Using redundant internal coordinates to optimize equilibrium geometries and transition states
TL;DR: In this paper, a redundant internal coordinate system for molecular geometries is constructed from all bonds, all valence angles between bonded atoms, and all dihedral angles between pairs of atoms.
Abstract: A redundant internal coordinate system for optimizing molecular geometries is constructed from all bonds, all valence angles between bonded atoms, and all dihedral angles between bonded atoms. Redundancies are removed by using the generalized inverse of the G matrix; constraints can be added by using an appropriate projector. For minimizations, redundant internal coordinates provide substantial improvements in optimization efficiency over Cartesian and nonredundant internal coordinates, especially for flexible and polycyclic systems. Transition structure searches are also improved when redundant coordinates are used and when the initial steps are guided by the quadratic synchronous transit approach. © 1996 by John Wiley & Sons, Inc.
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TL;DR: MOLCAS as discussed by the authors is a package for calculations of electronic and structural properties of molecular systems in gas, liquid, or solid phase, which contains a number of modern quantum chemical methods for studies of the electronic structure in ground and excited electronic states.
1,678 citations
TL;DR: In this contribution to the special software-centered issue, the ORCA program package is described, which is a widely used program in various areas of chemistry and spectroscopy with a current user base of over 22 000 registered users in academic research and in industry.
Abstract: In this contribution to the special software-centered issue, the ORCA program package is described. We start with a short historical perspective of how the project began and go on to discuss its current feature set. ORCA has grown into a rather comprehensive general-purpose package for theoretical research in all areas of chemistry and many neighboring disciplines such as materials sciences and biochemistry. ORCA features density functional theory, a range of wavefunction based correlation methods, semi-empirical methods, and even force-field methods. A range of solvation and embedding models is featured as well as a complete intrinsic to ORCA quantum mechanics/molecular mechanics engine. A specialty of ORCA always has been a focus on transition metals and spectroscopy as well as a focus on applicability of the implemented methods to "real-life" chemical applications involving systems with a few hundred atoms. In addition to being efficient, user friendly, and, to the largest extent possible, platform independent, ORCA features a number of methods that are either unique to ORCA or have been first implemented in the course of the ORCA development. Next to a range of spectroscopic and magnetic properties, the linear- or low-order single- and multi-reference local correlation methods based on pair natural orbitals (domain based local pair natural orbital methods) should be mentioned here. Consequently, ORCA is a widely used program in various areas of chemistry and spectroscopy with a current user base of over 22 000 registered users in academic research and in industry.
1,308 citations
TL;DR: Crystal14 as discussed by the authors is an ab initio code that uses a Gaussian-type basis set: both pseudopotential and all-electron strategies are permitted; the latter is not much more expensive than the former up to the first second transition metal rows of the periodic table.
Abstract: The capabilities of the Crystal14 program are presented, and the improvements made with respect to the previous Crystal09 version discussed. Crystal14 is an ab initio code that uses a Gaussian-type basis set: both pseudopotential and all-electron strategies are permitted; the latter is not much more expensive than the former up to the first-second transition metal rows of the periodic table. A variety of density functionals is available, including as an extreme case Hartree–Fock; hybrids of various nature (global, range-separated, double) can be used. In particular, a very efficient implementation of global hybrids, such as popular B3LYP and PBE0 prescriptions, allows for such calculations to be performed at relatively low computational cost. The program can treat on the same grounds zero-dimensional (molecules), one-dimensional (polymers), two-dimensional (slabs), as well as three-dimensional (3D; crystals) systems. No spurious 3D periodicity is required for low-dimensional systems as happens when plane-waves are used as a basis set. Symmetry is fully exploited at all steps of the calculation; this permits, for example, to investigate nanotubes of increasing radius at a nearly constant cost (better than linear scaling!) or to perform self-consistent-field (SCF) calculations on fullerenes as large as (10,10), with 6000 atoms, 84,000 atomic orbitals, and 20 SCF cycles, on a single core in one day. Three versions of the code exist, serial, parallel, and massive-parallel. In the second one, the most relevant matrices are duplicated, whereas in the third one the matrices in reciprocal space are distributed for diagonalization. All the relevant vectors are now dynamically allocated and deallocated after use, making Crystal14 much more agile than the previous version, in which they were statically allocated. The program now fits more easily in low-memory machines (as many supercomputers nowadays are). Crystal14 can be used on parallel machines up to a high number of cores (benchmarks up to 10,240 cores are documented) with good scalability, the main limitation remaining the diagonalization step. Many tensorial properties can be evaluated in a fully automated way by using a single input keyword: elastic, piezoelectric, photoelastic, dielectric, as well as first and second hyperpolarizabilies, electric field gradients, Born tensors and so forth. Many tools permit a complete analysis of the vibrational properties of crystalline compounds. The infrared and Raman intensities are now computed analytically and related spectra can be generated. Isotopic shifts are easily evaluated, frequencies of only a fragment of a large system computed and nuclear contribution to the dielectric tensor determined. New algorithms have been devised for the investigation of solid solutions and disordered systems. The topological analysis of the electron charge density, according to the Quantum Theory of Atoms in Molecules, is now incorporated in the code via the integrated merge of the Topond package. Electron correlation can be evaluated at the Moller–Plesset second-order level (namely MP2) and a set of double-hybrids are presently available via the integrated merge with the Cryscor program. © 2014 Wiley Periodicals, Inc.
1,172 citations
TL;DR: The electronic Ligand Builder and Optimization Workbench is a program module of the PHENIX suite of computational crystallographic software designed to be a flexible procedure that uses simple and fast quantum-chemical techniques to provide chemically accurate information for novel and known ligands alike.
