An Introduction to Hartree-Fock Molecular Orbital Theory
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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. -
Basis Sets Running a Calculation • in Performing a Computational
Session 2: Basis Sets • Two of the major methods (ab initio and DFT) require some understanding of basis sets and basis functions • This session describes the essentials of basis sets: – What they are – How they are constructed – How they are used – Significance in choice 1 Running a Calculation • In performing a computational chemistry calculation, the chemist has to make several decisions of input to the code: – The molecular geometry (and spin state) – The basis set used to determine the wavefunction – The properties to be calculated – The type(s) of calculations and any accompanying assumptions 2 Running a calculation •For ab initio or DFT calculations, many programs require a basis set choice to be made – The basis set is an approx- imate representation of the atomic orbitals (AOs) – The program then calculates molecular orbitals (MOs) using the Linear Combin- ation of Atomic Orbitals (LCAO) approximation 3 Computational Chemistry Map Chemist Decides: Computer calculates: Starting Molecular AOs determine the Geometry AOs O wavefunction (ψ) Basis Set (with H H ab initio and DFT) Type of Calculation LCAO (Method and Assumptions) O Properties to HH be Calculated MOs 4 Critical Choices • Choice of the method (and basis set) used is critical • Which method? • Molecular Mechanics, Ab initio, Semiempirical, or DFT • Which approximation? • MM2, MM3, HF, AM1, PM3, or B3LYP, etc. • Which basis set (if applicable)? • Minimal basis set • Split-valence • Polarized, Diffuse, High Angular Momentum, ...... 5 Why is Basis Set Choice Critical? • The -
User Manual for the Uppsala Quantum Chemistry Package UQUANTCHEM V.35
User manual for the Uppsala Quantum Chemistry package UQUANTCHEM V.35 by Petros Souvatzis Uppsala 2016 Contents 1 Introduction 6 2 Compiling the code 7 3 What Can be done with UQUANTCHEM 9 3.1 Hartree Fock Calculations . 9 3.2 Configurational Interaction Calculations . 9 3.3 M¨ollerPlesset Calculations (MP2) . 9 3.4 Density Functional Theory Calculations (DFT)) . 9 3.5 Time Dependent Density Functional Theory Calculations (TDDFT)) . 10 3.6 Quantum Montecarlo Calculations . 10 3.7 Born Oppenheimer Molecular Dynamics . 10 4 Setting up a UQANTCHEM calculation 12 4.1 The input files . 12 4.1.1 The INPUTFILE-file . 12 4.1.2 The BASISFILE-file . 13 4.1.3 The BASISFILEAUX-file . 14 4.1.4 The DENSMATSTARTGUESS.dat-file . 14 4.1.5 The MOLDYNRESTART.dat-file . 14 4.1.6 The INITVELO.dat-file . 15 4.1.7 Running Uquantchem . 15 4.2 Input parameters . 15 4.2.1 CORRLEVEL ................................. 15 4.2.2 ADEF ..................................... 15 4.2.3 DOTDFT ................................... 16 4.2.4 NSCCORR ................................... 16 4.2.5 SCERR .................................... 16 4.2.6 MIXTDDFT .................................. 16 4.2.7 EPROFILE .................................. 16 4.2.8 DOABSSPECTRUM ............................... 17 4.2.9 NEPERIOD .................................. 17 4.2.10 EFIELDMAX ................................. 17 4.2.11 EDIR ..................................... 17 4.2.12 FIELDDIR .................................. 18 4.2.13 OMEGA .................................... 18 2 CONTENTS 3 4.2.14 NCHEBGAUSS ................................. 18 4.2.15 RIAPPROX .................................. 18 4.2.16 LIMPRECALC (Only openmp-version) . 19 4.2.17 DIAGDG ................................... 19 4.2.18 NLEBEDEV .................................. 19 4.2.19 MOLDYN ................................... 19 4.2.20 DAMPING ................................... 19 4.2.21 XLBOMD .................................. -
Theory and Technique
Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Title COMPUTATIONAL METHODS FOR MOLEUCLAR STRUCTURE DETERMINATION: THEORY AND TECHNIQUE Permalink https://escholarship.org/uc/item/3b7795px Author Lester, W.A. Publication Date 1980-03-14 Peer reviewed eScholarship.org Powered by the California Digital Library University of California CONTENTS Foreword v List of Invited Speakers vii Workshop Participants viii LECTURES 1 Introduction to Computational Quantum Chemistry Ernest R. Davidson 1-1 2/3 Introduction to SCF Theory Ernest R. Davidson 2/3-1 4 Semi-Empirical SCF Theory Michael C. Zerner 4-1 5 An Introduction to Some Semi-Empirical and Approximate Molecular Orbital Methods Miehael C. Zerner 5-1 6/7 Ab Initio Hartree Fock John A. Pople 6/7-1 8 SCF Properties Ernest R. Davidson 8-1 9/10 Generalized Valence Bond William A, Goddard, III 9/10-1 11 Open Shell KF and MCSCF Theory Ernest R. Davidson 11-1 12 Some Semi-Empirical