Stochastic Neural Network Approach for Learning High-Dimensional Free Energy Surfaces

Physical Review Letters

Volumn 119, Issue 15, 2017, Pages

  Schneider, Elia ^a   Dai, Luke ^a   Topper, Robert Q ^b   Drechsel Grau, Christof ^a   Tuckerman, Mark E ^a,c,d  

^a NEW YORK UNIVERSITY   (United States)

^b The Cooper Union for the Advancement of Science and Art   (United States)

^c NEW YORK UNIVERSITY   (United States)

^d NEW YORK UNIVERSITY SHANGHAI   (China)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; STOCHASTIC SYSTEMS;

COMPLEX MOLECULAR SYSTEMS; COMPUTATIONAL CHALLENGES; CONFORMATIONAL EQUILIBRIUM; ENHANCED SAMPLINGS; ENSEMBLE AVERAGES; FREE ENERGY LANDSCAPE; FREE ENERGY SURFACE; STOCHASTIC NEURAL NETWORK;

FREE ENERGY;

ARTICLE; CALCULATION; LEARNING; STOCHASTIC MODEL;

EID: 85031325693     PISSN: 00319007     EISSN: 10797114     Source Type: Journal    
DOI: 10.1103/PhysRevLett.119.150601     Document Type: Article

References (37)

