Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals
Numerical Analysis
2025-10-15 v1 Soft Condensed Matter
Numerical Analysis
Statistics Theory
Statistics Theory
Abstract
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.
Keywords
Cite
@article{arxiv.2504.16029,
title = {Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals},
author = {Heiko Gimperlein and Ruma R. Maity and Apala Majumdar and Michael Oberguggenberger},
journal= {arXiv preprint arXiv:2504.16029},
year = {2025}
}
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25 pages