Moritz Bensberg

Last Name

Bensberg

First Name

Moritz

ORCID

0000-0002-3479-4772

Organisational unit

03736 - Reiher, Markus / Reiher, Markus

Show all metadata

Search Results

Publications 1 - 10 of 13

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.
Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks
Müller, Charlotte H.; Steiner, Miguel; Unsleber, Jan Patrick; et al. (2024)
The Journal of Physical Chemistry A
Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexity of the tasks and in the amount of generated data. An efficient and intuitive way for an operator to interact with these data and to steer virtual experiments is required. Here, we introduce Heron, a graphical user interface that allows for advanced human-machine interactions with quantum chemical exploration campaigns into molecular structure and reactivity. Heron offers access to interactive and automated explorations of chemical reactions with standard electronic structure modules, haptic force feedback, microkinetic modeling, and refinement of data by automated correlated calculations including black-box complete active space calculations. It is tailored to the exploration and analysis of vast chemical reaction networks. We show how interoperable modules enable advanced workflows and pave the way for routine low-entrance-barrier access to advanced modeling techniques.
Hierarchical Quantum Embedding by Machine Learning for Large Molecular Assemblies
Bensberg, Moritz; Eckhoff, Marco; Husistein, Raphael T.; et al. (2025)
Journal of Chemical Theory and Computation
We present a quantum-in-quantum embedding strategy coupled to machine learning potentials to improve on the accuracy of quantum-classical hybrid models for the description of large molecules. In such hybrid models, relevant structural regions (such as those around reaction centers or pockets for binding of host molecules) can be described by a quantum model that is then embedded into a classical molecular-mechanics environment. However, this quantum region may become so large that only approximate electronic structure models are applicable. To then restore accuracy in the quantum description, we here introduce the concept of quantum cores within the quantum region that are amenable to accurate electronic structure models due to their limited size. Huzinaga-type projection-based embedding, for example, can deliver accurate electronic energies obtained with advanced electronic structure methods. The resulting total electronic energies are then fed into a transfer learning approach that efficiently exploits the higher-accuracy data to improve on a machine learning potential obtained for the original quantum-classical hybrid approach. We explore the potential of this approach in the context of a well-studied protein–ligand complex for which we calculate the free energy of binding using alchemical free energy and nonequilibrium switching simulations.
High Ground State Overlap via Quantum Embedding Methods
Erakovic, Mihael; Witteveen, Freek; Harley, Dylan; et al. (2025)
PRX Life
Quantum computers can accurately compute ground state energies using phase estimation, but this requires a guiding state that has significant overlap with the true ground state. For large molecules and extended materials, it becomes difficult to find guiding states with good ground state overlap for growing molecule sizes. Additionally, the required number of qubits and quantum gates may become prohibitively large. One approach for dealing with these challenges is to use a quantum embedding method, which allows a reduction to one or multiple smaller quantum cores embedded in a larger quantum region. In such situations, it is unclear how the embedding method affects the hardness of constructing good guiding states. In this work, we therefore investigate the preparation of guiding states in the context of quantum embedding methods. We extend previous work on quantum impurity problems, a framework in which we can rigorously analyze the embedding of a subset of orbitals. While there exist results for optimal active orbital space selection in terms of energy minimization, we rigorously demonstrate how the same principles can be used to define selected orbital spaces for state preparation in terms of the overlap with the ground state. Moreover, we perform numerical studies of molecular systems relevant to biochemistry, one field in which quantum embedding methods are required due to the large size of biomacromolecules such as proteins and nucleic acids. We investigate two different embedding strategies which can exhibit qualitatively different orbital entanglement. In all cases, we demonstrate that the easy-to-obtain mean-field state will have a sufficiently high overlap with the target state to perform quantum phase estimation.
Concentration-Flux-Steered Mechanism Exploration with an Organocatalysis Application
Bensberg, Moritz; Reiher, Markus (2023)
Israel Journal of Chemistry
Investigating a reactive chemical system with automated reaction network exploration algorithms provides a more detailed picture of its chemical mechanism than what would be accessible by manual investigation. In general, exploration algorithms cannot uncover reaction networks exhaustively for feasibility reasons. They should therefore decide which part of a network is kinetically relevant under some external conditions given. Here, we propose an automated algorithm that identifies and explores kinetically accessible regions of a reaction network on the fly by explicit modeling of concentration fluxes through an (incomplete) reaction network that is emerging during automated first-principles exploration. Key compounds are automatically identified and selected for the continuation of the exploration. As an example, we explore the reaction network of the multi-component proline-catalyzed Michael addition of propanal and nitropropene. Our algorithm provides a mechanistic picture of the Michael addition in unprecedented detail.
Uncertainty-Aware First-Principles Exploration of Chemical Reaction Networks
Bensberg, Moritz; Reiher, Markus (2024)
The Journal of Physical Chemistry A
Exploring large chemical reaction networks with automated exploration approaches and accurate quantum chemical methods can require prohibitively large computational resources. Here, we present an automated exploration approach that focuses on the kinetically relevant part of the reaction network by interweaving (i) large-scale exploration of chemical reactions, (ii) identification of kinetically relevant parts of the reaction network through microkinetic modeling, (iii) quantification and propagation of uncertainties, and (iv) reaction network refinement. Such an uncertainty-aware exploration of kinetically relevant parts of a reaction network with automated accuracy improvement has not been demonstrated before in a fully quantum mechanical approach. Uncertainties are identified by local or global sensitivity analysis. The network is refined in a rolling fashion during the exploration. Moreover, the uncertainties are considered during kinetically steering of a rolling reaction network exploration. We demonstrate our approach for Eschenmoser-Claisen rearrangement reactions. The sensitivity analysis identifies that only a small number of reactions and compounds are essential for describing the kinetics reliably, resulting in efficient explorations without sacrificing accuracy and without requiring prior knowledge about the chemistry unfolding.
