Efficient Evaluation of Exact Exchange for Periodic Systems Via
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Free and Open Source Software for Computational Chemistry Education
Free and Open Source Software for Computational Chemistry Education Susi Lehtola∗,y and Antti J. Karttunenz yMolecular Sciences Software Institute, Blacksburg, Virginia 24061, United States zDepartment of Chemistry and Materials Science, Aalto University, Espoo, Finland E-mail: [email protected].fi Abstract Long in the making, computational chemistry for the masses [J. Chem. Educ. 1996, 73, 104] is finally here. We point out the existence of a variety of free and open source software (FOSS) packages for computational chemistry that offer a wide range of functionality all the way from approximate semiempirical calculations with tight- binding density functional theory to sophisticated ab initio wave function methods such as coupled-cluster theory, both for molecular and for solid-state systems. By their very definition, FOSS packages allow usage for whatever purpose by anyone, meaning they can also be used in industrial applications without limitation. Also, FOSS software has no limitations to redistribution in source or binary form, allowing their easy distribution and installation by third parties. Many FOSS scientific software packages are available as part of popular Linux distributions, and other package managers such as pip and conda. Combined with the remarkable increase in the power of personal devices—which rival that of the fastest supercomputers in the world of the 1990s—a decentralized model for teaching computational chemistry is now possible, enabling students to perform reasonable modeling on their own computing devices, in the bring your own device 1 (BYOD) scheme. In addition to the programs’ use for various applications, open access to the programs’ source code also enables comprehensive teaching strategies, as actual algorithms’ implementations can be used in teaching. -
Open Babel Documentation Release 2.3.1
Open Babel Documentation Release 2.3.1 Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.) December 05, 2011 Contents 1 Introduction 3 1.1 Goals of the Open Babel project ..................................... 3 1.2 Frequently Asked Questions ....................................... 4 1.3 Thanks .................................................. 7 2 Install Open Babel 9 2.1 Install a binary package ......................................... 9 2.2 Compiling Open Babel .......................................... 9 3 obabel and babel - Convert, Filter and Manipulate Chemical Data 17 3.1 Synopsis ................................................. 17 3.2 Options .................................................. 17 3.3 Examples ................................................. 19 3.4 Differences between babel and obabel .................................. 21 3.5 Format Options .............................................. 22 3.6 Append property values to the title .................................... 22 3.7 Filtering molecules from a multimolecule file .............................. 22 3.8 Substructure and similarity searching .................................. 25 3.9 Sorting molecules ............................................ 25 3.10 Remove duplicate molecules ....................................... 25 3.11 Aliases for chemical groups ....................................... 26 4 The Open Babel GUI 29 4.1 Basic operation .............................................. 29 4.2 Options ................................................. -
On the Calculation of Molecular Properties of Heavy Element Systems with Ab Initio Approaches: from Gas-Phase to Complex Systems André Severo Pereira Gomes
