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This work reports on a spin‐pure configuration‐based implementation of the heatbath configuration interaction (HCI) algorithm for selective configuration interaction. Besides the obvious advantage of being spin‐pure, the presented method combines the compactness of the configurational ansatz with the known efficiency of the HCI algorithm and a variety of algorithmic and conceptual ideas to achieve a high level of performance. In particular, through pruning of the selected configurational space after HCI selection by means of a more strict criterion, a more compact wavefunction representation is obtained. Moreover, the underlying logic of the method allows us to minimize the number of redundant matrix‐matrix multiplications while making use of just‐in‐time compilation to achieve fast diagonalization of the Hamiltonian. The critical search for 2‐electron connections within the configurational space is facilitated by a tree‐based representation thereof as suggested previously by Gopal et al. Usage of a prefix‐based parallelization and batching during the calculation of the PT2‐correction leads to a good load balancing and significantly reduced memory requirements for these critical steps of the calculation. In this way, the need for a semistochastic approach to the PT2 correction is avoided even for large configurational spaces. Finally, several test‐cases are discussed to demonstrate the strengths and weaknesses of the presented method. [ABSTRACT FROM AUTHOR]

We present MultiPsi, an open‐source MCSCF program for the calculation of ground and excited states properties of strongly correlated systems. The program currently implements a general MCSCF code with excited states available using either state‐averaging or linear response. It is written in a highly modular fashion using Python/C++ which makes it well suited as a development platform, enabling easy prototyping of novel methods, and as a teaching tool using interactive notebooks. The code is also very efficient and designed for modern high‐performance computing environments using hybrid OpenMP/MPI parallelization. This efficiency is demonstrated with the calculation of the CASSCF energy and linear response of a molecule with more than 700 atoms as well as a fully optimized conventional CI calculation on more than 400 billion determinants. This article is categorized under:Software > Quantum ChemistryElectronic Structure Theory > Ab Initio Electronic Structure MethodsTheoretical and Physical Chemistry > Spectroscopy [ABSTRACT FROM AUTHOR]

Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn–Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. Finally, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets. Program summary: Program title: ELSI Interface CPC Library link to program files: http://dx.doi.org/10.17632/473mbbznrs.1 Licensing provisions: BSD 3-clause Programming language: Fortran 2003, with interface to C/C++ External routines/libraries: BLACS, BLAS, BSEPACK (optional), EigenExa (optional), ELPA, FortJSON, LAPACK, libOMM, MPI, MAGMA (optional), MUMPS (optional), NTPoly, ParMETIS (optional), PETSc (optional), PEXSI, PT-SCOTCH (optional), ScaLAPACK, SLEPc (optional), SuperLU_DIST Nature of problem: Solving the electronic structure from given Hamiltonian and overlap matrices in electronic structure calculations. Solution method: ELSI provides a unified software interface to facilitate the use of various electronic structure solvers including cubic scaling dense eigensolvers, linear scaling density matrix methods, and other approaches.

Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn–Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. Finally, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets. Program summary: Program title: ELSI Interface CPC Library link to program files: http://dx.doi.org/10.17632/473mbbznrs.1 Licensing provisions: BSD 3-clause Programming language: Fortran 2003, with interface to C/C++ External routines/libraries: BLACS, BLAS, BSEPACK (optional), EigenExa (optional), ELPA, FortJSON, LAPACK, libOMM, MPI, MAGMA (optional), MUMPS (optional), NTPoly, ParMETIS (optional), PETSc (optional), PEXSI, PT-SCOTCH (optional), ScaLAPACK, SLEPc (optional), SuperLU_DIST Nature of problem: Solving the electronic structure from given Hamiltonian and overlap matrices in electronic structure calculations. Solution method: ELSI provides a unified software interface to facilitate the use of various electronic structure solvers including cubic scaling dense eigensolvers, linear scaling density matrix methods, and other approaches.

