ORBKIT: A modular python toolbox for cross‐platform postprocessing of quantum chemical wavefunction data

Hermann, Günter; Pohl, Vincent; Tremblay, Jean Christophe; Paulus, Beate; Hege, Hans‐Christian; Schild, Axel

doi:10.1002/jcc.24358

Cited by 107 publications

(91 citation statements)

References 44 publications

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“…1 To illustrate the challenges present when analysing excitedstates with previously available tools, we want to start with the example of oligothiophene, a widely studied system due to its importance as a building block for organoelectronic materials. [71,72] An inspection of these densities, shown in the centre column of Figure 1, reveals that all states possess about the same degree of delocalization and that similar nodal planes are present on the individual thiophene units. [70] The symmetry labels and excitation energies of the lowest five states are presented in the left column of Figure 1.…”

Section: Felix Plasser* [A]mentioning

confidence: 99%

Visualisation of Electronic Excited‐State Correlation in Real Space

Plasser

2019

ChemPhotoChem

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A method for the visualisation of excited-state electron correlation is introduced and shown to address two notorious problems in excited-state electronic structure theory, the analysis of excitonic correlation and the distinction between covalent and ionic wavefunction character. The method operates by representing the excited state in terms of electron and hole quasiparticles, fixing the hole on a fragment of the system and observing the resulting conditional electron density in real space. The application of this approach to oligothiophene, an exemplary conjugated polymer, illuminates excitonic correlation effects of its excited states in unprecedented clarity and detail. A study of naphthalene shows that the distinction between the ionic and covalent states of this molecule, which has so far only been achieved using elaborate valence-bond theory protocols, arises naturally in terms of electron-hole avoidance and enhanced overlap, respectively. More generally, the method is relevant for any excited state that cannot be described by a single electronic configuration.Electronically excited states of molecules form the underpinnings of a wide range of processes of utmost scientific interest, such as light-driven natural processes [1,2] photochemical reactions, [3] signalling and sensing, [4] and the operation of organoelectronic materials. [5,6] Computational photochemistry has become an indispensable part of scientific investigations in these areas through two main tasks, the interpretation of experimental results and the prediction of unknown photophysical properties. Indeed, the predictive power of computational photochemistry has steadily increased over the recent years due to the tremendous effort spent in the development of new methods as well as rapid progress in computer technology. [7][8][9][10][11][12] However, the interpretation of this wealth of computational data can act as a significant impediment in practical work. Therefore, a number of analysis tools have been developed to quantify excited-state properties [13][14][15][16][17] and to visualise the molecular orbitals (MOs) involved and their location in space in a compact and rigorous way. [18][19][20][21][22][23] However, the above-mentioned visualisation tools -and the MO picture itself -break down if the information of interest does not lie in the MOs themselves but in the interaction of different quasidegenerate electronic configurations. Such cases are widespread and two notorious failures of the MO picture relate to excitons in extended systems [24][25][26] and to ionic/ covalent wavefunction character in alternant hydrocarbons. [27,28] The first case is related to the emergence of band structure in large systems, which leads to excited states formed as a superposition of many different electronic configurations whose description requires moving from the MO picture to a representation in terms of correlated electron and hole quasiparticles. [26,[29][30][31] Previous attempts of visualising the ensuing correlated electron-hole distribution ha...

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Section: Felix Plasser* [A]mentioning

confidence: 99%

Visualisation of Electronic Excited‐State Correlation in Real Space

Plasser

2019

ChemPhotoChem

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“…In our laboratory, we have developed the Graphics Processing Units for Atoms and Molecules (GPUAM) code to evaluate several scalar and vector quantum chemistry fields coupled with the Atoms in Molecules (AIM) analysis . It is worth to mention that there are several codes with some of these capabilities . However, GPUAM has been designed to use heterogeneous computational resources.…”

Section: Evaluation Of Quantum Chemistry Fields By Using Gpusmentioning

confidence: 99%

GPUs as boosters to analyze scalar and vector fields in quantum chemistry

Hernández‐Esparza

Vázquez‐Mayagoitia

Soriano-Agueda

et al. 2018

Int J of Quantum Chemistry

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The analysis of scalar and vector fields in quantum chemistry is an essential task for the computational chemistry community, where such quantities must be evaluated rapidly to perform a particular study. For example, the atoms in molecules approach proposed by Bader has become popular; however, this method demands significant computational resources to compute the involved tasks in short times. In this article, we discuss the importance of graphics processing units (GPU) to analyze electron density, and related fields, implementing several scalar, and vector fields within the graphics processing units for atoms and molecules (GPUAM) code developed by a group of the Universidad Autónoma Metropolitana in México City. With this application, the quantum chemistry community can perform demanding computational tasks on a desktop, where CPUs and GPUs are used to their maximum capabilities. The performance of GPUAM is tested in several systems and over different GPUs, where a GPU installed in a workstation converts it to a robust high‐performance computing system.

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“…All required information to reconstruct MO, that is, the MO‐LCAO coefficients

D_{i A}^{false(a false)}

and the atom‐centered basis functions, can be found in the output of standard quantum chemistry program packages. The integrals in the atomic orbital basis are computed analytically with our Python post‐processing toolbox ORBKIT for a wide range of one‐electron operators …”

Section: Computational Procedures and Theorymentioning

confidence: 99%

An open‐source framework for analyzing N‐electron dynamics. I. Multideterminantal wave functions

2017

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The aim of the present contribution is to provide a framework for analyzing and visualizing the correlated many-electron dynamics of molecular systems, where an explicitly time-dependent electronic wave packet is represented as a linear combination of N -electron wave functions. The central quantity of interest is the electronic flux density, which contains all information about the transient electronic density, the associated phase, and their temporal evolution. It is computed from the associated one-electron operator by reducing the multi-determinantal, many-electron wave packet using the Slater-Condon rules. Here, we introduce a general tool for post-processing multi-determinant configuration-interaction wave functions obtained at various levels of theory. It is tailored to extract directly the data from the output of standard quantum chemistry packages using atom-centered Gaussian-type basis functions. The procedure is implemented in the open-source Python program detCI@ORBKIT, which shares and builds upon the modular design of our recently published post-processing toolbox [J. Comput. Chem. 37 (2016) 1511]. The new procedure is applied to ultrafast charge migration processes in different molecular systems, demonstrating its broad applicability.Convergence of the N -electron dynamics with respect to the electronic structure theory level and basis set size is investigated. This provides an assessment of the robustness of qualitative and quantitative statements that can be made concerning dynamical features observed in charge migration simulations.

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ORBKIT: A modular python toolbox for cross‐platform postprocessing of quantum chemical wavefunction data

Cited by 107 publications

References 44 publications

Visualisation of Electronic Excited‐State Correlation in Real Space

Visualisation of Electronic Excited‐State Correlation in Real Space

GPUs as boosters to analyze scalar and vector fields in quantum chemistry

An open‐source framework for analyzing N‐electron dynamics. I. Multideterminantal wave functions

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