Markus Reiher

Last Name

Reiher

First Name

Markus

ORCID

0000-0002-9508-1565

Organisational unit

03736 - Reiher, Markus / Reiher, Markus

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Publications 1 - 10 of 141

Access the Molecular World through Haptic Quantum Chemistry
Müller, Charlotte H.; Kapur, Manu; Reiher, Markus (2021)
Semiclassical Dispersion Corrections Efficiently Improve Multiconfigurational Theory with Short-Range Density-Functional Dynamic Correlation
Stein, Christopher J.; Reiher, Markus (2020)
The Journal of Physical Chemistry A
Multiscale Embedding for Quantum Computing
Weisburn, Leah P.; Cho, Minsik; Bensberg, Moritz; et al. (2025)
Journal of Chemical Theory and Computation
We present a novel multiscale embedding scheme that links conventional QM/MM embedding and bootstrap embedding (BE) to allow simulations of large chemical systems on limited quantum devices. We also propose a mixed-basis BE scheme that facilitates BE calculations on extended systems using classical computers with limited memory resources. Benchmark data suggest the combination of these two strategies as a robust path in attaining the correlation energies of large realistic systems, combining the proven accuracy of BE with chemical and biological systems of interest in a lower computational cost method. Due to the flexible tunability of the resource requirements and systematic fragment construction, future developments in the realization of quantum computers naturally offer improved accuracy for multiscale BE calculations.
Analytically projected, rotationally symmetric, explicitly correlated Gaussian functions with one-axis-shifted centers
Muolo, Andrea; Reiher, Markus (2020)
Physical Review A
An explicitly correlated functional form for expanding the wave function of an N-particle system with arbitrary angular momentum and parity is presented. We develop the projection-based approach, numerically exploited in our previous work [J. Muolo, E. Mátyus, and M. Reiher, J. Chem. Phys. 149, 184105 (2018)], to explicitly correlated Gaussian functions with one-axis-shifted centers and derive the matrix elements for the Hamiltonian and the angular momentum operators by analytically solving the integral projection operator. Variational few-body calculations without assuming the Born-Oppenheimer approximation are presented for several rotationally excited states of three- and four-particle systems. We show how the formalism can be used as a unified framework for high-accuracy calculations of properties of small atoms and molecules. ©2020 American Physical Society
Solvation Free Energies in Subsystem Density Functional Theory
Bensberg, Moritz; Türtscher, Paul Lorenz; Unsleber, Jan Patrick; et al. (2022)
Journal of Chemical Theory and Computation
For many chemical processes the accurate description of solvent effects are vitally important. Here, we describe a hybrid ansatz for the explicit quantum mechanical description of solute-solvent and solvent-solvent interactions based on subsystem density functional theory and continuum solvation schemes. Since explicit solvent molecules may compromise the scalability of the model and transferability of the predicted solvent effect, we aim to retain both, for different solutes as well as for different solvents. The key for the transferability is the consistent subsystem decomposition of solute and solvent. The key for the scalability is the performance of subsystem DFT for increasing numbers of subsystems. We investigate molecular dynamics and stationary point sampling of solvent configurations and compare the resulting (Gibbs) free energies to experiment and theoretical methods. We can show that with our hybrid model reaction barriers and reaction energies are accurately reproduced compared to experimental data.
Automated Reaction Exploration of Ozonation Processes for Model Olefins in Water
Petrus , Enric; Hunkeler , Livia A.; Reiher, Markus; et al. (2025)
Environmental Science & Technology
The comprehensive evaluation of pollutant abatement during chemical oxidation processes and the identification of potentially hazardous transformation products are fundamental challenges in water and wastewater treatment. Here, we demonstrate how high-throughput computational chemistry enables the elucidation of reaction pathways via automated, quantum-chemistry-based chemical reaction network (CRN) explorations. We evaluated the predictive capabilities of this computational approach using the Software for Chemical Interaction Networks (SCINE) for studying the reactions of ozone with two olefins, ethene and tetramethylethene, in aqueous solution. Following a benchmarking of the quantum chemical methodology for structure optimization and energy calculations, we generated CRNs containing hundreds of compounds and thousands of reactions, identified reaction mechanisms, and evaluated product formation kinetics through microkinetic modeling. These CRN explorations led to the correct reproduction of experimental evidence for mechanisms and products of olefin ozonolysis for reactions of ozone and ethene solely on the basis of defining the reactants and their initial concentrations. The study of reactions of ozone and tetramethylethene also matched experimental data for the main products but revealed consequences of the limited exploration depth and shortcomings of the implicit solvation model. We envision that CRN explorations not only offer novel means for predicting pollutant transformation pathways but also will support chemical analysis and the assessment of effects on human and environmental health.
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
Husistein, Raphael T.; Reiher, Markus; Eckhoff, Marco (2025)
The Thirteenth International Conference on Learning Representations
Artificial neural networks have been shown to be state-of-the-art machine learning models in a wide variety of applications, including natural language processing and image recognition. However, building a performant neural network is a labo rious task and requires substantial computing power. Neural Architecture Search (NAS) addresses this issue by an automatic selection of the optimal network from a set of potential candidates. While many NAS methods still require training of (some) neural networks, zero-cost proxies promise to identify the optimal network without training. In this work, we propose the zero-cost proxy Network Expres sivity by Activation Rank (NEAR). It is based on the effective rank of the pre and post-activation matrix, i.e., the values of a neural network layer before and after applying its activation function. We demonstrate the cutting-edge correla tion between this network score and the model accuracy on NAS-Bench-101 and NATS-Bench-SSS/TSS. In addition, we present a simple approach to estimate the optimal layer sizes in multi-layer perceptrons. Furthermore, we show that this score can be utilized to select hyperparameters such as the activation function and the neural network weight initialization scheme.