The subsystem quantum chemistry program Serenity
Niemeyer, Niklas; Eschenbach, Patrick; Bensberg, Moritz; et al. (2023)
Wiley Interdisciplinary Reviews. Computational Molecular Science
SERENITY [J Comput Chem. 2018;39:788-798] is an open-source quantum chemistry software that provides an extensive development platform focused on quantum-mechanical multilevel and embedding approaches. In this study, we give an overview over the developments done in Serenity since its original publication in 2018. This includes efficient electronic-structure methods for ground states such as multilevel domain-based local pair natural orbital coupled cluster and Moller-Plesset perturbation theory as well as the multistate frozen-density embedding quasi-diabatization method. For the description of excited states, SERENITY features various subsystem-based methods such as embedding variants of coupled time-dependent density-functional theory, approximate second-order coupled cluster theory and the second-order algebraic diagrammatic construction technique as well as GW/Bethe-Salpeter equation approaches. SERENITY's modular structure allows combining these methods with density-functional theory (DFT)-based embedding through various practical realizations and variants of subsystem DFT including frozen-density embedding, potential-reconstruction techniques and projection-based embedding.This article is categorized under:Electronic Structure Theory > Density Functional TheoryElectronic Structure Theory > Ab Initio Electronic Structure MethodsSoftware > Quantum Chemistry
On the accuracy of orbital based multi-level approaches for closed-shell transition metal chemistry
Amanollahi, Zohreh; Lampe, Lukas; Bensberg, Moritz; et al. (2023)
Physical Chemistry Chemical Physics
In this work, we investigate the accuracy of the local molecular orbital molecular orbital (LMOMO) scheme and projection-based wave function-in-density functional theory (WF-in-DFT) embedding for the prediction of reaction energies and barriers of typical reactions involving transition metals. To analyze the dependence of the accuracy on the system partitioning, we apply a manual orbital selection for LMOMO as well as the so-called direct orbital selection (DOS) for both approaches. We benchmark these methods on 30 closed shell reactions involving 16 different transition metals. This allows us to devise guidelines for the manual selection as well as settings for the DOS that provide accurate results within an error of 2 kcal mol(-1) compared to local coupled cluster. To reach this accuracy, on average 55% of the occupied orbitals have to be correlated with coupled cluster for the current test set. Furthermore, we find that LMOMO gives more reliable relative energies for small embedded regions than WF-in-DFT embedding.
Orbital pair selection for relative energies in the domain-based local pair natural orbital coupled-cluster method
Bensberg, Moritz; Neugebauer, Johannes (2022)
The Journal of Chemical Physics
For the accurate computation of relative energies, domain-based local pair natural orbital coupled-cluster [DLPNO-CCSD(T-0)] has become increasingly popular. Even though DLPNO-CCSD(T-0) shows a formally linear scaling of the computational effort with the system size, accurate predictions of relative energies remain costly. Therefore, multi-level approaches are attractive that focus the available computational resources on a minor part of the molecular system, e.g., a reaction center, where changes in the correlation energy are expected to be the largest. We present a pair-selected multi-level DLPNO-CCSD(T-0) ansatz that automatically partitions the orbital pairs according to their contribution to the overall correlation energy change in a chemical reaction. To this end, the localized orbitals are mapped between structures in the reaction; all pair energies are approximated through computationally efficient semi-canonical second-order Moller-Plesser perturbation theory, and the orbital pairs for which the pair energies change significantly are identified. This multi-level approach is significantly more robust than our previously suggested, orbital selection-based multi-level DLPNO-CCSD(T-0) ansatz [M. Bensberg and J. Neugebauer, J. Chem. Phys. 155, 224102 (2021)] for reactions showing only small changes in the occupied orbitals. At the same time, it is even more efficient without added input complexity or accuracy loss compared to the full DLPNO-CCSD(T-0) calculation. We demonstrate the accuracy of the multi-level approach for a total of 128 chemical reactions and potential energy curves of weakly interacting complexes from the S66x8 benchmark set.
SCINE-Software for chemical interaction networks
Weymuth, Thomas; Unsleber, Jan Patrick; Türtscher, Paul Lorenz; et al. (2024)
The Journal of Chemical Physics
The software for chemical interaction networks (SCINE) project aims at pushing the frontier of quantum chemical calculations on molecular structures to a new level. While calculations on individual structures as well as on simple relations between them have become routine in chemistry, new developments have pushed the frontier in the field to high-throughput calculations. Chemical relations may be created by a search for specific molecular properties in a molecular design attempt, or they can be defined by a set of elementary reaction steps that form a chemical reaction network. The software modules of SCINE have been designed to facilitate such studies. The features of the modules are (i) general applicability of the applied methodologies ranging from electronic structure (no restriction to specific elements of the periodic table) to microkinetic modeling (with little restrictions on molecularity), full modularity so that SCINE modules can also be applied as stand-alone programs or be exchanged for external software packages that fulfill a similar purpose (to increase options for computational campaigns and to provide alternatives in case of tasks that are hard or impossible to accomplish with certain programs), (ii) high stability and autonomous operations so that control and steering by an operator are as easy as possible, and (iii) easy embedding into complex heterogeneous environments for molecular structures taken individually or in the context of a reaction network. A graphical user interface unites all modules and ensures interoperability. All components of the software have been made available as open source and free of charge.

Publications 1 - 10 of 13

Moritz Bensberg

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results