Latent Spaces for Langevin Dynamics
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908698992967680 |
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| author | Bruce, Andy Aghili, Alexander Marinescu, Razvan Sabo, Daniel |
| author_facet | Bruce, Andy Aghili, Alexander Marinescu, Razvan Sabo, Daniel |
| contents | In the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of coarse-graining functions. In this paper, we derive a general family of coarse-graining embedding functions for which Langevin dynamics samples correctly. These equations have significant implications for molecular simulations and pave the way for Langevin dynamics on non-geometric coarse-graining representations, such as those provided by principal components of component analysis or latent embeddings of molecules obtained from neural networks. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2510_25773 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Latent Spaces for Langevin Dynamics Bruce, Andy Aghili, Alexander Marinescu, Razvan Sabo, Daniel Chemical Physics In the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of coarse-graining functions. In this paper, we derive a general family of coarse-graining embedding functions for which Langevin dynamics samples correctly. These equations have significant implications for molecular simulations and pave the way for Langevin dynamics on non-geometric coarse-graining representations, such as those provided by principal components of component analysis or latent embeddings of molecules obtained from neural networks. |
| title | Latent Spaces for Langevin Dynamics |
| topic | Chemical Physics |
| url | https://arxiv.org/abs/2510.25773 |