Automated preparation of nanoscopic structures: Graph-based sequence analysis, mismatch detection, and pH-consistent protonation with uncertainty estimates
Csizi, Katja-Sophia; Reiher, Markus (2024)
Journal of Computational Chemistry
Structure and function in nanoscale atomistic assemblies are tightly coupled, andevery atom with its specific position and even every electron will have a decisiveeffect on the electronic structure, and hence, on the molecular properties. Molec-ular simulations of nanoscopic atomistic structures therefore require accuratelyresolved three-dimensional input structures. If extracted from experiment, thesestructures often suffer from severe uncertainties, of which the lack of informationon hydrogen atoms is a prominent example. Hence, experimental structuresrequire careful review and curation, which is a time-consuming and error-proneprocess. Here, we present a fast and robust protocol for the automated structureanalysis and pH-consistent protonation, in short, ASAP. For biomolecules as atarget, the ASAP protocol integrates sequence analysis and error assessment of agiven input structure. ASAP allows for pKₐ prediction from reference data throughGaussian process regression including uncertainty estimation and connects tosystem-focused atomistic modeling described in Brunken and Reiher (J. Chem. TheoryComput.16, 2020, 1646). Although focused on biomolecules, ASAP can be extendedto other nanoscopic objects, because most of its design elements rely on a generalgraph-based foundation guaranteeing transferability. The modular character ofthe underlying pipeline supports different degrees of automation, which allows for(i) efficient feedback loops for human-machine interaction with a low entrance barrierand for (ii) integration into autonomous procedures such as automated force fieldparametrizations. This facilitates fast switching of the pH-state through on-the-flysystem-focused reparametrization during a molecular simulation at virtually no extracomputational cost.
Tailored coupled cluster theory in varying correlation regimes
Mörchen, Maximilian; Freitag, Leon; Reiher, Markus (2020)
The Journal of Chemical Physics
The tailored coupled cluster (TCC) approach is a promising ansatz that preserves the simplicity of single-reference coupled cluster theory while incorporating a multi-reference wave function through amplitudes obtained from a preceding multi-configurational calculation. Here, we present a detailed analysis of the TCC wave function based on model systems, which require an accurate description of both static and dynamic correlation. We investigate the reliability of the TCC approach with respect to the exact wave function. In addition to the error in the electronic energy and standard coupled cluster diagnostics, we exploit the overlap of TCC and full configuration interaction wave functions as a quality measure. We critically review issues, such as the required size of the active space, size-consistency, symmetry breaking in the wave function, and the dependence of TCC on the reference wave function. We observe that possible errors caused by symmetry breaking can be mitigated by employing the determinant with the largest weight in the active space as reference for the TCC calculation. We find the TCC model to be promising in calculations with active orbital spaces which include all orbitals with a large single-orbital entropy, even if the active spaces become very large and then may require modern active-space approaches that are not restricted to comparatively small numbers of orbitals. Furthermore, utilizing large active spaces can improve on the TCC wave function approximation and reduce the size-consistency error because the presence of highly excited determinants affects the accuracy of the coefficients of low-excited determinants in the active space.
Classification of electronic structures and state preparation for quantum computation of reaction chemistry
Mörchen, Maximilian; Low, Guang Hao; Weymuth, Thomas; et al. (2024)
arXiv
Quantum computation for chemical problems will require the construction of guiding states with sufficient overlap with a target state. Since easily available and initializable mean-field states are characterized by an overlap that is reduced for multi-configurational electronic structures and even vanishes with growing system size, we here investigate the severity of state preparation for reaction chemistry. We emphasize weaknesses in current traditional approaches (even for weakly correlated molecules) and highlight the advantage of quantum phase estimation algorithms. An important result is the introduction of a new classification scheme for electronic structures based on orbital entanglement information. We identify two categories of multi-configurational molecules. Whereas class-1 molecules are dominated by very few determinants and often found in reaction chemistry, class-2 molecules do not allow one to single out a reasonably sized number of important determinants. The latter are particularly hard for traditional approaches and an ultimate target for quantum computation. Some open-shell iron-sulfur clusters belong to class 2. We discuss the role of the molecular orbital basis set and show that true class-2 molecules remain in this class independent of the choice of the orbital basis, with the iron-molybdenum cofactor of nitrogenase being a prototypical example. We stress that class-2 molecules can be build in a systematic fashion from open-shell centers or unsaturated carbon atoms. Our key result is that it will always be possible to initialize a guiding state for chemical reaction chemistry in the ground state based on initial low-cost approximate electronic structure information, which is facilitated by the finite size of the atomistic structures to be considered.

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Markus Reiher

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