The Chronus Quantum (ChronusQ) software package is an open source (under the GNU General Public License v2) software infrastructure which targets the solution of challenging problems that arise in ab initio electronic structure theory. Special emphasis is placed on the consistent treatment of time dependence and spin in the electronic wave function, as well as the inclusion of relativistic effects in said treatments. In addition, ChronusQ provides support for the inclusion of uniform finite magnetic fields as external perturbations through the use of gauge-including atomic orbitals. ChronusQ is a parallel electronic structure code written in modern C++ which utilizes both message passing implementation and shared memory (OpenMP) parallelism. In addition to the examination of the current state of code base itself, a discussion regarding ongoing developments and developer contributions will also be provided. This article is categorized under: Software > Quantum Chemistry Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Density Functional Theory.

A short scientific biography of Peter M. W. Gill, a prominent theoretical chemist, is reported as the introduction to a collection of manuscripts comprising a Special Issue in his honour. [ABSTRACT FROM AUTHOR]

A novel methodology for the evaluation of two electron integrals up to f functions using Graphics Processing Units (GPUs) is presented. The Head-Gordon-Pople recursion relationships are solved via a simple heuristic methodology to minimize the number of evaluated intermediates in the recursion trees. Automatic code generation is used to generate highly optimized CUDA kernels. A novel approach for f functions is presented in which integral classes are split into smaller subclasses to minimize register pressure and exploit additional parallelism at the cost of recomputing a small number of intermediates. Alongside optimized kernels, the ERI evaluation scheme works in conjunction with an efficient work distribution scheme which guarantees load-balancing during computation. The new HGP scheme shows excellent speedups of 2 × to above 60 × against existing GPU code. Additionally, when coupled with digestion into the Fock matrix, the scaling is excellent on up to 7 GPUs with an 85% parallel efficiency for the 6-31G(d) basis set. [ABSTRACT FROM AUTHOR]

We explore a variety of unsolved problems in density functional theory, where mathematicians might prove useful. We give the background and context of the different problems, and why progress toward resolving them would help those doing computations using density functional theory. Subjects covered include the magnitude of the kinetic energy in Hartree–Fock calculations, the shape of adiabatic connection curves, using the constrained search with input densities, densities of states, the semiclassical expansion of energies, the tightness of Lieb–Oxford bounds, and how we decide the accuracy of an approximate density. [ABSTRACT FROM AUTHOR]

This work reports on a novel computational approach to the efficient evaluation of one‐electron coupling coefficients as they are required during spin‐adapted electronic structure calculations of the configuration interaction type. The presented approach relies on the equivalence of the representation matrix of excitation operators in the basis of configuration state functions and the representation matrix of permutation operators in the basis of genealogical spin eigenfunctions. After the details of this connection are established for every class of one‐electron excitation operator, a recursive scheme to evaluate permutation operator representations originally introduced by Yamanouchi and Kotani is recapitulated. On the basis of this scheme we have developed an efficient algorithm that allows the evaluation of all nonredundant coupling coefficients for systems with 20 unpaired electrons and a total spin of S=0 within only a few hours on a simple Desktop‐PC. Furthermore, a full‐CI implementation that utilizes the presented approach to one‐electron coupling coefficients is shown to perform well in terms of computational timings for CASCI calculations with comparably large active spaces. More importantly, however, this work paves the way to spin‐adapted and configuration driven selected configuration interaction calculations with many unpaired electrons. [ABSTRACT FROM AUTHOR]

