1, Yoshitate Takakura
1Université Louis Pasteur, Strasbourg I Laboratoire des Sciences de l'Image et de la Télédétection CNRS UMR 7005, Boulevard Sébastien Brant, 67412 Illkirch, France. jawadsayed@termxjy.u-strasbg.fr
Abstract:
One can explicitly retrieve physically realizable Mueller matrices from quantified intensity data even in the presence of noise. This is done by integrating the physical realizability criterion obtained by Givens and Kostinski, [J. Mod. Opt. 40, 471 (1993)], as an active constraint in a global optimization process. Among different global optimization techniques, two of them have been tested and their robustness analyzed: a deterministic approach based on sequential quadratic programming and a stochastic approach based on constrained simulated annealing algorithms are implemented for this purpose. We illustrate the validity of both methods on experimental data and on the inadmissible Mueller matrix given by Howell, [Appl. Opt. 18, No. 6, 808-812 (1979)]. In comparison, the constrained simulated annealing method produced higher accuracy with similar computing time.
Related Concept Videos
Lagrange Multipliers: Two Constraints
Methods of Medium Optimization
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Lagrange Multipliers: One Constraint
Local Maximum and Minimum Values