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

2025/04/22 by Gimperlein, Heiko, Maity, Ruma R., Majumdar, Apala +1 · 1 citation
#FOS: Mathematics #FOS: Physical sciences #Numerical Analysis (math.NA) #Soft Condensed Matter (cond-mat.soft) #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.2504.16029

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.

Citations

• Stochastic effects on solution landscapes for nematic liquid crystals
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