Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals

Fuente: arXiv
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Main Authors: Gimperlein, Heiko, Maity, Ruma R., Majumdar, Apala, Oberguggenberger, Michael
Format: Preprint
Published: 2025
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author Gimperlein, Heiko
Maity, Ruma R.
Majumdar, Apala
Oberguggenberger, Michael
author_facet Gimperlein, Heiko
Maity, Ruma R.
Majumdar, Apala
Oberguggenberger, Michael
contents This manuscript establishes a pathway to reconstruct material parameters from measurements within the Landau-de Gennes model for nematic liquid crystals. We present a Bayesian approach to this inverse problem and analyse its properties using given, simulated data for benchmark problems of a planar bistable nematic device. In particular, we discuss the accuracy of the Markov chain Monte Carlo approximations, confidence intervals and the limits of identifiability.
format Preprint
id arxiv_https___arxiv_org_abs_2504_16029
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals
Gimperlein, Heiko
Maity, Ruma R.
Majumdar, Apala
Oberguggenberger, Michael
Numerical Analysis
Soft Condensed Matter
Statistics Theory
This manuscript establishes a pathway to reconstruct material parameters from measurements within the Landau-de Gennes model for nematic liquid crystals. We present a Bayesian approach to this inverse problem and analyse its properties using given, simulated data for benchmark problems of a planar bistable nematic device. In particular, we discuss the accuracy of the Markov chain Monte Carlo approximations, confidence intervals and the limits of identifiability.
title Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals
topic Numerical Analysis
Soft Condensed Matter
Statistics Theory
url https://arxiv.org/abs/2504.16029