Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model

Hsu, Tim; Sadigh, Babak; Bulatov, Vasily; Zhou, Fei

doi:10.1021/acs.jctc.3c01361

Title: Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model

Journal Article · 14 March 2024 · Journal of Chemical Theory and Computation

DOI: https://doi.org/10.1021/acs.jctc.3c01361 · OSTI ID:2324663

^[1]; Sadigh, Babak ^[1]; Bulatov, Vasily ^[1]; Zhou, Fei ^[1]

Lawrence Livermore National Laboratory, Livermore, California 94551, United States

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Sponsoring Organization:: USDOE

OSTI ID:: 2324663

Alternate ID(s):: OSTI ID: 2370158

Journal Information:: Journal of Chemical Theory and Computation, Journal Name: Journal of Chemical Theory and Computation Journal Issue: 6 Vol. 20; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (58)

Perspective: Machine learning potentials for atomistic simulations Behler, Jörg The Journal of Chemical Physics, Vol. 145, Issue 17 https://doi.org/10.1063/1.4966192	journal	November 2016
Phase Transition for a Hard Sphere System Alder, B. J.; Wainwright, T. E. The Journal of Chemical Physics, Vol. 27, Issue 5 https://doi.org/10.1063/1.1743957	journal	November 1957
Learning dislocation dynamics mobility laws from large-scale MD simulations Bertin, Nicolas; Bulatov, Vasily V.; Zhou, Fei arXiv https://doi.org/10.48550/arXiv.2309.14450	preprint	January 2023
From data to noise to data for mixing physics across temperatures with generative artificial intelligence Wang, Yihang; Herron, Lukas; Tiwary, Pratyush Proceedings of the National Academy of Sciences, Vol. 119, Issue 32 https://doi.org/10.1073/pnas.2203656119	journal	August 2022
Accelerate Microstructure Evolution Simulation Using Graph Neural Networks with Adaptive Spatiotemporal Resolution Fan, Shaoxun; Hitt, Andrew L.; Tang, Ming arXiv https://doi.org/10.48550/arXiv.2310.15153	preprint	January 2023
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems Zhang, Xuan; Wang, Limei; Helwig, Jacob arXiv https://doi.org/10.48550/arXiv.2307.08423	preprint	January 2023
Score-based denoising for atomic structure identification Hsu, Tim; Sadigh, Babak; Bertin, Nicolas arXiv https://doi.org/10.48550/arXiv.2212.02421	preprint	January 2022
Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism Wang, Qian; Ripamonti, Nicolò; Hesthaven, Jan S. Journal of Computational Physics, Vol. 410 https://doi.org/10.1016/j.jcp.2020.109402	journal	June 2020
Calculation of excess free energies of precipitates via direct thermodynamic integration across phase boundaries Sadigh, Babak; Erhart, Paul Physical Review B, Vol. 86, Issue 13 https://doi.org/10.1103/PhysRevB.86.134204	journal	October 2012
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations Wu, Fang; Li, Stan Z. Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37, Issue 4 https://doi.org/10.1609/aaai.v37i4.25663	journal	June 2023
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling Lu, Jiarui; Zhong, Bozitao; Zhang, Zuobai arXiv https://doi.org/10.48550/arXiv.2306.03117	preprint	January 2023
Machine learning to improve efficiency of non-empirical interaction parameter for dissipative particle dynamics (DPD) simulation Doi, Hideo; Matsuoka, Sota; Okuwaki, Koji Japanese Journal of Applied Physics, Vol. 62, Issue 7 https://doi.org/10.35848/1347-4065/ace575	journal	July 2023
Transport, Collective Motion, and Brownian Motion Mori, Hazime Progress of Theoretical Physics, Vol. 33, Issue 3 https://doi.org/10.1143/PTP.33.423	journal	March 1965
Accelerating discrete dislocation dynamics simulations with graph neural networks Bertin, Nicolas; Zhou, Fei Journal of Computational Physics, Vol. 487 https://doi.org/10.1016/j.jcp.2023.112180	journal	August 2023
Nonlinear generalized Langevin equations Zwanzig, Robert Journal of Statistical Physics, Vol. 9, Issue 3 https://doi.org/10.1007/BF01008729	journal	November 1973
Replica-exchange molecular dynamics method for protein folding Sugita, Yuji; Okamoto, Yuko Chemical Physics Letters, Vol. 314, Issue 1-2 https://doi.org/10.1016/S0009-2614(99)01123-9	journal	November 1999
First-Passage Monte Carlo Algorithm: Diffusion without All the Hops Opplestrup, Tomas; Bulatov, Vasily V.; Gilmer, George H. Physical Review Letters, Vol. 97, Issue 23 https://doi.org/10.1103/PhysRevLett.97.230602	journal	December 2006