Simulations of chemical reaction probabilities in gas surface dynamics require the calculation of ensemble averages over many tens of thousands of reaction events to predict dynamical observables that can be compared to experiments. At the same time, the energy landscapes need to be accurately mapped, as small errors in barriers can lead to large deviations in reaction probabilities. This brings a particularly interesting challenge for machine learning interatomic potentials, which are becoming well-established tools to accelerate molecular dynamics simulations. We compare state-of-the-art machine learning interatomic potentials with a particular focus on their inference performance on CPUs and suitability for high throughput simulation of reactive chemistry at surfaces. The considered models include polarizable atom interaction neural networks (PaiNN), recursively embedded atom neural networks (REANN), the MACE equivariant graph neural network, and atomic cluster expansion potentials (ACE). The models are applied to a dataset on reactive molecular hydrogen scattering on low-index surface facets of copper. All models are assessed for their accuracy, time-to-solution, and ability to simulate reactive sticking probabilities as a function of the rovibrational initial state and kinetic incidence energy of the molecule. REANN and MACE models provide the best balance between accuracy and time-to-solution and can be considered the current state-of-the-art in gas-surface dynamics. PaiNN models require many features for the best accuracy, which causes significant losses in computational efficiency. ACE models provide the fastest time-to-solution, however, models trained on the existing dataset were not able to achieve sufficiently accurate predictions in all cases.

Machine learning (ML) provides access to fast and accurate quantum chemistry (QC) calculations for various properties of interest such as excitation energies. It is often the case that high accuracy in prediction using a ML model, demands a large and costly training set. Various solutions and procedures have been presented to reduce this cost. These include methods such as Δ-ML, hierarchical-ML, and multifidelity machine learning (MFML). MFML combines various Δ-ML like sub-models for various fidelities according to a fixed scheme derived from the sparse grid combination technique. In this work we implement an optimization procedure to combine multifidelity models in a flexible scheme resulting in optimized MFML (o-MFML) that provides superior prediction capabilities. This hyperparameter optimization is carried out on a holdout validation set of the property of interest. This work benchmarks the o-MFML method in predicting the atomization energies on the QM7b dataset, and again in the prediction of excitation energies for three molecules of growing size. The results indicate that o-MFML is a strong methodological improvement over MFML and provides lower error of prediction. Even in cases of poor data distributions and lack of clear hierarchies among the fidelities, which were previously identified as issues for multifidelity methods, the o-MFML is advantageous for the prediction of quantum chemical properties.

Abstract The recently introduced coupled cluster (CC) downfolding techniques for reducing the dimensionality of quantum many-body problems recast the CC formalism in the form of the renormalization procedure allowing, for the construction of effective (or downfolded) Hamiltonians in small-dimensionality sub-space, usually identified with the so-called active space, of the entire Hilbert space. The resulting downfolded Hamiltonians integrate out the external (out-of-active-space) Fermionic degrees of freedom from the internal (in-the-active-space) parameters of the wave function, which can be determined as components of the eigenvectors of the downfolded Hamiltonians in the active space. This paper will discuss the extension of non-Hermitian (associated with standard CC formulations) and Hermitian (associated with the unitary CC approaches) downfolding formulations to composite quantum systems commonly encountered in materials science and chemistry. The non-Hermitian formulation can provide a platform for developing local CC approaches, while the Hermitian one can serve as an ideal foundation for developing various quantum computing applications based on the limited quantum resources. We also discuss the algorithm for extracting the semi-analytical form of the inter-electron interactions in the active spaces.

We describe an efficient parallel implementation of the selected inversion algorithm for distributed memory computer systems, which we call PSelInv. The PSelInv method computes selected elements of a general sparse matrix Athat can be decomposed as A= LU, where L is lower triangular and U is upper triangular. The implementation described in this article focuses on the case of sparse symmetric matrices. It contains an interface that is compatible with the distributed memory parallel sparse direct factorization SuperLU-DIST. However, the underlying data structure and design of PSelInv allows it to be easily combined with other factorization routines, such as PARDISO. We discuss general parallelization strategies such as data and task distribution schemes. In particular, we describe how to exploit the concurrency exposed by the elimination tree associated with the LU factorization of A. We demonstrate the efficiency and accuracy of PSelInv by presenting several numerical experiments. In particular, we show that PSelInv can run efficiently on more than 4,000 cores for a modestly sized matrix. We also demonstrate how PSelInv can be used to accelerate large-scale electronic structure calculations.