On the calculation of molecular properties of heavy element systems with ab initio approaches: from gas-phase to complex systems André Severo Pereira Gomes To cite this version: André Severo Pereira Gomes. On the calculation of molecular properties of heavy element systems with ab initio approaches: from gas-phase to complex systems. Theoretical and/or physical chemistry. Universite de Lille, 2016. tel-01960393 HAL Id: tel-01960393 https://hal.archives-ouvertes.fr/tel-01960393 Submitted on 19 Dec 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. M´emoirepr´esent´epour obtenir le dipl^omed' Habilitation `adiriger des recherches { Sciences Physiques de l'Universit´ede Lille (Sciences et Technologies) ANDRE´ SEVERO PEREIRA GOMES Universit´ede Lille - CNRS Laboratoire PhLAM UMR 8523 On the calculation of molecular properties of heavy element systems with ab initio approaches: from gas-phase to complex systems M´emoirepr´esent´epour obtenir le dipl^omed' Habilitation `adiriger des recherches { Sciences Physiques de l'Universit´ede Lille (Sciences et -
In Quantum Chemistry
http://www.cca-forum.org Computational Quality of Service (CQoS) in Quantum Chemistry Joseph Kenny1, Kevin Huck2, Li Li3, Lois Curfman McInnes3, Heather Netzloff4, Boyana Norris3, Meng-Shiou Wu4, Alexander Gaenko4 , and Hirotoshi Mori5 1Sandia National Laboratories, 2University of Oregon, 3Argonne National Laboratory, 4Ames Laboratory, 5Ochanomizu University, Japan This work is a collaboration among participants in the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS), Performance Engineering Research Institute (PERI), Quantum Chemistry Science Application Partnership (QCSAP), and the Tuning and Analysis Utilities (TAU) group at the University of Oregon. Quantum Chemistry and the CQoS in Quantum Chemistry: Motivation and Approach Common Component Architecture (CCA) Motivation: CQoS Approach: CCA Overview: • QCSAP Challenges: How, during runtime, can we make the best choices • Overall: Develop infrastructure for dynamic component adaptivity, i.e., • The CCA Forum provides a specification and software tools for the for reliability, accuracy, and performance of interoperable quantum composing, substituting, and reconfiguring running CCA component development of high-performance components. chemistry components based on NWChem, MPQC, and GAMESS? applications in response to changing conditions – Performance, accuracy, mathematical consistency, reliability, etc. • Components = Composition – When several QC components provide the same functionality, what • Approach: Develop CQoS tools for – A component is a unit -
Application Profiling at the HPCAC High Performance Center Pak Lui 157 Applications Best Practices Published
Best Practices: Application Profiling at the HPCAC High Performance Center Pak Lui 157 Applications Best Practices Published • Abaqus • COSMO • HPCC • Nekbone • RFD tNavigator • ABySS • CP2K • HPCG • NEMO • SNAP • AcuSolve • CPMD • HYCOM • NWChem • SPECFEM3D • Amber • Dacapo • ICON • Octopus • STAR-CCM+ • AMG • Desmond • Lattice QCD • OpenAtom • STAR-CD • AMR • DL-POLY • LAMMPS • OpenFOAM • VASP • ANSYS CFX • Eclipse • LS-DYNA • OpenMX • WRF • ANSYS Fluent • FLOW-3D • miniFE • OptiStruct • ANSYS Mechanical• GADGET-2 • MILC • PAM-CRASH / VPS • BQCD • Graph500 • MSC Nastran • PARATEC • BSMBench • GROMACS • MR Bayes • Pretty Fast Analysis • CAM-SE • Himeno • MM5 • PFLOTRAN • CCSM 4.0 • HIT3D • MPQC • Quantum ESPRESSO • CESM • HOOMD-blue • NAMD • RADIOSS For more information, visit: http://www.hpcadvisorycouncil.com/best_practices.php 2 35 Applications Installation Best Practices Published • Adaptive Mesh Refinement (AMR) • ESI PAM-CRASH / VPS 2013.1 • NEMO • Amber (for GPU/CUDA) • GADGET-2 • NWChem • Amber (for CPU) • GROMACS 5.1.2 • Octopus • ANSYS Fluent 15.0.7 • GROMACS 4.5.4 • OpenFOAM • ANSYS Fluent 17.1 • GROMACS 5.0.4 (GPU/CUDA) • OpenMX • BQCD • Himeno • PyFR • CASTEP 16.1 • HOOMD Blue • Quantum ESPRESSO 4.1.2 • CESM • LAMMPS • Quantum ESPRESSO 5.1.1 • CP2K • LAMMPS-KOKKOS • Quantum ESPRESSO 5.3.0 • CPMD • LS-DYNA • WRF 3.2.1 • DL-POLY 4 • MrBayes • WRF 3.8 • ESI PAM-CRASH 2015.1 • NAMD For more information, visit: http://www.hpcadvisorycouncil.com/subgroups_hpc_works.php 3 HPC Advisory Council HPC Center HPE Apollo 6000 HPE ProLiant -