Approaches to Electron Correlation Miahael C. Zerner 12-1 13 Configuration Interaction Method Ernest R. Davidson 13-1 14 Geometry Optimization of Large Systems Michael C. Zerner 14-1 15 MCSCF Calculations: Results Boaen Liu 15-1 lfi/18 Empirical Potentials, Semi-Empirical Potentials, and Molecular Mechanics Norman L. Allinger 16/18-1 iv 17 CI Calculations: Results Bowen Liu 17-1 19 Computational Quantum Chemistry: Future Outlook Ernest R. Davidson 19-1 V FOREWORD The National Resource for Computation in Chemistry (NRCC) was established as a Division of Lawrence Berkeley Laboratory (LBL) in October 1977. The functions of the NRCC may be broadly categorized as follows: (1) to make information on existing and developing computa tional methodologies available to all segments of the chemistry community, (2) to make state-of-the-art computational facilities (both hardware and software] accessible to the chemistry community, and (3) to foster research and development of new computational methods for application to chemical problems. -
Diagonalization, Eigenvalues Problem, Secular Equation
Diagonalization, eigenvalues problem, secular equation Diagonalization procedure of a matrix A with dimensionality n × n (e.g. the Hessian matrix) 2 3 a11 a12 : : : a1n 6 7 6 a21 a22 : : : a2n 7 6 7 A = 6 . 7 6 . 7 4 5 an1 an2 : : : ann consists in finding a matrix C such, that the matrix D=C−1AC is diagonal: 2 3 d1 0 ::: 0 6 7 6 0 d2 ::: 0 7 −1 6 7 C AC = D = 6 . 7 6 . 7 4 5 0 0 : : : dn Equation C−1AC=D can also be written as AC = CD Denoting the elements of matrix C by cij and using te fact that D is diagonal (i.e., its elements dij are of the form djδij, where δij denotes the Kronecker delta, δii=1 i δij=0 for i6=j) we obtain X X X (AC)ij = aik ckj (CD)ij = cik dkj = cik dj δkj = djcij k k k Diagonalization, eigenvalues problem, secular equation Employing the equation (AC)ij = (CD)ij we obtain X aik ckj = djcij k In matrix notation this equation takes the form ACj = dj Cj where Cj is the jth column of matrix C. This is equation for the eigenvalues (dj) and eigenvectors (Cj) of matrix A. Solving this equation, that is the solving the so called eigenproblem for matrix A, is equivalent to diagonalization of matrix A. This is because the matrix C is built from the (column) eigenvectors C1;C2;:::;Cn: C = [C1;C2;:::;Cn] The equation for eigenvectors can also be written as( A − dj E) Cj = 0, where E is the unit matrix with elements δij. -
Introduction to DFT and the Plane-Wave Pseudopotential Method
Introduction to DFT and the plane-wave pseudopotential method Keith Refson STFC Rutherford Appleton Laboratory Chilton, Didcot, OXON OX11 0QX 23 Apr 2014 Parallel Materials Modelling Packages @ EPCC 1 / 55 Introduction Synopsis Motivation Some ab initio codes Quantum-mechanical approaches Density Functional Theory Electronic Structure of Condensed Phases Total-energy calculations Introduction Basis sets Plane-waves and Pseudopotentials How to solve the equations Parallel Materials Modelling Packages @ EPCC 2 / 55 Synopsis Introduction A guided tour inside the “black box” of ab-initio simulation. Synopsis • Motivation • The rise of quantum-mechanical simulations. Some ab initio codes Wavefunction-based theory • Density-functional theory (DFT) Quantum-mechanical • approaches Quantum theory in periodic boundaries • Plane-wave and other basis sets Density Functional • Theory SCF solvers • Molecular Dynamics Electronic Structure of Condensed Phases Recommended Reading and Further Study Total-energy calculations • Basis sets Jorge Kohanoff Electronic Structure Calculations for Solids and Molecules, Plane-waves and Theory and Computational Methods, Cambridge, ISBN-13: 9780521815918 Pseudopotentials • Dominik Marx, J¨urg Hutter Ab Initio Molecular Dynamics: Basic Theory and How to solve the Advanced Methods Cambridge University Press, ISBN: 0521898633 equations • Richard M. Martin Electronic Structure: Basic Theory and Practical Methods: Basic Theory and Practical Density Functional Approaches Vol 1 Cambridge University Press, ISBN: 0521782856 -
A Comparison of Pariser-Parr-Pople Calculations on Furan with Nddo(+
