A Hybrid Monte Carlo algorithm for sampling rare events in space-time histories of stochastic fields

التفاصيل البيبلوغرافية
العنوان: A Hybrid Monte Carlo algorithm for sampling rare events in space-time histories of stochastic fields
المؤلفون: Margazoglou, G., Biferale, L., Grauer, R., Jansen, K., Mesterházy, D., Rosenow, T., Tripiccione, R.
المصدر: Phys. Rev. E 99, 053303 (2019)
سنة النشر: 2018
المجموعة: Condensed Matter
High Energy Physics - Lattice
Nonlinear Sciences
Physics (Other)
مصطلحات موضوعية: Physics - Computational Physics, Condensed Matter - Statistical Mechanics, High Energy Physics - Lattice, Nonlinear Sciences - Chaotic Dynamics, Physics - Fluid Dynamics
الوصف: We introduce a variant of the Hybrid Monte Carlo (HMC) algorithm to address large-deviation statistics in stochastic hydrodynamics. Based on the path-integral approach to stochastic (partial) differential equations, our HMC algorithm samples space-time histories of the dynamical degrees of freedom under the influence of random noise. First, we validate and benchmark the HMC algorithm by reproducing multiscale properties of the one-dimensional Burgers equation driven by Gaussian and white-in-time noise. Second, we show how to implement an importance sampling protocol to significantly enhance, by orders of magnitudes, the probability to sample extreme and rare events, making it possible to estimate moments of field variables of extremely high order (up to 30 and more). By employing reweighting techniques, we map the biased configurations back to the original probability measure in order to probe their statistical importance. Finally, we show that by biasing the system towards very intense negative gradients, the HMC algorithm is able to explore the statistical fluctuations around instanton configurations. Our results will also be interesting and relevant in lattice gauge theory since they provide insight into reweighting techniques.
Comment: 23 pages, 16 figures; revised manuscript and updated figures based on published version
نوع الوثيقة: Working Paper
DOI: 10.1103/PhysRevE.99.053303
URL الوصول: http://arxiv.org/abs/1808.02020
رقم الأكسشن: edsarx.1808.02020
قاعدة البيانات: arXiv
الوصف
DOI:10.1103/PhysRevE.99.053303