Berni Alder and the pioneering times of molecular simulation

Battimelli, Giovanni; Ciccotti, Giovanni

doi:10.1140/epjh/e2018-90027-5

Cited by 22 publications

(15 citation statements)

References 41 publications

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“…Free energy differences between different states of a system or different systems of interest are of great importance in various scientific fields. [1][2][3][4] The free energy profile or the free energy landscape depicts the variation of the free energy along generalized coordinates. From these curves or surfaces, we can get insights about various properties of the system, such as the relative stability of different states and the rate constants of transitions between them.…”

Section: Introductionmentioning

confidence: 99%

BAR-Based Multi-Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscape

Wang

Sun

2018

Preprint

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<p>Construction of free energy landscapes at Quantum mechanics (QM) level is computationally demanding. By constructing a thermodynamic cycle connecting QM states via an alchemical pathway, we can obtain converged statistics with much less computational resources. The indirect scheme of QM/ molecular mechanics (MM) free energy simulation is often orders of magnitude faster than direct QM/MM simulations. Previous reports on indirect QM/MM simulations are mostly equilibrium sampling based and nonequilibrium methods are only exploited in one-dimensional alchemical QM/MM end-state correction at two end states. In the current work, we report a multi-dimensional nonequilibrium pulling scheme for indirect QM/MM free energy simulations, where the whole free energy simulation is performed only with nonequilibrium methods. The collective variable (CV) space we explore is the combination of one alchemical CV and one physically meaningful CV. The current nonequilibrium indirect QM/MM simulation method can be seen as the generalization of equilibrium perturbation based indirect QM/MM methods. The test systems include one backbone dihedral case and one distance case. The two cases are significantly different in size, enabling us to investigate the dependence of the speedup of the indirect scheme on the size of the system. It is shown that the speedup becomes larger when the size of the system becomes larger, which is consistent with the scaling behavior of QM Hamiltonian. </p>

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Section: Introductionmentioning

confidence: 99%

BAR-Based Multi-Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscape

Wang

Sun

2018

Preprint

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“…Berni Alder, at that time was known as the inventor of the Molecular Dynamics method [Alder, 1958] which he had successfully applied to various classical model systems of statistical physics. He was very then much interested in extending his Molecular Dynamics methods to quantum systems: Berni was impressed by David Ceperley and he understood the potential developments of his thesis achievements, as he said in an interview [Battimelli, 2018] The first big problem has been the calculation of the electron gas which we have already alluded to, « the calculation that made me famous », as David Ceperley puts it. For Berni Alder, this was like a toy model, used to show that one could do an exact calculation on a N-body quantum system, just as Molecular Dynamics could do on classical N-particle models.…”

Section: Meeting Berni Aldermentioning

confidence: 99%

The early years of quantum Monte Carlo (1): the ground state

Mareschal

2021

EPJ H

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The first Monte Carlo simulation on a computer was performed at the initiative of John Von Neumann in the years 1947-48. It concerned the direct simulation of the fission reaction : many of the elementary steps, like, for example, the reactive events when a neutron collides with an Uranium nucleus, were modeled as stochastic processes and use was made of (pseudo-)random numbers to that effect. Von Neumann's simulation proposal was described in a letter written to the director of the theory division in Los Alamos, Dr. Richtmyer. The letter has been since declassified ; it is written with so 3 many details that one can figure out precisely what the computer is really doing. The simulation itself took several years to be performed, it involved several people, among whom John Von Neumann and his wife Klara, Nick Metropolis, Stan Ulam and a few others. It was performed on various computers, starting from the historic ENIAC, within a rapidly-evolving hardware architecture as well as programming technique: at some stage, it involved the creation of the storedprogram concept [Haigh, 2014].This work is well documented and has been already analyzed by Peter Galison [Galison, 1996] as symptomatic of the paradigm shift induced by the computer in the physical sciences (the so-called trading zone).Those years of post-war period were years of great intellectual freedom and creativity. It also led to the organisation of several scientific meetings where engineers, chemists, physicists and mathematicians would discuss the possibilities offered by the new electronic machines [Hurd,1985]. Among topics being discussed, the use of statistical sampling and probability theory to produce solutions to partial differential equations and integro-differential equations .

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“…Early pioneers started with the very first molecular dynamics or Monte Carlo simulations of simple hard-sphere liquids or lattice models for polymers (for a historical account, see Ref. [1]). While these first in silico experiments at the time were genuinely exploratory, their applicability, of course, was strongly hampered by the limitations of available soft-and hardware.…”

Section: Introductionmentioning

confidence: 99%

“…th (x) + T hermostat (T1) and I(2) = F(2) th (x) + T hermostat (T2) so that I(1) + I(2) = F(1) th (x) + T hermostat (T1) + F (2) th (x) + T hermostat (T2)…”

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confidence: 99%

From adaptive resolution to molecular dynamics of open systems

et al. 2021

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We provide an overview of the Adaptive Resolution Simulation method (AdResS) based on discussing its basic principles and presenting its current numerical and theoretical developments. Examples of applications to systems of interest to soft matter, chemical physics, and condensed matter illustrate the method’s advantages and limitations in its practical use and thus settle the challenge for further future numerical and theoretical developments. Graphic abstract

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Berni Alder and the pioneering times of molecular simulation

Cited by 22 publications

References 41 publications

BAR-Based Multi-Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscape

BAR-Based Multi-Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscape

The early years of quantum Monte Carlo (1): the ground state

From adaptive resolution to molecular dynamics of open systems

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