BackgroundThe testing of theoretical models with experimental data is an integral part of the scientific method, and a logical place to search for new ways of stimulating scientific productivity. Often experiment/theory comparisons may be viewed as a workflow comprised of well-defined, rote operations distributed over several distinct computers, as exemplified by the way in which predictions from electronic structure theories are evaluated with results from spectroscopic experiments. For workflows such as this, which may be laborious and time consuming to perform manually, software that could orchestrate the operations and transfer results between computers in a seamless and automated fashion would offer major efficiency gains. Such tools also promise to alter how researchers interact with data outside their field of specialization by, e.g., making raw experimental results more accessible to theorists, and the outputs of theoretical calculations more readily comprehended by experimentalists.ResultsAn implementation of an automated workflow has been developed for the integrated analysis of data from nuclear magnetic resonance (NMR) experiments and electronic structure calculations. Kepler (Altintas et al. 2004) open source software was used to coordinate the processing and transfer of data at each step of the workflow. This workflow incorporated several open source software components, including electronic structure code to compute NMR parameters, a program to simulate NMR signals, NMR data processing programs, and others. The Kepler software was found to be sufficiently flexible to address several minor implementation challenges without recourse to other software solutions. The automated workflow was demonstrated with data from a [Formula: see text] NMR study of uranyl salts described previously (Cho et al. in J Chem Phys 132:084501, 2010).ConclusionsThe functional implementation of an automated process linking NMR data with electronic structure predictions demonstrates that modern software tools such as Kepler can be used to construct programs that comprehensively manage complex, multi-step scientific workflows spanning several different computers. Automation of the workflow can greatly accelerate the pace of discovery, and allows researchers to focus on the fundamental scientific questions rather than mastery of specialized software and data processing techniques. Future developments that would expand the scope and power of this approach include tools to standardize data and associated metadata formats, and the creation of interactive user interfaces to allow real-time exploration of the effects of program inputs on calculated outputs.

We describe an efficient parallel implementation of the selected inversion algorithm for distributed memory computer systems, which we call PSelInv. The PSelInv method computes selected elements of a general sparse matrix Athat can be decomposed as A= LU, where L is lower triangular and U is upper triangular. The implementation described in this article focuses on the case of sparse symmetric matrices. It contains an interface that is compatible with the distributed memory parallel sparse direct factorization SuperLU-DIST. However, the underlying data structure and design of PSelInv allows it to be easily combined with other factorization routines, such as PARDISO. We discuss general parallelization strategies such as data and task distribution schemes. In particular, we describe how to exploit the concurrency exposed by the elimination tree associated with the LU factorization of A. We demonstrate the efficiency and accuracy of PSelInv by presenting several numerical experiments. In particular, we show that PSelInv can run efficiently on more than 4,000 cores for a modestly sized matrix. We also demonstrate how PSelInv can be used to accelerate large-scale electronic structure calculations.

The recently introduced coupled cluster (CC) downfolding techniques for reducing the dimensionality of quantum many-body problems recast the CC formalism in the form of the renormalization procedure allowing, for the construction of effective (or downfolded) Hamiltonians in small-dimensionality sub-space, usually identified with the so-called active space, of the entire Hilbert space. The resulting downfolded Hamiltonians integrate out the external (out-of-active-space) Fermionic degrees of freedom from the internal (in-the-active-space) parameters of the wave function, which can be determined as components of the eigenvectors of the downfolded Hamiltonians in the active space. This paper will discuss the extension of non-Hermitian (associated with standard CC formulations) and Hermitian (associated with the unitary CC approaches) downfolding formulations to composite quantum systems commonly encountered in materials science and chemistry. The non-Hermitian formulation can provide a platform for developing local CC approaches, while the Hermitian one can serve as an ideal foundation for developing various quantum computing applications based on the limited quantum resources. We also discuss the algorithm for extracting the semi-analytical form of the inter-electron interactions in the active spaces. [ABSTRACT FROM AUTHOR]

