Bayesian Parameter Identification in the Landau-de Gennes Theory for Nematic Liquid Crystals
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866914091065409536 |
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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 |