RT Journal Article
T1 Bayesian inference approach for Full Poincaré Mueller polarimetry
A1 Suárez Bermejo, Juan Carlos
A1 Gorgas García, Francisco Javier
A1 Pascual Ramírez, Sergio
A1 Santarsiero, Massimo
A1 González de Sande, Juan Carlos
A1 Piquero Sanz, Gemma María
AB Full Poincare Mueller Polarimetry is a new technique for characterizing samples by means of their Mueller matrix. The method is based on the use of a full Poincare beam as a generator of polarization states. These beams present different polarization states, covering the entire Poincare sphere surface, at different points in the beam cross section. To obtain the Mueller matrix, Stokes parameters are collected at both the entrance and the output of the sample. They are calculated from irradiance measurements at each pixel of a CCD camera for different configurations of the polarization state analyzer. These measurements can be processed in several ways. In this work, we propose to use Bayesian inference, in particular, Markov chain Monte Carlo methods, to obtain, without any prior knowledge of the sample, its Mueller matrix together with its uncertainties. The new approach is tested with experimental measurements of different samples and compared with the real theoretical Mueller matrices. Excellent agreement is observed between the experimental results and the theoretical ones for all the samples tested.
PB Elsevier
SN 0030-3992
YR 2024
FD 2024-01
LK https://hdl.handle.net/20.500.14352/128885
UL https://hdl.handle.net/20.500.14352/128885
LA eng
NO J.C. Suárez-Bermejo, J. Gorgas, S. Pascual, M. Santarsiero, J.C.G. De Sande, G. Piquero, Bayesian inference approach for Full Poincaré Mueller polarimetry, Optics & Laser Technology 168 (2024) 109983. https://doi.org/10.1016/j.optlastec.2023.109983.
NO © 2023 Elsevier Ltd.
NO Ministerio de Ciencia e Innovación (España)
NO Agencia Estatal de Investigación
NO European Commission
DS Docta Complutense
RD 21 dic 2025