High-Performance Algorithms and Software for Large-Scale Molecular Simulation
HIGH-PERFORMANCE ALGORITHMS AND SOFTWARE FOR LARGE-SCALE MOLECULAR SIMULATION A Thesis Presented to The Academic Faculty by Xing Liu In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the School of Computational Science and Engineering Georgia Institute of Technology May 2015 Copyright ⃝c 2015 by Xing Liu HIGH-PERFORMANCE ALGORITHMS AND SOFTWARE FOR LARGE-SCALE MOLECULAR SIMULATION Approved by: Professor Edmond Chow, Professor Richard Vuduc Committee Chair School of Computational Science and School of Computational Science and Engineering Engineering Georgia Institute of Technology Georgia Institute of Technology Professor Edmond Chow, Advisor Professor C. David Sherrill School of Computational Science and School of Chemistry and Biochemistry Engineering Georgia Institute of Technology Georgia Institute of Technology Professor David A. Bader Professor Jeffrey Skolnick School of Computational Science and Center for the Study of Systems Biology Engineering Georgia Institute of Technology Georgia Institute of Technology Date Approved: 10 December 2014 To my wife, Ying Huang the woman of my life. iii ACKNOWLEDGEMENTS I would like to first extend my deepest gratitude to my advisor, Dr. Edmond Chow, for his expertise, valuable time and unwavering support throughout my PhD study. I would also like to sincerely thank Dr. David A. Bader for recruiting me into Georgia Tech and inviting me to join in this interesting research area. My appreciation is extended to my committee members, Dr. Richard Vuduc, Dr. C. David Sherrill and Dr. Jeffrey Skolnick, for their advice and helpful discussions during my research. Similarly, I want to thank all of the faculty and staff in the School of Compu- tational Science and Engineering at Georgia Tech. -
Modern Quantum Chemistry with [Open]Molcas
Modern quantum chemistry with [Open]Molcas Cite as: J. Chem. Phys. 152, 214117 (2020); https://doi.org/10.1063/5.0004835 Submitted: 17 February 2020 . Accepted: 11 May 2020 . Published Online: 05 June 2020 Francesco Aquilante , Jochen Autschbach , Alberto Baiardi , Stefano Battaglia , Veniamin A. Borin , Liviu F. Chibotaru , Irene Conti , Luca De Vico , Mickaël Delcey , Ignacio Fdez. Galván , Nicolas Ferré , Leon Freitag , Marco Garavelli , Xuejun Gong , Stefan Knecht , Ernst D. Larsson , Roland Lindh , Marcus Lundberg , Per Åke Malmqvist , Artur Nenov , Jesper Norell , Michael Odelius , Massimo Olivucci , Thomas B. Pedersen , Laura Pedraza-González , Quan M. Phung , Kristine Pierloot , Markus Reiher , Igor Schapiro , Javier Segarra-Martí , Francesco Segatta , Luis Seijo , Saumik Sen , Dumitru-Claudiu Sergentu , Christopher J. Stein , Liviu Ungur , Morgane Vacher , Alessio Valentini , and Valera Veryazov J. Chem. Phys. 152, 214117 (2020); https://doi.org/10.1063/5.0004835 152, 214117 © 2020 Author(s). The Journal ARTICLE of Chemical Physics scitation.org/journal/jcp Modern quantum chemistry with [Open]Molcas Cite as: J. Chem. Phys. 152, 214117 (2020); doi: 10.1063/5.0004835 Submitted: 17 February 2020 • Accepted: 11 May 2020 • Published Online: 5 June 2020 Francesco Aquilante,1,a) Jochen Autschbach,2,b) Alberto Baiardi,3,c) Stefano Battaglia,4,d) Veniamin A. Borin,5,e) Liviu F. Chibotaru,6,f) Irene Conti,7,g) Luca De Vico,8,h) Mickaël Delcey,9,i) Ignacio Fdez. Galván,4,j) Nicolas Ferré,10,k) Leon Freitag,3,l) Marco Garavelli,7,m) Xuejun Gong,11,n) Stefan Knecht,3,o) Ernst D. Larsson,12,p) Roland Lindh,4,q) Marcus Lundberg,9,r) Per Åke Malmqvist,12,s) Artur Nenov,7,t) Jesper Norell,13,u) Michael Odelius,13,v) Massimo Olivucci,8,14,w) Thomas B. -
Charge-Transfer Biexciton Annihilation in a Donor-Acceptor
