Michael F. Herbst

Bio: Michael F. Herbst is an academic researcher from RWTH Aachen University. The author has contributed to research in topics: Python (programming language) & Basis function. The author has an hindex of 7, co-authored 20 publications receiving 134 citations. Previous affiliations of Michael F. Herbst include University of Paris & École des ponts ParisTech.

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

Abstract: This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

adcc: A versatile toolkit for rapid development of algebraic‐diagrammatic construction methods

Abstract: ADC-connect (adcc) is a hybrid python/C++ module for performing excited state calculations based on the algebraic-diagrammatic construction scheme for the polarisation propagator (ADC). Key design goal is to restrict adcc to this single purpose and facilitate connection to external packages, e.g., for obtaining the Hartree-Fock references, plotting spectra, or modelling solvents. Interfaces to four self-consistent field codes have already been implemented, namely pyscf, psi4, molsturm, and veloxchem. The computational workflow, including the numerical solvers, are implemented in python, whereas the working equations and other expensive expressions are done in C++. This equips adcc with adequate speed, making it a flexible toolkit for both rapid development of ADC-based computational spectroscopy methods as well as unusual computational workflows. This is demonstrated by three examples. Presently, ADC methods up to third order in perturbation theory are available in adcc, including the respective core-valence separation and spin-flip variants. Both restricted or unrestricted Hartree-Fock references can be employed.

DFTK: A Julian approach for simulating electrons in solids

Abstract: Density-functional theory (DFT) is a widespread method for simulating the quantum-chemical behaviour of electrons in matter. It provides a first-principles description of many optical, mechanical and chemical properties at an acceptable computational cost [16, 2, 3]. For a wide range of systems the obtained predictions are accurate and shortcomings of the theory are by now wellunderstood [2, 3]. The desire to tackle even bigger systems and more involved materials, however, keeps posing novel challenges that require methods to constantly improve. One example are socalled high-throughput screening approaches, which are becoming prominent in recent years. In these techniques one wishes to systematically scan over huge design spaces of compounds in order to identify promising novel materials for targeted follow-up investigation. This has already lead to many success stories [14], such as the discovery of novel earth-abundant semiconductors [11], novel light-absorbing materials [20], electrocatalysts [8], materials for hydrogen storage [13] or for Li-ion batteries [1]. Keeping in mind the large range of physics that needs to be covered in these studies as well as the typical number of calculations (up to the order of millions), a bottleneck in these studies is the reliability and performance of the underlying DFT codes.

Polarizable Embedding Combined with the Algebraic Diagrammatic Construction: Tackling Excited States in Biomolecular Systems.

Abstract: We present a variant of the algebraic diagrammatic construction (ADC) scheme by combining ADC with the polarizable embedding (PE) model. The presented PE-ADC method is implemented through second and third order and is designed with the aim of performing accurate calculations of excited states in large molecular systems. Accuracy and large-scale applicability are demonstrated with three case studies, and we further analyze the importance of both state-specific and linear-response-type corrections to the excitation energies in the presence of the polarizable environment. We demonstrate how our combined method can be readily applied to study photoinduced biochemical processes as we model the charge-transfer (CT) excitation which is key to the photoprotection mechanism in the dodecin protein with PE-ADC(2). Through direct access to state-of-the-art excited state analysis, we find that the polarizable environment plays a decisive role by significantly increasing the CT character of the electronic excitation in...

Quantifying the error of the core-valence separation approximation.

Abstract: For the calculation of core-excited states probed through X-ray absorption spectroscopy, the core-valence separation (CVS) scheme has become a vital tool. This approach allows us to target such states with high specificity, albeit introducing an error. We report the implementation of a post-processing step for CVS excitations obtained within the algebraic-diagrammatic construction scheme for the polarization propagator, which removes this error. Based on this, we provide a detailed analysis of the CVS scheme, identifying its accuracy to be dominated by an error balance between two neglected couplings, one between core and valence single excitations and the other between single and double core excitations. The selection of the basis set is shown to be vital for a proper description of both couplings, with tight polarizing functions being necessary for a good balance of errors. The CVS error is confirmed to be stable across multiple systems, with an element-specific spread for K-edge spectrum calculations of only about ±0.02 eV. A systematic lowering of the CVS error by 0.02 eV-0.03 eV is noted when considering excitations to extremely diffuse states, emulating ionization.

Adaptive finite element methods for differential equations.

