October 2017

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A Conversation on Neural Networks, from Polymorph Recognition to Acceleration of Quantum Simulations

A Conversation on Neural Networks, from Polymorph Recognition to Acceleration of Quantum Simulations

With Prof. Christoph Dellago (CD), University of Vienna, and Dr. Donal Mackernan (DM), University College Dublin.

Recently there has been a dramatic increase in the use of machine learning in physics and chemistry, including its use to accelerate simulations of systems at an ab-initio level of accuracy, as well as for pattern recognition. It is now clear that these developments will significantly increase the impact of simulations on large scale systems requiring a quantum level of treatment, both for ground and excited states. These developments also lend themselves to simulations on massively parallel computing platforms, in many cases using classical simulation engines for quantum systems.

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Rare events, path sampling and the

OpenPathSampling package

In the last few years, modelling of rare events has made tremendous progress and several computational methods have been put forward to study these events. Despite this effort, new approaches have not yet been included, with adequate efficiency and scalability, in common simulation packages. One objective of the Classical Dynamics Work Package of the project E-CAM is to close this gap. The present text is an easy-to-read article on the use of path sampling methods to study rare events, and the role of the OpenPathSampling package to performing these simulations. Practical applications of rare events sampling and scalabilities opportunities in OpenPathSampling are also discussed.

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Featured Software Modules


Path density for OpenPathSampling

Module path density implements path density calculations for the OpenPathSampling (OPS) package, including a generic multidimensional sparse histogram, and plotting functions for the two-dimensional case. Path density plots provide a way to visualize kinetic information obtained from path sampling, such as the mechanism of a rare event. In addition, the code in this module can also be used to visualize thermodynamic information such as free energy landscapes.

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Second-Order Differencing Scheme

This module, SodLib, provides exact wavefunction propagation using the second-order differencing (SOD) integrator scheme to solve the time-dependent Schrödinger equation as described by Leforestier et al, J. Comp Phys, 94, 59-80, 1991. Within this scheme the time interval is determined through dividing hbar by the eigenvalue of the Hamiltonian operator with the largest absolute value. This routine has been implemented …

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LibOMM : Orbital Minimization Method Library

Purpose The library LibOMM solves the Kohn-Sham equation as a generalized eigenvalue problem for a fixed Hamiltonian. It implements the orbital minimization method (OMM), which works within a density matrix formalism. The basic strategy of the OMM is to find the set of Wannier functions (WFs) describing the occupied subspace by direct unconstrained minimization of an appropriately-constructed functional. The density …

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Analysis of charge dipole moments in DL_MESO_DPD

The present module, gen_dipole.f90, is a generalization of the dipole.f90 post-processing utility of DL_MESO_DPD, the Dissipative Particle Dynamics (DPD) code from the DL_MESO package. It processes the trajectory (HISTORY) files to obtain the charge dipole moments of all the (neutral) molecules in the system. It produces files dipole_* containing the time evolution of relevant quantities (see module documentation for …

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E-CAM Publications

The opposing effects of isotropic and anisotropic attraction on association kinetics of proteins and colloids
Arthur C. Newton, Ramses Kools, David W. H. Swenson, and Peter G. Bolhuis,
J. Chem. Phys. 2017, 147, 155101

A parallel orbital-updating based plane-wave basis method for electronic structure calculations
Yan Pana, Xiaoying Dai, Stefano de Gironcolib, Xin-Gao Gongc, Gian-Marco Rignanesed and Aihui Zhoua, J. Comput. Phys. 2017, 348, 482-492

Benchmarking a Fast Proton Titration Scheme in Implicit Solvent for Biomolecular Simulations
Fernando Luís Barroso da Silva and Donal MacKernan, J. Chem. Theory Comput. 2017, 13, 2915-2929

Towards Open Boundary Molecular Dynamics Simulation of Ionic Liquids
Christian Krekeler and Luigi Delle Site, Phys. Chem. Chem. Phys. 2017, 19, 4701-4709

We are currently working on a program of events for 2018. Program expected release: 20 November 2017. Stay-tuned!


  • D1.2: Classical MD E-CAM modules I
Software modules based on the OpenPathSampling package, for the simulation of rare events using path sampling techniques.
  • D2.1: Electronic structure E-CAM modules I
New libraries revolved around the broad theme of solvers, written by the ESL developers team, starting from an E-CAM workshop.

  • D3.1: Quantum dynamics E-CAM modules I
Software modules in quantum dynamics, which are related to an E-CAM workshop held at Maison de la Simulation, Paris.

  • D4.2: Meso- and multi-scale modelling E-CAM modules I
Software module based on the DL_MESO_DPD and the ESPResSo+ simulation codes, in the framework of pilot projects which involve industrial partnerships.
  • D7.3: Hardware Developments II
Report on the hardware developments that we see relevant to the E-CAM community in the 3-5 year horizon; as well as a summary of the software needs to explore extreme-scale resources; and feedback to software developers, and hardware and software vendors.
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