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arXiv · 2504.16029

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

Heiko Gimperlein·Ruma R. Maity·Apala Majumdar·Michael Oberguggenberger
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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.

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Heiko Gimperlein, Ruma R. Maity, Apala Majumdar, Michael Oberguggenberger. 2025-04-22. Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals. https://doi.org/10.1098/rspa.2025.0355

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