Digital quantum computers provide a computational framework for solving the Schrödinger equation for a variety of many‐particle systems. Quantum computing algorithms for the quantum simulation of these systems have recently witnessed remarkable growth, notwithstanding the limitations of existing quantum hardware, especially as a tool for electronic structure computations in molecules. In this review, we provide a self‐contained introduction to emerging algorithms for the simulation of Hamiltonian dynamics and eigenstates, with emphasis on their applications to the electronic structure in molecular systems. Theoretical foundations and implementation details of the method are discussed, and their strengths, limitations, and recent advances are presented. This article is categorized under:Quantum Computing > AlgorithmsElectronic Structure Theory > Ab Initio Electronic Structure MethodsQuantum Computing > Theory Development [ABSTRACT FROM AUTHOR]

Electron–electron interactions and correlations form the basis of difficulties encountered in the theoretical solution of problems dealing with multi-electron systems. Accurate treatment of the electron–electron problem is likely to unravel some nice physical properties of matter embedded in the interaction. In an effort to tackle this many-body problem, a symmetry-dependent all-electron potential generalized for an n-electron atom is suggested in this study. The symmetry dependence in the proposed potential hinges on an empirically determined angular momentum-dependent partitioning fraction for the electron–electron interaction. With the potential, all atoms are treated in the same way regardless of whether they are open or closed shell using their system specific information. The non-relativistic ground-state ionization potentials for atoms with up to 103 electrons generated using the all-electron potential are in reasonable agreement with the existing experimental and theoretical data. The effects of higher-order non-relativistic interactions as well as the finite nuclear mass of the atoms are also analysed.

The development of relativistic coupled‐cluster (CC) and equation‐of‐motion coupled‐cluster (EOM‐CC) methods is reviewed. An emphasis is placed on recent efforts to improve the computational efficiency of CC and EOM‐CC calculations with non‐perturbative treatments of spin‐orbit coupling (SO‐CC and EOM‐CC) by partially recovering spin symmetry in the formulations. Example calculations of electronic ground state as well as valence‐excited and core‐excited states for molecules containing heavy elements are presented to demonstrate the applicability and usefulness of the SO‐CC and EOM‐CC methods. Future directions for the development of the SO‐CC and EOM‐CC methods are also discussed. This article is categorized under:Electronic Structure Theory > Ab Initio Electronic Structure Methods [ABSTRACT FROM AUTHOR]

The Gator program has been developed for computational spectroscopy and calculations of molecular properties using real and complex propagators at the correlated level of wave function theory. Currently, the focus lies on methods based on the algebraic diagrammatic construction (ADC) scheme up to the third order of perturbation theory. An auxiliary Fock matrix‐driven implementation of the second‐order ADC method for excitation energies has been realized with an underlying hybrid MPI/OpenMP parallelization scheme suitable for execution in high‐performance computing cluster environments. With a modular and object‐oriented program structure written in a Python/C++ layered fashion, Gator additionally enables time‐efficient prototyping of novel scientific approaches, as well as interactive notebook‐driven training of students in quantum chemistry. This article is categorized under:Computer and Information Science > Computer Algorithms and ProgrammingElectronic Structure Theory > Ab Initio Electronic Structure MethodsSoftware > Quantum Chemistry [ABSTRACT FROM AUTHOR]

The recent many‐body expanded full configuration interaction (MBE‐FCI) method is reviewed by critically assessing its advantages and drawbacks in the context of contemporary near‐exact electronic structure theory. Besides providing a succinct summary of the history of MBE‐FCI to date within a generalized and unified theoretical setting, its finer algorithmic details are discussed alongside our optimized computational implementation of the theory. A selected few of the most recent applications of MBE‐FCI are revisited, before we close by outlining its future research directions as well as its place among modern near‐exact wave function‐based methods. This article is categorized under:Electronic Structure Theory > Ab Initio Electronic Structure Methods [ABSTRACT FROM AUTHOR]

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller-Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.

