Journal
PHYSICAL REVIEW RESEARCH
Volume 4, Issue 4, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevResearch.4.L042005
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Funding
- Deutsche Forschungsgemeinschaft [SFB1114, C03, A04, B08]
- European Research Council (ERC CoG) [772230]
- Berlin Mathematics center MATH + [AA1-6]
- German Ministry for Education and Research (BIFOLD-Berlin Institute for the Foundations of Learning and Data)
- European Research Council (ERC) [772230] Funding Source: European Research Council (ERC)
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Boltzmann generators solve the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method. Temperature steerable flows (TSFs) are proposed to generate a family of probability densities parametrized by a choosable temperature parameter, allowing for sampling of a physical system across multiple thermodynamic states.
Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples in thermodynamic equilibrium. The equilibrium distribution is usually defined by an energy function and a thermodynamic state. Here, we propose temperature steerable flows (TSFs) which are able to generate a family of probability densities parametrized by a choosable temperature parameter. TSFs can be embedded in generalized ensemble sampling frameworks to sample a physical system across multiple thermodynamic states.
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