Free Energy Calculation

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Free energy calculation estimates the relative stability of states, which helps explain processes such as protein folding, molecular binding, and material phase transitions. Established approaches include thermodynamic integration, BAR and MBAR, and enhanced sampling, while newer diffusion, flow, and autoregressive models generate configurations or improve sampling. Methods are tested on molecular systems such as proteins and hydration, and on lattice models and alloys; machine-learning interatomic potentials also help estimate finite-temperature material properties. A central challenge is accurately sampling rare states when phases have little overlap, while keeping estimates reliable and computationally efficient across different systems.

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21 papers0 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

SPIBER: Reconstructing Free Energy Landscapes from Short, Unconverged Trajectories with Generative Flow Networks
Sep 19, 2026Venkata Sai Sreyas Adury, Pratyush TiwaryFree Energy Calculation Molecular Dynamics Simulation
Chemical Physics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Biophysics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Department of Chemistry and Biochemistry and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA +1
FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions
Sep 1, 2026Kyucheol Min, Elyssa Hofgard, Tess SmidtFree Energy Calculation Materials Science
Massachusetts Institute of Technology Cambridge, MA 02139
Universal Thermodynamic Interatomic Potentials for Crystalline Materials
Aug 14, 2026Juno Nam, Bowen Deng, Xiaochen Du +3Computational Materials Science Free Energy Calculation
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Fundamental AI Research, Meta, San Francisco, CA 94105, USA
Free energy landscape of Dense Associative Memory
Jul 21, 2026Sumedha, Abhishek SinghFree Energy Calculation Neural Network Memorization
School of Physical Sciences, National Institute of Science Education and Research, Bhubaneswar, P.O. Jatni, 752050, India · 2Homi Bhabha National Institute, Training School Complex, Anushakti Nagar 400094, India
Expected Free Energy as Belief-Dependent Utility for rho-POMDPs
Jul 18, 2026Patrick Cooper, Alvaro VelasquezFree Energy Calculation Active Inference
Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA
Principled Direction-Free Intrinsic Motivation through Model-Free Epistemic Free-Energy Estimators
Jul 18, 2026Alireza Furutanpey, Schahram DustdarFree Energy Calculation Intrinsic Reward Methods
Coovally, Barcelona, Spain · Distributed Systems Group, TU Vienna, Austria · ICREA Barcelona, Spain
AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms
Jul 3, 2026Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5Free Energy Calculation Boltzmann Sampling
Valence Labs · Recursion · UC Berkeley
Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout
Jun 28, 2026Wenjie XiFree Energy Calculation Molecular Dynamics Simulation
Department of Physics and HK Institute of Quantum Science & Technology, The University of Hong Kong, Pokfulam Road, Hong Kong, China
Expected Free Energy-based Planning as Variational Inference
Jun 9, 2026Wouter W. L. Nuijten, Thijs van de Laar, Bert de VriesFree Energy Calculation Active Inference
Eindhoven University of Technology, Eindhoven, the Netherlands · Lazy Dynamics B.V., the Netherlands
Conditioned free-energy density of proteins using unbalanced solutions to constraint satisfaction problems
May 31, 2026Pratik Worah, Subhash Khot, Srinivasa VaradhanFree Energy Calculation Semidefinite Programming
Free energy Estimation on Any State Space
May 29, 2026Jiajun He, Zijing Ou, Francisco Vargas +4Free Energy Calculation Doob H-Transform
University of Cambridge · Imperial College London · Xaira Therapeutics +1
MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Well-Tempered Metadynamics
May 20, 2026Xiaochen Du, Juno Nam, Jaemoo Choi +7Free Energy Calculation Adaptive Sampling
Massachusetts Institute of Technology · Georgia Institute of Technology
Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building
May 15, 2026Sauradeep Majumdar, Miguel Steiner, Johannes C. B. Dietschreit +4Free Energy Calculation Machine Learning Interatomic Potentials
Department of Material Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, United States. · Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090, Vienna, Austria. · Department of Physical and Macromolecular Chemistry, Charles University, Hlavova 8, Praha 2, 12800, Czech Republic.
CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation
May 4, 2026Ziyang Yu, Yi He, Wenbing Huang +2Free Energy Calculation Autoregressive Generation
ByteDance Seed · Department of Computer Science and Technology, Tsinghua University · Institute for AI Industry Research (AIR), Tsinghua University +2
Free Energy Surface Sampling via Reduced Flow Matching
May 1, 2026Zichen Liu, Tiejun LiFree Energy Calculation Flow Matching
Center for Data Science, Peking University · LMAM and School of Mathematical Sciences, Peking University · Center for Machine Learning Research, Peking University
Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models
Apr 10, 2026Shuo-Hui Li, Chen Chen, Yao-Wen Zhang +1Free Energy Calculation Rare-Event Estimation
Department of Physics, The Hong Kong University of Science and Technology, Hong Kong, China · Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong, China · IAS Center for AI for Scientific Discoveries, Hong Kong University of Science and Technology, Hong Kong, China
Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization
Mar 27, 2026Ajith Anil Meera, Wouter KouwFree Energy Calculation Bayesian Optimization
Faculty of Electrical Engineering, TU Eindhoven, The Netherlands
Hessian-informed machine learning interatomic potential towards bridging theory and experiments
Mar 26, 2026Bangchen Yin, Jian Ouyang, Zhen Fan +7Machine Learning Interatomic Potentials Computational Materials Science
ByteDance Seed · Tsinghua University · Peking University
Rapid Neural Network Prediction of Linear Block Copolymer Free Energies
Mar 18, 2026Ian Chen, Alfredo Alexander-KatzFree Energy Calculation Polymer Property Prediction
Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge, MA 02139
Scaling Autoregressive Models for Lattice Thermodynamics
Mar 16, 2026Xiaochen Du, Juno Nam, Sulin Liu +1Autoregressive Modeling Computational Materials Science
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models
Feb 18, 2026Yu Xie, Ludwig Winkler, Lixin Sun +10Free Energy Calculation Diffusion Sampling
Microsoft Research AI for Science

