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PRODID:-//Memento EPFL//
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SUMMARY:CECAM workshop on "Quantum2 on machine learning enhanced sampling"
DTSTART:20231129T090000
DTEND:20231201T123000
DTSTAMP:20260503T022650Z
UID:c9ef34b5debc6678b8380efe234f29455fc453417ecb1ab3abeeffa1
CATEGORIES:Conferences - Seminars
DESCRIPTION:You can apply to participate and find all the relevant informa
 tion (speakers\, abstracts\, program\,...) on the event website: https://
 www.cecam.org/workshop-details/1255\nRegistration deadline: 25th Oct 2023\
 n\nDescriprion:\nEnhanced sampling methods (ES) and machine learning poten
 tials (MLPs) have enabled classical molecular dynamics (MD) simulations to
  characterize molecular systems in a reasonable computational time: ES all
 ows to explore broader portions of the configuration space much faster tha
 n conventional MD [1]\, while MLPs can reach ab initio accuracy at the cos
 t of a force field [2]\, making possible\, for instance\, to include solve
 nt effects in chemical reactions [3]. However\, the accuracy of classical 
 MD is limited in cases where nuclear quantum effects (NQEs) are important\
 , for example\, when computing equilibrium properties of hydrogen-bonded s
 ystems like water[4] or chemical transformations where proton transfers ar
 e at play\, which is the case for many biological systems such as the DNA 
 [5\,6].\nMany of the methods used to include NQEs are based on the path in
 tegral approach [7-10] and need the introduction of many replicas of the s
 ystem\, increasing the computational cost. For this reason\, these methods
  would benefit from the introduction of MLPs along with ES\, which can ach
 ieve ab initio accuracy for all the atoms while keeping the computational 
 cost low. ES and MLPs are independent of each other\, hence easily compati
 ble. In the case of methods that treat NQEs\, the introduction of replicas
  has an influence on how ES and MLPs should be used. In fact\, during the 
 training of the MLPs\, it must be taken into account that the distribution
  sampled by NQEs is different from the classical one. Still\, it is not cl
 ear how to do it\, or if it would be possible to train on entire ring poly
 mers\, rather than just replicas of the system. Another question is how so
 lvent effects brought by MLPs couple with a system treated at the quantum 
 level.\nIn this workshop\, we will discuss recent developments and applica
 tions on enhanced sampling and nuclear quantum effects and how the use of 
 machine learning potentials can be a practical bridge between the two aspe
 cts. This will be made possible through a variety of talks\, given by invi
 ted but also contributed experts coming from different communities\, with 
 the main aim being to raise discussions and find solutions to the question
  of including nuclear quantum effects in the study of chemical reactions. 
 Such advances would improve accuracy in predicting both kinetic and thermo
 dynamic properties. Moreover\, a big part of this workshop will be dedicat
 ed to discussions\, establishing a common language and sketching ideas for
  future works in the three communities.\n\nReference\n[1] F. Pietrucci\, R
 eviews in Physics\, 2\, 32-45 (2017)\n[2] J. Behler\, M. Parrinello\, Phy
 s. Rev. Lett.\, 98\, 146401 (2007)\n[3] M. Yang\, L. Bonati\, D. Polino\,
  M. Parrinello\, Catalysis Today\, 387\, 143-149 (2022)\n[4] M. Ceriotti\
 , W. Fang\, P. Kusalik\, R. McKenzie\, A. Michaelides\, M. Morales\, T. Ma
 rkland\, Chem. Rev.\, 116\, 7529-7550 (2016)\n[5] A. Pérez\, M. Tuckerma
 n\, H. Hjalmarson\, O. von Lilienfeld\, J. Am. Chem. Soc.\, 132\, 11510-1
 1515 (2010)\n[6] W. Fang\, J. Chen\, M. Rossi\, Y. Feng\, X. Li\, A. Micha
 elides\, J. Phys. Chem. Lett.\, 7\, 2125-2131 (2016)\n[7] B. Berne\, J. S
 tat. Phys.\, 43\, 911-929 (1986)\n[8] B. Berne\, D. Thirumalai\, Annu. Re
 v. Phys. Chem.\, 37\, 401-424 (1986)\n[9] J. Cao\, G. Voth\, The Journal 
 of Chemical Physics\, 100\, 5093-5105 (1994)\n[10] I. Craig\, D. Manolopo
 ulos\, The Journal of Chemical Physics\, 121\, 3368-3373 (2004)\n 
LOCATION:BCH 2103 https://plan.epfl.ch/?room==BCH%202103
STATUS:CONFIRMED
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