Introducing Memory in Coarse-Grained Molecular Simulations Klippenstein, Viktor; Tripathy, Madhusmita; Jung, Gerhard The Journal of Physical Chemistry B, Vol. 125, Issue 19 https://doi.org/10.1021/acs.jpcb.1c01120	journal	May 2021
Escaping free-energy minima Laio, A.; Parrinello, M. Proceedings of the National Academy of Sciences, Vol. 99, Issue 20 https://doi.org/10.1073/pnas.202427399	journal	September 2002
A comparison of united atom, explicit atom, and coarse-grained simulation models for poly(ethylene oxide) Chen, Chunxia; Depa, Praveen; Sakai, Victoria García The Journal of Chemical Physics, Vol. 124, Issue 23 https://doi.org/10.1063/1.2204035	journal	June 2006
The MARTINI Coarse-Grained Force Field: Extension to Proteins Monticelli, Luca; Kandasamy, Senthil K.; Periole, Xavier Journal of Chemical Theory and Computation, Vol. 4, Issue 5 https://doi.org/10.1021/ct700324x	journal	April 2008
Recent advances in the development and application of implicit solvent models in biomolecule simulations Feig, Michael; Brooks, Charles L. Current Opinion in Structural Biology, Vol. 14, Issue 2 https://doi.org/10.1016/j.sbi.2004.03.009	journal	April 2004
LINCS: A linear constraint solver for molecular simulations Hess, Berk; Bekker, Henk; Berendsen, Herman J. C. Journal of Computational Chemistry, Vol. 18, Issue 12 https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H	journal	September 1997
Machine Learning of Coarse-Grained Molecular Dynamics Force Fields Wang, Jiang; Olsson, Simon; Wehmeyer, Christoph ACS Central Science https://doi.org/10.1021/acscentsci.8b00913	journal	April 2019
Simulating Microscopic Hydrodynamic Phenomena with Dissipative Particle Dynamics Hoogerbrugge, P. J.; Koelman, J. M. V. A. Europhysics Letters (EPL), Vol. 19, Issue 3 https://doi.org/10.1209/0295-5075/19/3/001	journal	June 1992
Temperature-accelerated dynamics for simulation of infrequent events So/rensen, Mads R.; Voter, Arthur F. The Journal of Chemical Physics, Vol. 112, Issue 21 https://doi.org/10.1063/1.481576	journal	June 2000
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics Klein, Leon; Foong, Andrew Y. K.; Fjelde, Tor Erlend arXiv https://doi.org/10.48550/arXiv.2302.01170	preprint	January 2023
Butane dihedral angle dynamics in water is dominated by internal friction Daldrop, Jan O.; Kappler, Julian; Brünig, Florian N. Proceedings of the National Academy of Sciences, Vol. 115, Issue 20 https://doi.org/10.1073/pnas.1722327115	journal	April 2018
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning Zheng, Shuxin; He, Jiyan; Liu, Chang arXiv https://doi.org/10.48550/arXiv.2306.05445	preprint	January 2023
Construction of dissipative particle dynamics models for complex fluids via the Mori–Zwanzig formulation Li, Zhen; Bian, Xin; Caswell, Bruce Soft Matter, Vol. 10, Issue 43 https://doi.org/10.1039/C4SM01387E	journal	January 2014
Crystal Diffusion Variational Autoencoder for Periodic Material Generation Xie, Tian; Fu, Xiang; Ganea, Octavian-Eugen arXiv https://doi.org/10.48550/arXiv.2110.06197	preprint	January 2021
A Connection Between Score Matching and Denoising Autoencoders Vincent, Pascal Neural Computation, Vol. 23, Issue 7 https://doi.org/10.1162/NECO_a_00142	journal	July 2011
Fast Graph Representation Learning with PyTorch Geometric Fey, Matthias; Lenssen, Jan Eric arXiv https://doi.org/10.48550/arXiv.1903.02428	preprint	January 2019
Coarse-grained models of protein folding: toy models or predictive tools? Clementi, Cecilia Current Opinion in Structural Biology, Vol. 18, Issue 1 https://doi.org/10.1016/j.sbi.2007.10.005	journal	February 2008
Machine learning for molecular and materials science Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh Nature, Vol. 559, Issue 7715 https://doi.org/10.1038/s41586-018-0337-2	journal	July 2018
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning Noé, Frank; Olsson, Simon; Köhler, Jonas Science, Vol. 365, Issue 6457 https://doi.org/10.1126/science.aaw1147	journal	September 2019
Accelerated Molecular Dynamics Methods: Introduction and Recent Developments Perez, Danny; Uberuaga, Blas P.; Shim, Yunsic Annual Reports in Computational Chemistry, Vol. 5, p. 79-98 https://doi.org/10.1016/S1574-1400(09)00504-0	book	January 2009
Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning Fu, Xiang; Xie, Tian; Rebello, Nathan J. arXiv https://doi.org/10.48550/arXiv.2204.10348	preprint	January 2022
Monte Carlo Simulations Frenkel, Daan; Smit, Berend Understanding Molecular Simulation, 2nd edition https://doi.org/10.1016/B978-012267351-1/50005-5	book	September 2002
Parallel replica method for dynamics of infrequent events Voter, Arthur F. Physical Review B, Vol. 57, Issue 22 https://doi.org/10.1103/PhysRevB.57.R13985	journal	June 1998
Molecular dynamics with coupling to an external bath Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F. The Journal of Chemical Physics, Vol. 81, Issue 8 https://doi.org/10.1063/1.448118	journal	October 1984
GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers Abraham, Mark James; Murtola, Teemu; Schulz, Roland SoftwareX, Vol. 1-2 https://doi.org/10.1016/j.softx.2015.06.001	journal	September 2015
Combining molecular dynamics with Monte Carlo simulations: implementations and applications Neyts, Erik C.; Bogaerts, Annemie Theoretical Chemistry Accounts, Vol. 132, Issue 2 https://doi.org/10.1007/s00214-012-1320-x	journal	December 2012
Gaussian Error Linear Units (GELUs) Hendrycks, Dan; Gimpel, Kevin arXiv https://doi.org/10.48550/arXiv.1606.08415	preprint	January 2016
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics Schreiner, Mathias; Winther, Ole; Olsson, Simon arXiv https://doi.org/10.48550/arXiv.2305.18046	preprint	January 2023
Scalable parallel Monte Carlo algorithm for atomistic simulations of precipitation in alloys Sadigh, Babak; Erhart, Paul; Stukowski, Alexander Physical Review B, Vol. 85, Issue 18 https://doi.org/10.1103/PhysRevB.85.184203	journal	May 2012
Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids Jorgensen, William L.; Maxwell, David S.; Tirado-Rives, Julian Journal of the American Chemical Society, Vol. 118, Issue 45 https://doi.org/10.1021/ja9621760	journal	January 1996
Self-supervised learning and prediction of microstructure evolution with convolutional recurrent neural networks Yang, Kaiqi; Cao, Yifan; Zhang, Youtian Patterns, Vol. 2, Issue 5 https://doi.org/10.1016/j.patter.2021.100243	journal	May 2021
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism Li, Zhen; Bian, Xin; Li, Xiantao The Journal of Chemical Physics, Vol. 143, Issue 24 https://doi.org/10.1063/1.4935490	journal	December 2015
Metadynamics As a Tool for Mapping the Conformational and Free-Energy Space of Peptides — The Alanine Dipeptide Case Study Vymětal, Jiří; Vondrášek, Jiří The Journal of Physical Chemistry B, Vol. 114, Issue 16 https://doi.org/10.1021/jp100950w	journal	April 2010
Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems Darden, Tom; York, Darrin; Pedersen, Lee The Journal of Chemical Physics, Vol. 98, Issue 12 https://doi.org/10.1063/1.464397	journal	June 1993
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics Arts, Marloes; Garcia Satorras, Victor; Huang, Chin-Wei Journal of Chemical Theory and Computation, Vol. 19, Issue 18 https://doi.org/10.1021/acs.jctc.3c00702	journal	September 2023
Diffusion Models: A Comprehensive Survey of Methods and Applications Yang, Ling; Zhang, Zhilong; Song, Yang ACM Computing Surveys, Vol. 56, Issue 4 https://doi.org/10.1145/3626235	journal	November 2023
Hyperdynamics: Accelerated Molecular Dynamics of Infrequent Events Voter, Arthur F. Physical Review Letters, Vol. 78, Issue 20 https://doi.org/10.1103/PhysRevLett.78.3908	journal	May 1997
Comparison of simple potential functions for simulating liquid water Jorgensen, William L.; Chandrasekhar, Jayaraman; Madura, Jeffry D. The Journal of Chemical Physics, Vol. 79, Issue 2 https://doi.org/10.1063/1.445869	journal	July 1983
Neural Parametric Fokker--Planck Equation Liu, Shu; Li, Wuchen; Zha, Hongyuan SIAM Journal on Numerical Analysis, Vol. 60, Issue 3 https://doi.org/10.1137/20M1344986	journal	June 2022
Learning Mesh-Based Simulation with Graph Networks Pfaff, Tobias; Fortunato, Meire; Sanchez-Gonzalez, Alvaro arXiv https://doi.org/10.48550/arXiv.2010.03409	text	January 2020
SE(3)-Equivariant Energy-based Models for End-to-End Protein Folding Wu, Jiaxiang; Shen, Tao; Lan, Haidong bioRxiv https://doi.org/10.1101/2021.06.06.447297	preprint	June 2021

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