FEAT: Free energy Estimators with Adaptive Transport
- URL: http://arxiv.org/abs/2504.11516v1
- Date: Tue, 15 Apr 2025 15:16:18 GMT
- Title: FEAT: Free energy Estimators with Adaptive Transport
- Authors: Jiajun He, Yuanqi Du, Francisco Vargas, Yuanqing Wang, Carla P. Gomes, José Miguel Hernández-Lobato, Eric Vanden-Eijnden,
- Abstract summary: We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation.<n>FEAT leverages learned transports implemented via interpolants, alongside variational upper and lower bounds on free energy differences.<n> Experimental validation on toy examples, molecular simulations, and quantum field theory demonstrates improvements over existing learning-based methods.
- Score: 61.85373609950878
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across scientific domains. FEAT leverages learned transports implemented via stochastic interpolants and provides consistent, minimum-variance estimators based on escorted Jarzynski equality and controlled Crooks theorem, alongside variational upper and lower bounds on free energy differences. Unifying equilibrium and non-equilibrium methods under a single theoretical framework, FEAT establishes a principled foundation for neural free energy calculations. Experimental validation on toy examples, molecular simulations, and quantum field theory demonstrates improvements over existing learning-based methods.
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