Electronic Supplementary Material (ESI) for Chemical Science. This journal is © The Royal Society of Chemistry 2020 Supporting Information for Charge-Transfer Biexciton Annihilation in a Donor-Acceptor Co-crystal yields High-Energy Long-Lived Charge Carriers Itai Schlesinger, Natalia E. Powers-Riggs, Jenna L. Logsdon, Yue Qi, Stephen A. Miller, Roel Tempelaar, Ryan M. Young, and Michael R. Wasielewski* Department of Chemistry and Institute for Sustainability and Energy at Northwestern, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208-3113 Contents 1. Single crystal X-ray structure data. ..................................................................................................2 2. Crystal structure determination and refinement.............................................................................3 3. Additional Steady-state absorption Spectra.....................................................................................4 4. Pump and probe spot sizes.................................................................................................................5 5. Excitation density and fraction of molecules excited calculations ..................................................6 6. Calculation of the fraction of CT excitons adjacent to one another ...............................................7 7. Calculation of reorganization energies and charge transfer rates..................................................9 8. Model Hamiltonian for calculating polarization-dependent steady-state absorption -
Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program
Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program Start: Sunday, May 7, 2017 afternoon. Resort check-in at 4:00 pm. Finish: Wednesday, May 10, noon Lectures are in Scripps, posters are in Heather. Sunday 6:00-7:00: Dinner 7:30-9:00 Opening session 7:30–7:45 Anna Krylov (USC): “MolSSI and some lessons from previous workshop, goals of the workshop” 7:45-8:00 Theresa Windus (Iowa): “Mission of the Molecular Science Consortium” 8:00-9:00 Introduction of participants: 2 min presentation, can have one slide (send in advance) 9:00-10:30 Reception and posters Monday Breakfast: 7:30-9:00 9:00-11:45 Session I: Overview of tensors projects and current developments (moderator Daniel Smith) 9:00-9:10 Daniel Smith (MolSSI): Overview of tensor projects 9:10-9:30 Evgeny Epifanovsky (Q-Chem): Overview of Libtensor 9:30-9:50 Ed Solomonik: "An Overview of Cyclops Tensor Framework" 9:50-10:10 Ed Valeev (VT): "TiledArray: A composable massively parallel block-sparse tensor framework" 10:10-10:30 Coffee break 10:30-10:50 Devin Matthews (UT Austin): "Aquarius and TBLIS: Orthogonal Axes in Multilinear Algebra" 10:50-11:10 Karol Kowalskii (PNNL, NWChem): "NWChem, NWChemEX , and new tensor algebra systems for many-body methods" 11:10-11:30 Peng Chong (VT): "Many-body toolkit in re-designed Massively Parallel Quantum Chemistry package" 11:30-11:55 Moderated discussion: "What problems are we *still* solving?” Lunch: 12:00-1:00 Free time for unstructured discussions 5:00 Posters (coffee/tea) Dinner: 6-7:00 7:15-9:00 Session II: Computer -
FORCE FIELDS and CRYSTAL STRUCTURE PREDICTION Contents
FORCE FIELDS AND CRYSTAL STRUCTURE PREDICTION Bouke P. van Eijck ([email protected]) Utrecht University (Retired) Department of Crystal and Structural Chemistry Padualaan 8, 3584 CH Utrecht, The Netherlands Originally written in 2003 Update blind tests 2017 Contents 1 Introduction 2 2 Lattice Energy 2 2.1 Polarcrystals .............................. 4 2.2 ConvergenceAcceleration . 5 2.3 EnergyMinimization .......................... 6 3 Temperature effects 8 3.1 LatticeVibrations............................ 8 4 Prediction of Crystal Structures 9 4.1 Stage1:generationofpossiblestructures . .... 9 4.2 Stage2:selectionoftherightstructure(s) . ..... 11 4.3 Blindtests................................ 14 4.4 Beyondempiricalforcefields. 