We describe a novel variant of the driven molecular dynamics (DMD) method derived for probing Raman active vibrations. The method is an extension of the conventional μ-DMD formulation for simulating IR activity by means of coupling an oscillating electric field to the molecule's dipole moment, μ, and inducing absorption of energy via tuning the field to a resonant frequency. Presently, we modify the above prescription to invoke Raman activity by coupling two electric fields, i.e. a 'Pump' photon of frequency ωP and a Stokes photon of frequency ωS to the molecule's polarizability tensor, α, with the difference in the frequencies ω = ωP – ωS corresponding to the Stokes Raman shift. If ω is close to a Raman active vibrational frequency, energy absorption ensues. Varying ω allows identifying and assigning all Raman active vibrational modes, including anharmonic corrections, by means of trajectory analysis. We show that only one element of the full polarizability tensor, and its nuclear derivative, is needed for an α-DMD trajectory, making this method well suited for ab initio dynamics implementation. Numerical results using first-principles calculations are presented and discussed for the vibrational fundamentals, combination bands, overtones of H2O, CH4, and the C20 fullerene. [ABSTRACT FROM AUTHOR]

We describe a novel variant of the driven molecular dynamics (DMD) method derived for probing Raman active vibrations. The method is an extension of the conventional μ-DMD formulation for simulating IR activity by means of coupling an oscillating electric field to the molecule's dipole moment, μ, and inducing absorption of energy via tuning the field to a resonant frequency. Presently, we modify the above prescription to invoke Raman activity by coupling two electric fields, i.e. a 'Pump' photon of frequency ωP and a Stokes photon of frequency ωS to the molecule's polarizability tensor, α, with the difference in the frequencies ω = ωP – ωS corresponding to the Stokes Raman shift. If ω is close to a Raman active vibrational frequency, energy absorption ensues. Varying ω allows identifying and assigning all Raman active vibrational modes, including anharmonic corrections, by means of trajectory analysis. We show that only one element of the full polarizability tensor, and its nuclear derivative, is needed for an α-DMD trajectory, making this method well suited for ab initio dynamics implementation. Numerical results using first-principles calculations are presented and discussed for the vibrational fundamentals, combination bands, overtones of H2O, CH4, and the C20 fullerene. [ABSTRACT FROM AUTHOR]

We make an initial exploration of a spectral filtering approach to numerically approximating solutions to the time-independent Schrödinger equation for a model system of two spinless fermions with harmonic interactions. Fourier transformation of the time evolution of an arbitrary antisymmetrized wave packet results in resonance at frequencies proportional to eigenenergies of the system Hamiltonian, while the Fourier coefficient approximates the corresponding eigenfunction. Spectral filtering is explored using the two-particle model through both direct numerical integration of the Schrödinger equation and a semiclassical parametrisation. In the former, a discrete position basis describes the time-evolution operator, which is then repeatedly applied to an antisymmetrized wave packet to obtain the packet's time evolution. In the semiclassical parametrisation, equations of motion for the parameters are obtained from the Dirac-Frenkel-McLachlan functional. Integration of the parameter equations of motion describes the packet's time evolution. The semiclassical approach requires less memory and accurately obtains the eigenspectrum. In a step towards application of spectral filtering to realistic systems, a possible ansatz for use with Coulomb potentials is explored, using a simple model Hamiltonian. [ABSTRACT FROM AUTHOR]

Transition metal porphyrazines are a widely used class of compounds with applications in catalysis, organic solar cells, photodynamic therapy, and nonlinear optics. The most prominent members of that family of compounds are metallophtalocyanines, which have been the subject of numerous spectroscopic and theoretical studies. In this work, the electronic structure and X‐ray absorption characteristics of three Cu‐porphyrazine derivatives are investigated by means of modern electronic structure theory. More precisely, the experimentally observed N K‐edge and Cu L‐edge features are presented and reproduced by time‐dependent density functional theory, restricted open‐shell configuration interaction, and a restricted active space approach. Where possible, the calculations are used to interpret the observed spectroscopic features in terms of electronic transitions and, furthermore, to connect spectral differences to chemical variations. Part of the discussion of the computational results concerns the impact of various parameters and approximations that are used for the calculations, for example, the choice of active space. [ABSTRACT FROM AUTHOR]