Abstract: Gegenstand des Buches ist die Dual Weighted Residual method (DWR), ein sehr effizientes numerisches Verfahren zur Behandlung einer großen Klasse von variationell formulierten Differentialgleichungen. Das numerische Verfahren ist adaptiv, d.h. es konstruiert eigenständig eine Folge von Approximationen für eine gegebene Fragestellung. Typische Fragestellungen sind die Bestimmung gewichteter Mittelwerte der Lösung oder ihrer Ableitungen, die Bestimmung von Randintegralen über Lösungskomponenten (relevant z.B. für die Berechnung von strömungsmechanischen Kenngrößen) oder die Bestimmung von Spannungsintensitätsfaktoren (z.B. in der Bruchmechanik). Das Verfahren basiert auf Projektionsmethoden wie z.B. der Finiten Elemente Methode (FEM). Dort wird die Approximationsgüte durch die Wahl der Gitter gesteuert. Der Kern jeder adaptiven FEM ist deshalb die Art, wie die Gitter gewählt werden. Typischerweise geschieht dies in einer adaptiven Schleife, in der in mehreren Durchgängen schrittweise das Gitter verbessert wird, bis eine gewünschte Genauigkeit erreicht ist. Bei der DWR wird in jedem Schleifendurchgang ein lineares Hilfsproblem—das sog. duale Problem, welches von der vorliegenden Fragestellung abhängt—(näherungsweise) gelöst. Weiterhin wird eine Approximation der Differentialgleichung bestimmt. Aus diesen nun vorliegenden Daten wird dann herausdestilliert, wo das Gitter verfeinert werden sollte bzw. vergröbert werden kann, um eine genauere Lösung zu erhalten. Ziel eines adaptiven Algorithmus ist, das gewünschte Ergebnis möglichst effizient zu bestimmen, d.h. mit möglichst geringem Bedarf an Resourcen (Rechenzeit, Speicherbedarf etc.). Mit zahlreichen Beispielen belegt das Buch, daß die DWR dieses Ziel erreicht. Es sei hier besonders hervorgehoben, daß eine Kosten-Nutzen-Betrachtung für die DWR besonders bei nichtlinearen Problemen günstig ausfällt, da die Kosten für die Lösung des linearen Hilfsproblems vergleichbar mit denen eines Newtonschrittes sind und somit nur einen kleinen Teil der Gesamtkosten ausmachen. Das Buch gibt einen sehr guten Überblick über die Technik und die Möglichkeiten der DWR. In einleitenden Kapiteln wird die DWR an gewöhnlichen Differentialgleichungen und dann an einfachen linearen, elliptischen partiellen Differentialgleichungen sehr klar und verständlich vorgeführt. Anschließend wird die DWR in einem abstrakten funktionalanalytischen Rahmen vorgestellt. Der Rest des Buches illustriert auf eindrucksvolle Weise die Leistungsfähigkeit und Breite der Anwendungsfähigkeit des Konzeptes an Hand von Fallbeispielen: Es werden Eigenwertprobleme, Optimierungsaufgaben mit Zwangsbedingungen, die durch eine partielle Differentialgleichung gegeben sind, Strukturmechanikprobleme (lineare Elastizität, Plastizität), Strömungsmechanik (hydrodynamische Stabilitätsanalyse, Berechnung von Strömungskennwerten) behandelt. Auch zeitabhängige Probleme wie die Lösung der Wellengleichung werden mit der DWR erfolgreich bearbeitet. Insgesamt wird klar ersichtlich, daß die DWR eine sehr flexible und vielseitig anwendbare Technik ist. Die ausgewählten numerischen Beispiele, die vor allem aus umfangreichen numerischen Untersuchungen der Gruppe von Rolf Rannacher aus den letzten 10 Jahren ausgewählt wurden, sind sehr illustrativ. Die Erläuterungen zu den Beispielen sind auch deshalb interessant, weil eine Menge zusätzlicher Informationen über die numerische Behandlung des vorliegenden Problems quasi nebenbei einfließen. Das Buch entstand aus einer fortgeschrittenen Spezialvorlesung, die an der ETH Zürich gehalten wurde. Einen Lehrbuchcharakter erhält das Buch dadurch, daß Übungsaufgaben (mit detailierten Lösungen im Anhang) jedes Kapitel abschließen. Die Aufgaben enthal-

Psi4 1.4: Open-source software for high-throughput quantum chemistry

Abstract: PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient, thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of PSI4's core functionalities via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSCHEMA data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCARCHIVE INFRASTRUCTURE project, makes the latest version of PSI4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs.

Recent developments in the PySCF program package

Abstract: PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

Abstract: This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.