Bayesian umbrella quadrature accelerates free-energy calculations across diverse molecular systems and processes
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917199841591296 |
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| author | Kempkes, Eline K. Ortíz, Alberto Pérez de Alba |
| author_facet | Kempkes, Eline K. Ortíz, Alberto Pérez de Alba |
| contents | Biased sampling in molecular dynamics simulations overcomes timescale limitations and delivers free-energy landscapes, essential to understand complex atomistic phenomena. However, when applied across diverse systems and processes, biasing protocols often require time- and resource-consuming fine-tuning. In search for robustness, we boost a prominent biasing method, Umbrella Sampling. To estimate the value of an integral, i.e., the free energy, our Bayesian Umbrella Quadrature (BUQ) method iteratively selects gradient samples, i.e., bias locations, that most reduce the posterior integral variance based on a noise-tolerant Gaussian process model, which also effectively interpolates between samples. We validate the method for a conformational change in a small peptide, a water-to-ice phase transition, and a substitution chemical reaction; obtaining excellent accuracies and speedups. To ease adoption of this more automated and universal free-energy method, we interface BUQ with wide-spread simulation packages and share hyperparametrization guidelines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08783 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bayesian umbrella quadrature accelerates free-energy calculations across diverse molecular systems and processes Kempkes, Eline K. Ortíz, Alberto Pérez de Alba Statistical Mechanics Chemical Physics Biased sampling in molecular dynamics simulations overcomes timescale limitations and delivers free-energy landscapes, essential to understand complex atomistic phenomena. However, when applied across diverse systems and processes, biasing protocols often require time- and resource-consuming fine-tuning. In search for robustness, we boost a prominent biasing method, Umbrella Sampling. To estimate the value of an integral, i.e., the free energy, our Bayesian Umbrella Quadrature (BUQ) method iteratively selects gradient samples, i.e., bias locations, that most reduce the posterior integral variance based on a noise-tolerant Gaussian process model, which also effectively interpolates between samples. We validate the method for a conformational change in a small peptide, a water-to-ice phase transition, and a substitution chemical reaction; obtaining excellent accuracies and speedups. To ease adoption of this more automated and universal free-energy method, we interface BUQ with wide-spread simulation packages and share hyperparametrization guidelines. |
| title | Bayesian umbrella quadrature accelerates free-energy calculations across diverse molecular systems and processes |
| topic | Statistical Mechanics Chemical Physics |
| url | https://arxiv.org/abs/2601.08783 |