The Born–Oppenheimer potential energy surface (PES) has come a long way since its introduction in the 1920s, both conceptually and in predictive power for practical applications. Nevertheless, nearly 100 years later—despite astonishing advances in computational power—the state-of-the-art first-principles prediction of observables related to spectroscopy and scattering dynamics is surprisingly limited. For example, the water dimer, (H2O)2, with only six nuclei and 20 electrons, still presents a formidable challenge for full-dimensional variational calculations of bound states and is considered out of reach for rigorous scattering calculations. The extremely poor scaling of the most rigorous quantum methods is fundamental; however, recent progress in development of approximate methodologies has opened the door to fairly routine high-quality predictions, unthinkable 20 years ago. In this review, in relation to the workflow of spectroscopy and/or scattering studies, we summarize progress and challenges in the component areas of electronic structure calculations, PES fitting, and quantum dynamical calculations. [ABSTRACT FROM AUTHOR]

Kohn-Sham density functional theory with the available exchange–correlation functionals is less accurate for strongly correlated systems, which require a multiconfigurational description as a zero-order function, than for weakly correlated systems, and available functionals of the spin densities do not accurately predict energies for many strongly correlated systems when one uses multiconfigurational wave functions with spin symmetry. Furthermore, adding a correlation functional to a multiconfigurational reference energy can lead to double counting of electron correlation. Multiconfiguration pair-density functional theory (MC-PDFT) overcomes both obstacles, the second by calculating the quantum mechanical part of the electronic energy entirely by a functional, and the first by using a functional of the total density and the on-top pair density rather than the spin densities. This allows one to calculate the energy of strongly correlated systems efficiently with a pair-density functional and a suitable multiconfigurational reference function. This article reviews MC-PDFT and related background information. [ABSTRACT FROM AUTHOR]

Interfacing magnetism with superconductivity gives rise to a wonderful playground for intertwining key degrees of freedom: Cooper pairs, spin, charge, and spin-orbit interaction, from which emerge a wealth of exciting phenomena, fundamental in the nascent field of superconducting spinorbitronics and topological quantum technologies. Magnetic exchange interactions (MEIs), being isotropic or chiral such as the Dzyaloshinskii-Moriya interactions, are vital in establishing the magnetic behavior at these interfaces as well as in dictating not only complex transport phenomena, but also the manifestation of topologically trivial or non-trivial objects. Here, we propose a methodology enabling the extraction of the tensor of MEI from electronic structure simulations accounting for superconductivity. We apply our scheme to the case of a Mn layer deposited on Nb(110) surface and explore proximity-induced impact on the MEI. The latter are weakly modified by a realistic electron-phonon coupling. However, tuning the superconducting order parameter, we unveil potential change of the magnetic order accompanied with chirality switching, as induced by the interplay of spin-orbit interaction and Cooper pairing. Owing to its simple formulation, our methodology can be readily implemented in state-of-the-art frameworks capable of tackling superconductivity and magnetism. We thus foresee implications in the simulations and prediction of topological superconducting bits as well as of cryogenic superconducting hybrid devices involving magnetic units., (Creative Commons Attribution license.)

Since the postulation of carbenes by Buchner (1903) and Staudinger (1912) as electron-deficient transient species carrying a divalent carbon atom, carbenes have emerged as key reactive intermediates in organic synthesis and in molecular mass growth processes leading eventually to carbonaceous nanostructures in the interstellar medium and in combustion systems. Contemplating the short lifetimes of these transient molecules and their tendency for dimerization, free carbenes represent one of the foremost obscured classes of organic reactive intermediates. Here, we afford an exceptional glance into the fundamentally unknown gas-phase chemistry of preparing two prototype carbenes with distinct multiplicities--triplet pentadiynylidene (HCCCCCH) and singlet ethynylcyclopropenylidene (c-C5H2) carbene-- via the elementary reaction of the simplest organic radical-- methylidyne (CH)--with diacetylene (HCCCCH) under single-collision conditions. Our combination of crossed molecular beam data with electronic structure calculations and quasi-classical trajectory simulations reveals fundamental reaction mechanisms and facilitates an intimate understanding of bond-breaking processes and isomerization processes of highly reactive hydrocarbon intermediates. The agreement between experimental chemical dynamics studies under single-collision conditions and the outcome of trajectory simulations discloses that molecular beam studies merged with dynamics simulations have advanced to such a level that polyatomic reactions with relevance to extreme astrochemical and combustion chemistry conditions can be elucidated at the molecular level and expanded to higher-order homolog carbenes such as butadiynylcyclopropenylidene and triplet heptatriynylidene, thus offering a versatile strategy to explore the exotic chemistry of novel higherorder carbenes in the gas phase. [ABSTRACT FROM AUTHOR]