University of New Hampshire University of New Hampshire Scholars' Repository Doctoral Dissertations Student Scholarship Fall 1975 A COMPARISON OF PARISER-PARR-POPLE CALCULATIONS ON FURAN WITH NDDO(+ NEGLECT OF DIATOMIC DIFFERENTIAL OVERLAP) CALCULATIONS ON FURAN AND PYRROLE INCLUDING A COMPARISON WITH AB INITIO AND OTHER SEMIEMPIRICAL METHODS DONALD RICHARD LAND University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/dissertation Recommended Citation LAND, DONALD RICHARD, "A COMPARISON OF PARISER-PARR-POPLE CALCULATIONS ON FURAN WITH NDDO(+ NEGLECT OF DIATOMIC DIFFERENTIAL OVERLAP) CALCULATIONS ON FURAN AND PYRROLE INCLUDING A COMPARISON WITH AB INITIO AND OTHER SEMIEMPIRICAL METHODS" (1975). Doctoral Dissertations. 2349. https://scholars.unh.edu/dissertation/2349 This Dissertation is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. INFORMATION TO USERS This material was produced from a microfilm copy of the original document. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the original submitted. The following explanation of techniques is provided to help you understand markings or patterns which may appear on this reproduction. 1.The sign or "target” for pages apparently lacking from the document photographed is "Missing Page(s)”. If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. -
Hartree-Fock Approach
The Wave equation The Hamiltonian The Hamiltonian Atomic units The hydrogen atom The chemical connection Hartree-Fock theory The Born-Oppenheimer approximation The independent electron approximation The Hartree wavefunction The Pauli principle The Hartree-Fock wavefunction The L#AO approximation An example The HF theory The HF energy The variational principle The self-consistent $eld method Electron spin &estricted and unrestricted HF theory &HF versus UHF Pros and cons !er ormance( HF equilibrium bond lengths Hartree-Fock calculations systematically underestimate equilibrium bond lengths !er ormance( HF atomization energy Hartree-Fock calculations systematically underestimate atomization energies. !er ormance( HF reaction enthalpies Hartree-Fock method fails when reaction is far from isodesmic. Lack of electron correlations!! Electron correlation In the Hartree-Fock model, the repulsion energy between two electrons is calculated between an electron and the a!erage electron density for the other electron. What is unphysical about this is that it doesn't take into account the fact that the electron will push away the other electrons as it mo!es around. This tendency for the electrons to stay apart diminishes the repulsion energy. If one is on one side of the molecule, the other electron is likely to be on the other side. Their positions are correlated, an effect not included in a Hartree-Fock calculation. While the absolute energies calculated by the Hartree-Fock method are too high, relative energies may still be useful. Basis sets Minimal basis sets Minimal basis sets Split valence basis sets Example( Car)on 6-3/G basis set !olarized basis sets 1iffuse functions Mix and match %2ective core potentials #ounting basis functions Accuracy Basis set superposition error Calculations of interaction energies are susceptible to basis set superposition error (BSSE) if they use finite basis sets. -
Arxiv:1912.01335V4 [Physics.Atom-Ph] 14 Feb 2020
Fast apparent oscillations of fundamental constants Dionysios Antypas Helmholtz Institute Mainz, Johannes Gutenberg University, 55128 Mainz, Germany Dmitry Budker Helmholtz Institute Mainz, Johannes Gutenberg University, 55099 Mainz, Germany and Department of Physics, University of California at Berkeley, Berkeley, California 94720-7300, USA Victor V. Flambaum School of Physics, University of New South Wales, Sydney 2052, Australia and Helmholtz Institute Mainz, Johannes Gutenberg University, 55099 Mainz, Germany Mikhail G. Kozlov Petersburg Nuclear Physics Institute of NRC “Kurchatov Institute”, Gatchina 188300, Russia and St. Petersburg Electrotechnical University “LETI”, Prof. Popov Str. 5, 197376 St. Petersburg Gilad Perez Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel 7610001 Jun Ye JILA, National Institute of Standards and Technology, and Department of Physics, University of Colorado, Boulder, Colorado 80309, USA (Dated: May 2019) Precision spectroscopy of atoms and molecules allows one to search for and to put stringent limits on the variation of fundamental constants. These experiments are typically interpreted in terms of variations of the fine structure constant α and the electron to proton mass ratio µ = me/mp. Atomic spectroscopy is usually less sensitive to other fundamental constants, unless the hyperfine structure of atomic levels is studied. However, the number of possible dimensionless constants increases when we allow for fast variations of the constants, where “fast” is determined by the time scale of the response of the studied species or experimental apparatus used. In this case, the relevant dimensionless quantity is, for example, the ratio me/hmei and hmei is the time average. In this sense, one may say that the experimental signal depends on the variation of dimensionful constants (me in this example). -
Powerpoint Presentation