1. A. Laio and M. Parrinello, Proc. Natl. Acad. Sci. U.S.A. 99, 12562 (2002). PNASA6 0027-8424 10.1073/pnas.202427399
2. A. Barducci, G. Bussi, and M. Parrinello, Phys. Rev. Lett. 100, 020603 (2008). PRLTAO 0031-9007 10.1103/PhysRevLett.100.020603
3. M. Bonomi and M. Parrinello, Phys. Rev. Lett. 104, 190601 (2010). PRLTAO 0031-9007 10.1103/PhysRevLett.104.190601
4. L. Rosso, P. Mináry, Z. Zhu, and M. E. Tuckerman, J. Chem. Phys. 116, 4389 (2002). JCPSA6 0021-9606 10.1063/1.1448491
5. J. B. Abrams and M. E. Tuckerman, J. Phys. Chem. B 112, 15742 (2008). JPCBFK 1520-6106 10.1021/jp805039u
6. A. T. Tzanov, M. A. Cuendet, and M. E. Tuckerman, J. Phys. Chem. B 118, 6539 (2014). JPCBFK 1520-6106 10.1021/jp500193w
7. L. Maragliano and E. Vanden-Eijnden, Chem. Phys. Lett. 426, 168 (2006). CHPLBC 0009-2614 10.1016/j.cplett.2006.05.062
8. G. Tribello, M. Ceriotti, and M. Parrinello, Proc. Natl. Acad. Sci. U.S.A. 107, 17509 (2010). PNASA6 0027-8424 10.1073/pnas.1011511107
9. M. Rohrdanz, W. Zheng, and C. Clementi, Annu. Rev. Phys. Chem. 64, 295 (2013). ARPLAP 0066-426X 10.1146/annurev-physchem-040412-110006
10. L. Nedialkova, M. Armat, I. Kevrekidis, and G. Hummer, J. Chem. Phys. 141, 114102 (2014). JCPSA6 0021-9606 10.1063/1.4893963
11. C. Dsilva, R. Talmon, C. Gear, R. Coifman, and I. Kevrekidis, SIAM J. Appl. Dyn. Syst. 15, 1327 (2016). SJADAY 1536-0040 10.1137/151004896
12. C. M. Bishop, Pattern Recognition and Machine Learning (Springer, New York, 2006).
13. J. Behler, Int. J. Quantum Chem. 115, 1032 (2015). IJQCB2 0020-7608 10.1002/qua.24890
14. P. Geiger and C. Dellago, J. Chem. Phys. 139, 164105 (2013). JCPSA6 0021-9606 10.1063/1.4825111
15. E. Chiavazzo, R. Covino, R. R. Coifman, C. W. Geard, A. G. Georgiou, G. Hummer, and I. G. Kevrekidis, Proc. Natl. Acad. Sci. U.S.A. 114, E5494 (2017). PNASA6 0027-8424 10.1073/pnas.1621481114
16. T. Stecher, N. Bernstein, and G. Csányi, J. Chem. Theory Comput. 10, 4079 (2014). JCTCCE 1549-9618 10.1021/ct500438v
17. L. Mones, N. Bernstein, and G. Csányi, J. Chem. Theory Comput. 12, 5100 (2016). JCTCCE 1549-9618 10.1021/acs.jctc.6b00553
18. M. Chen, T.-Q. Yu, and M. E. Tuckerman, Proc. Natl. Acad. Sci. U.S.A. 112, 3235 (2015). PNASA6 0027-8424 10.1073/pnas.1418241112
19. M. Chen, M. A. Cuendet, and M. E. Tuckerman, J. Chem. Phys. 137, 024102 (2012). JCPSA6 0021-9606 10.1063/1.4733389
20. M. A. Cuendet and M. E. Tuckerman, J. Chem. Theory Comput. 10, 2975 (2014). JCTCCE 1549-9618 10.1021/ct500012b
21. K. Hornik, M. Stinchcombe, and H. White, Neural Netw. 2, 359 (1989). NNETEB 0893-6080 10.1016/0893-6080(89)90020-8
22. S. Ferrari and R. F. Stengel, IEEE Trans. Neural Networks 16, 24 (2005). ITNNEP 1045-9227 10.1109/TNN.2004.836233
23. See Supplemental Material at http://link.aps.org/supplemental/10.1103/PhysRevLett.119.150601 for description of the backpropagation method, a discussion about the dependence of the efficiency of the neural networks used in this study on their architecture, and a discussion of the use of classification networks to define thermodynamically accessible regions on the free energy surfaces generated in this study.
24. A. D. MacKerell, J. Phys. Chem. B 102, 3586 (1998). JPCBFK 1520-6106 10.1021/jp973084f
25. A. D. Mackerell, M. Feig, and C. L. Brooks, J. Comput. Chem. 25, 1400 (2004). JCCHDD 0192-8651 10.1002/jcc.20065
26. M. Karplus, J. Chem. Phys. 30, 11 (1959). JCPSA6 0021-9606 10.1063/1.1729860
27. K. A. Beauchamp, Y.-S. Lin, R. Das, and V. S. Pande, J. Chem. Theory Comput. 8, 1409 (2012). JCTCCE 1549-9618 10.1021/ct2007814
28. A. B. Belonoshko, R. Ahuja, and B. Johansson, Phys. Rev. Lett. 87, 165505 (2001). PRLTAO 0031-9007 10.1103/PhysRevLett.87.165505
29. A. B. Belonoshko, O. LeBacq, R. Ahuja, and B. Johansson, J. Chem. Phys. 117, 7233 (2002). JCPSA6 0021-9606 10.1063/1.1507775
30. F. Saija and S. Prestipino, Phys. Rev. B 72, 024113 (2005). PRBMDO 1098-0121 10.1103/PhysRevB.72.024113
31. A. B. Belonoshko, Phys. Rev. B 78, 174109 (2008). PRBMDO 1098-0121 10.1103/PhysRevB.78.174109
32. T. Q. Yu, P. Y. Chen, M. Chen, A. Samanta, E. Vanden-Eijnden, and M. E. Tuckerman, J. Chem. Phys. 140, 214109 (2014). JCPSA6 0021-9606 10.1063/1.4878665
33. M. Ross and A. K. McMahan, Phys. Rev. B 21, 1658 (1980). PRBMDO 0163-1829 10.1103/PhysRevB.21.1658
34. D. Quigley and P. M. Rodger, J. Chem. Phys. 128, 154518 (2008). JCPSA6 0021-9606 10.1063/1.2888999
35. A. N. Zisman, I. V. Aleksandrov, and S. M. Stishov, Phys. Rev. B 32, 484 (1985). PRBMDO 0163-1829 10.1103/PhysRevB.32.484
36. T. Q. Yu and M. E. Tuckerman, Phys. Rev. Lett. 107, 015701 (2011). PRLTAO 0031-9007 10.1103/PhysRevLett.107.015701
37. A. M. Reilly, Acta Crystallogr. Sect. B 72, 439 (2016). ASBSDK 0108-7681 10.1107/S2052520616007447