Results from single photon vacuum ultraviolet photoionization of astrophysically relevant CnN clusters, n = 4 - 12, in the photon energy range of 8.0 eV to 12.8 eV are presented. The experimental photoionization efficiency curves, combined with electronic structure calculations, provide improved ionization energies of the CnN species. A search through numerous nitrogen-terminated CnN isomers for n=4-9 indicates that the linear isomer has the lowest energy, and therefore should be the most abundant isomer in the molecular beam. Comparison with calculated results also shed light on the energetics of the linear CnN clusters, particularly in the trends of the even-carbon and the odd-carbon series. These results can help guide the search of potential astronomical observations of these neutral molecules together with their cations in highly ionized regions or regions with a high UV/VUV photon flux (ranging from the visible to VUV with flux maxima in the Lyman- region) in the interstellar medium.

We seek correlation‐consistent diffuse‐augmented double‐zeta and triple‐zeta basis sets that perform optimally in extrapolating the correlation energy to the one‐electron complete basis set limit, denoted oAVXZ and oAV(X + d)Z. The novel basis sets are method‐dependent in that they are trained to perform optimally for the correlation energy at each specific level of theory. They are shown to yield accurate results in calculating both the energy and tensorial properties such as polarizabilities while not significantly altering the Hartree‐Fock energy. Quantitatively, complete basis set limit (CBS)‐/(oAVdZ,oAVtZ)‐extrapolated correlation energies typically outperform, by 3‐ to 5‐fold, the ones calculated with traditional ansatzes of similar flexibility. Attaining energies of CBS/(AVtZ,AVqZ) type or better accuracy, they frequently outperform expensive raw explicitly correlated ones. Promisingly, a limited test on CBS‐extrapolated energies based on conventional basis sets has shown that they compare well even with extrapolated explicitly correlated ones. Calculated atomization and dissociation energies, molecular geometries, ionization potentials, and electron affinities also tend to outperform the ones obtained with traditional Dunning's ansatzes from which the new basis sets have been determined. The method for basis set generation is simple, and there is no reason of principle why the approach could not be adapted for handling other bases in the literature. [ABSTRACT FROM AUTHOR]

In this work we report on single photon vacuum ultraviolet photoionization of small silicon clusters (n=1-7) produced via laser ablation of Si. The adiabatic ionization energies (AIE) are extracted from experimental photoionization efficiency (PIE) curves with the help of Frank?Condon simulations, used to interpret the shape and onset of the PIE curves. The obtained AIEs are (all energies are in eV): Si (8.13+-0.05), Si2 (7.92+-0.05), Si3 (8.12+-0.05), Si4 (8.2+-0.1), Si5 (7.96+-0.07), Si6 (7.8+-0.1), and Si7 (7.8+-0.1). Most of the experimental AIE values are in good agreement with ab initio electronic structure calculations. To explain observed deviations between the experimental and theoretical AIEs for Si4 and Si6, a theoretical search of different isomers of these species is performed. Electronic structure calculations aid in the interpretation of the a2PIu state of Si2+ dimer in the PIE spectrum. Time dependent density functional theory (TD-DFT) calculations are performed to reveal the energies of electronically excited states in the cations for a number of Si clusters.