Session 2 Basis Sets CCCE 2008 1 Session 2: Basis Sets • Two of the major methods (ab initio and DFT) require some understanding of basis sets and basis functions • This session describes the essentials of basis sets: – What they are – How they are constructed – How they are used – Significance in choice CCCE 2008 2 Running a Calculation • In performing ab initio and DFT computa- tional chemistry calculations, the chemist has to make several decisions of input to the code: – The molecular geometry (and spin state) – The basis set used to determine the wavefunction – The properties to be calculated – The type(s) of calculations and any accompanying assumptions CCCE 2008 3 Running a calculation • For ab initio or DFT calculations, many programs require a basis set choice to be made – The basis set is an approx- imate representation of the atomic orbitals (AOs) – The program then calculates molecular orbitals (MOs) using the Linear Combin- ation of Atomic Orbitals (LCAO) approximation CCCE 2008 4 Computational Chemistry Map Chemist Decides: Computer calculates: Starting Molecular AOs determine the Geometry AOs O wavefunction (ψ) Basis Set (with H H ab initio and DFT) Type of Calculation LCAO (Method and Assumptions) O Properties to HH be Calculated MOs CCCE 2008 5 Critical Choices • Choice of the method (and basis set) used is critical • Which method? • Molecular Mechanics, Ab initio, Semiempirical, or DFT • Which approximation? • MM2, MM3, HF, AM1, PM3, or B3LYP, etc. • Which basis set (if applicable)? • Minimal basis set • Split-valence -
The Hartree-Fock Method
An Iterative Technique for Solving the N-electron Hamiltonian: The Hartree-Fock method Tony Hyun Kim Abstract The problem of electron motion in an arbitrary field of nuclei is an important quantum mechanical problem finding applications in many diverse fields. From the variational principle we derive a procedure, called the Hartree-Fock (HF) approximation, to obtain the many-particle wavefunction describing such a sys- tem. Here, the central physical concept is that of electron indistinguishability: while the antisymmetry requirement greatly complexifies our task, it also of- fers a symmetry that we can exploit. After obtaining the HF equations, we then formulate the procedure in a way suited for practical implementation on a computer by introducing a set of spatial basis functions. An example imple- mentation is provided, allowing for calculations on the simplest heteronuclear structure: the helium hydride ion. We conclude with a discussion of how to derive useful chemical information from the HF solution. 1 Introduction In this paper I will introduce the theory and the techniques to solve for the approxi- mate ground state of the electronic Hamiltonian: N N M N N 1 X 2 X X ZA X X 1 H = − ∇i − + (1) 2 rAi rij i=1 i=1 A=1 i=1 j>i which describes the motion of N electrons (indexed by i and j) in the field of M nuclei (indexed by A). The coordinate system, as well as the fully-expanded Hamiltonian, is explicitly illustrated for N = M = 2 in Figure 1. Although we perform the analysis 2 Kim Figure 1: The coordinate system corresponding to Eq. -
Towards Efficient Data Exchange and Sharing for Big-Data Driven Materials Science: Metadata and Data Formats
www.nature.com/npjcompumats PERSPECTIVE OPEN Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats Luca M. Ghiringhelli1, Christian Carbogno1, Sergey Levchenko1, Fawzi Mohamed1, Georg Huhs2,3, Martin Lüders4, Micael Oliveira5,6 and Matthias Scheffler1,7 With big-data driven materials research, the new paradigm of materials science, sharing and wide accessibility of data are becoming crucial aspects. Obviously, a prerequisite for data exchange and big-data analytics is standardization, which means using consistent and unique conventions for, e.g., units, zero base lines, and file formats. There are two main strategies to achieve this goal. One accepts the heterogeneous nature of the community, which comprises scientists from physics, chemistry, bio-physics, and materials science, by complying with the diverse ecosystem of computer codes and thus develops “converters” for the input and output files of all important codes. These converters then translate the data of each code into a standardized, code- independent format. The other strategy is to provide standardized open libraries that code developers can adopt for shaping their inputs, outputs, and restart files, directly into the same code-independent format. In this perspective paper, we present both strategies and argue that they can and should be regarded as complementary, if not even synergetic. The represented appropriate format and conventions were agreed upon by two teams, the Electronic Structure Library (ESL) of the European Center for Atomic and Molecular Computations (CECAM) and the NOvel MAterials Discovery (NOMAD) Laboratory, a European Centre of Excellence (CoE). A key element of this work is the definition of hierarchical metadata describing state-of-the-art electronic-structure calculations.