Sep 19, 2026J/K move · Enter open · S save

SPIBER: Reconstructing Free Energy Landscapes from Short, Unconverged Trajectories with Generative Flow Networks

Venkata Sai Sreyas Adury, Pratyush Tiwary

Chemical Physics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Biophysics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA · Department of Chemistry and Biochemistry and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA+1

Free Energy Calculation Molecular Dynamics Simulation

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Molecular systems have many degrees of freedom, but their metastable behavior can often be described by a few collective variables. Identifying these variables and estimating free energies along them from limited simulation data remains a challenging, important problem. Separate short trajectories may sample different metastable states without capturing transitions or establishing their relative equilibrium populations. For unbiased trajectories generated with the same Hamiltonian at a single temperature, alternate methods based on histogram reweighting cannot correct this imbalance. Here we present SPIBER, which combines the State Predictive Information Bottleneck (SPIB) with Generative Flow Networks (GFlowNets). SPIB uses deep learning to approximate slow degrees of freedom through a past-future information bottleneck, retaining information needed to predict future metastable states. We show that this compression limits conditional entropy variations in populated regions, allowing conditional mean potential energies, which are much easier to calculate, to be used to approximate free energy differences. Given sufficient local sampling to estimate these energies, they define the target distribution for GFlowNets, energy-based generative samplers that sample according to estimated thermodynamic stability rather than observed populations. For a particle in a radial double-well potential, for alanine dipeptide, and for the nine-residue peptide AIB9, SPIBER recovers free energy differences between sampled metastable states to within one thermal energy unit of reference values. The method combines collective-variable learning and free energy estimation in up to four latent dimensions, without requiring converged state populations or additional molecular dynamics simulations.