15 4.5 Conclusions............................... 17 4.6 Update2017............................... 17 1 1 Introduction Everybody who looks at a crystal structure marvels how Nature finds a way to pack complex molecules into space-filling patterns. The question arises: can we understand such packings without doing experiments? This is a great challenge to theoretical chemistry. Most work in this direction uses the concept of a force field. This is just the po- tential energy of a collection of atoms as a function of their coordinates. In principle, this energy can be calculated by quantumchemical methods for a free molecule; even for an entire crystal computations are beginning to be feasible. But for nearly all work a parameterized functional form for the energy is necessary. An ab initio force field is derived from the abovementioned calculations on small model systems, which can hopefully be generalized to other related substances. This is a relatively new devel- opment, and most force fields are empirical: they have been developed to reproduce observed properties as well as possible. There exists a number of more or less time- honored force fields: MM3, CHARMM, AMBER, GROMOS, OPLS, DREIDING.. -
Pyscf: the Python-Based Simulations of Chemistry Framework
PySCF: The Python-based Simulations of Chemistry Framework Qiming Sun∗1, Timothy C. Berkelbach2, Nick S. Blunt3,4, George H. Booth5, Sheng Guo1,6, Zhendong Li1, Junzi Liu7, James D. McClain1,6, Elvira R. Sayfutyarova1,6, Sandeep Sharma8, Sebastian Wouters9, and Garnet Kin-Lic Chany1 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena CA 91125, USA 2Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA 3Chemical Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA 4Department of Chemistry, University of California, Berkeley, California 94720, USA 5Department of Physics, King's College London, Strand, London WC2R 2LS, United Kingdom 6Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA 7Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, P. R. China 8Department of Chemistry and Biochemistry, University of Colorado Boulder, Boulder, CO 80302, USA 9Brantsandpatents, Pauline van Pottelsberghelaan 24, 9051 Sint-Denijs-Westrem, Belgium arXiv:1701.08223v2 [physics.chem-ph] 2 Mar 2017 Abstract PySCF is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible ∗[email protected] [email protected] 1 computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines. -
Generating Gaussian Basis Sets for CRYSTAL and Qwalk Lucas K
Generating Gaussian basis sets for CRYSTAL and QWalk Lucas K. Wagner The point of a basis set is to describe a (generally unknown) function efficiently. That is, we are going to approximate some general function f(x) by a sum over known basis functions (in this case χ(x)): X f(x) = ciχi(x): (1) i We will usually choose χi(x) such that they are convenient to work with. Perhaps integrals are easy to do with them, or perhaps they very closely approximate the function f(x), so that we don’t need too many elements in the sum of Eqn1. One basis set expansion that you may be familiar with is the Fourier expansion, which uses plane waves as the χi’s. In many-body quantum systems, we typically start our description of the many-body wave function Ψ(r1; r2;:::) with a Slater determinant. This is written as follows: 0 1 φ1(r1) φ1(r2) φ1(r3) ::: B φ2(r1) φ2(r2) φ2(r3) ::: C ΨS(r1; r2;:::) = Det B C (2) @ φ3(r1) φ3(r2) φ3(r3) ::: A :::::::::::: where ri is the position of the ith electron and φi(r) is called a molecular or crystalline orbital (MO/CO). The Slater determinant is the simplest possible many-electron wave function that satisfies fermion antisymmetry [Ψ(r1; r2;:::) = Ψ(r2; r1;:::)]. There also − exist algorithms to evaluate properties of the Slater determinant efficiently. Note that these one-particle functions φi have not yet been specified, and we will have to come up with a way to represent them within the computer.