Free Energy Surface Sampling via Reduced Flow Matching

• URL: http://arxiv.org/abs/2605.00337v1
• Date: Fri, 01 May 2026 01:35:48 GMT
• Title: Free Energy Surface Sampling via Reduced Flow Matching
• Abstract summary: We propose a reduced flow matching (FM) method for free energy sampling (FES)<n>We train a dynamical transport map in the CV space, thereby enabling direct sampling of the free energy surface.<n>We evaluate the proposed method across a variety of potential functions and collective variables.
• Score: 17.93274903825365
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Sampling the free energy surface, namely, the distribution of collective variables (CVs), is a crucial problem in statistical physics, as it underpins a better understanding of chemical reactions and conformational transitions. Traditional methods for free energy surface sampling involve simulation in high-dimensional configuration space and projecting the resulting configurations onto the CV space. To reduce the computational costs of such sampling, we propose FES-FM, a reduced flow matching (FM) method for free energy sampling (FES). We train a dynamical transport map in the CV space, thereby enabling direct sampling of the free energy surface. For many-particle systems, we construct a prior distribution based on the Hessian at a local minimum of the potential, which ensures both rotation-translation invariance and physically meaningful configurations. We evaluate the proposed method across a variety of potential functions and collective variables. Comparative experiments demonstrate that our approach drastically reduces computational costs while delivering superior accuracy per unit sampling time.

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