Abstract: The electronic Ligand Builder and Optimization Workbench (eLBOW) is a program module of the PHENIX suite of computational crystallographic software. It is designed to be a flexible procedure that uses simple and fast quantum-chemical techniques to provide chemically accurate information for novel and known ligands alike. A variety of input formats and options allow the attainment of a number of diverse goals including geometry optimization and generation of restraints.
964 citations
Cites methods from "Using redundant internal coordinate..."
...…that uses a quadratic approximation to the potential energy hyper-surface, using a redundant internal coordinate set (Pulay & Fogarasi, 1992; Peng et al., 1996; Fogarasi et al., 1992; Pulay et al., 1979) and a modified DIIS method (Farkas & Schlegel, 2002; Pulay, 1980, 1982; Császár &…...
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TL;DR: In this paper, a detailed account of density functional theory and its application to the calculation of molecular properties of inorganic compounds is provided, including geometric, electric, magnetic and time-dependent perturbations.
871 citations
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3,606 citations
TL;DR: In this paper, a modified conjugate gradient algorithm for geometry optimization is presented for use with ab initio MO methods, where the second derivative matrix rather than its inverse is updated employing the gradients.
Abstract: A modified conjugate gradient algorithm for geometry optimization is outlined for use with ab initioMO methods. Since the computation time for analytical energy gradients is approximately the same as for the energy, the optimization algorithm evaluates and utilizes the gradients each time the energy is computed. The second derivative matrix, rather than its inverse, is updated employing the gradients. At each step, a one-dimensional minimization using a quartic polynomial is carried out, followed by an n-dimensional search using the second derivative matrix. By suitably controlling the number of negative eigenvalues of the second derivative matrix, the algorithm can also be used to locate transition structures. Representative timing data for optimizations of equilibrium geometries and transition structures are reported for ab initioSCF–MO calculations.
3,373 citations
TL;DR: In this paper, a class of approximating matrices as a function of a scalar parameter is presented, where the problem of optimal conditioning of these matrices under an appropriate norm is investigated and a set of computational results verifies the superiority of the new methods arising from conditioning considerations to known methods.
Abstract: Quasi-Newton methods accelerate the steepest-descent technique for function minimization by using computational history to generate a sequence of approximations to the inverse of the Hessian matrix. This paper presents a class of approximating matrices as a function of a scalar parameter. The problem of optimal conditioning of these matrices under an appropriate norm as a function of the scalar parameter is investigated. A set of computational results verifies the superiority of the new methods arising from conditioning considerations to known methods.
3,359 citations
TL;DR: In this paper, a rank-two variable-metric method was derived using Greenstadt's variational approach, which preserves the positive-definiteness of the approximating matrix.
Abstract: A new rank-two variable-metric method is derived using Greenstadt's variational approach [Math. Comp., this issue]. Like the Davidon-Fletcher-Powell (DFP) variable-metric method, the new method preserves the positive-definiteness of the approximating matrix. Together with Greenstadt's method, the new method gives rise to a one-parameter family of variable-metric methods that includes the DFP and rank-one methods as special cases. It is equivalent to Broyden's one-parameter family [Math. Comp., v. 21, 1967, pp. 368-381]. Choices for the inverse of the weighting matrix in the variational approach are given that lead to the derivation of the DFP and rank-one methods directly. In the preceding paper [6], Greenstadt derives two variable-metric methods, using a classical variational approach. Specifically, two iterative formulas are developed for updating the matrix Hk, (i.e., the inverse of the variable metric), where Hk is an approximation to the inverse Hessian G-'(Xk) of the function being minimized.* Using the iteration formula Hk+1 = Hk + Ek to provide revised estimates to the inverse Hessian at each step, Greenstadt solves for the correction term Ek that minimizes the norm N(Ek) = Tr (WEkWEkJ) subject to the conditions
2,788 citations
TL;DR: In this article, a more detailed analysis of a class of minimization algorithms, which includes as a special case the DFP (Davidon-Fenton-Powell) method, has been presented.
Abstract: This paper presents a more detailed analysis of a class of minimization algorithms, which includes as a special case the DFP (Davidon-Fletcher-Powell) method, than has previously appeared. Only quadratic functions are considered but particular attention is paid to the magnitude of successive errors and their dependence upon the initial matrix. On the basis of this a possible explanation of some of the observed characteristics of the class is tentatively suggested. PROBABLY the best-known algorithm for determining the unconstrained minimum of a function of many variables, where explicit expressions are available for the first partial derivatives, is that of Davidon (1959) as modified by Fletcher & Powell (1963). This algorithm has many virtues. It is simple and does not require at any stage the solution of linear equations. It minimizes a quadratic function exactly in a finite number of steps and this property makes convergence of this algorithm rapid, when applied to more general functions, in the neighbourhood of the solution. It is, at least in theory, stable since the iteration matrix H,, which transforms the jth gradient into the /th step direction, may be shown to be positive definite. In practice the algorithm has been generally successful, but it has exhibited some puzzling behaviour. Broyden (1967) noted that H, does not always remain positive definite, and attributed this to rounding errors. Pearson (1968) found that for some problems the solution was obtained more efficiently if H, was reset to a positive definite matrix, often the unit matrix, at intervals during the computation. Bard (1968) noted that H, could become singular, attributed this to rounding error and suggested the use of suitably chosen scaling factors as a remedy. In this paper we analyse the more general algorithm given by Broyden (1967), of which the DFP algorithm is a special case, and determine how for quadratic functions the choice of an arbitrary parameter affects convergence. We investigate how the successive errors depend, again for quadratic functions, upon the initial choice of iteration matrix paying particular attention to the cases where this is either the unit matrix or a good approximation to the inverse Hessian. We finally give a tentative explanation of some of the observed experimental behaviour in the case where the function to be minimized is not quadratic.
2,306 citations