20 citations · 138 across the 26 of their papers we have counts for
26 papers
OrbGNN: A Wave function-based Machine Learning Interelectronic Representation
Brody Quebedeaux, Shahzad Akram, Markus Reiher +1
Machine learning interatomic potentials (MLIPs) have become emerging tools in molecular modeling and computational chemistry. By learning high-dimensional potential energy surfaces…
General Symmetry-Based Potential Energy Surface Grid Reduction in Normal Coordinates
Can Liao, Markus Reiher
The construction of a grid-based potential energy surface (PES) can be prohibitively expensive as the number of grid points grows exponentially with molecular size. Molecular symme…
Utility-scale quantum computational chemistry
Davide Castaldo, Markus Reiher
Chemistry and materials science are widely regarded as potential killer application fields for quantum hardware. While the dream of unlocking unprecedented simulation capabilities…
N-Mode Quantized Anharmonic Vibronic Hamiltonians for Matrix Product State Dynamics
Valentin Barandun, Nina Glaser, Markus Reiher
Theoretical predictions of photochemical processes are essential for interpreting and understanding spectral features. Reliable quantum dynamics calculations of vibronic systems re…
Efficient Implementation of the Spin-Free Renormalized Internally-Contracted Multireference Coupled Cluster Theory
Kalman Szenes, Riya Kayal, Kantharuban Sivalingam +3
In this paper, an efficient implementation of the renormalized internally-contracted multreference coupled cluster with singles and doubles (RIC-MRCCSD) into the ORCA quantum chemi…
Automated Exploration of Radical-Molecule Chemistry: The Case of Oxirane + CH in the ISM
Moritz Bensberg, Silvia Alessandrini, Mattia Melosso +2
Quantum chemistry provides accurate and reliable methods to investigate reaction pathways of reactive molecular systems relevant to the interstellar medium. However, the exhaustive…
Ground and excited-state energies with analytic errors and short time evolution on a quantum computer
Timothy Stroschein, Davide Castaldo, Markus Reiher
Accurately solving the Schrödinger equation remains a central challenge in computational physics, chemistry, and materials science. Here, we propose an alternative eigenvalue probl…
How to use quantum computers for biomolecular free energies
Jakob Günther, Thomas Weymuth, Moritz Bensberg +18
Free energy calculations are at the heart of physics-based analyses of biochemical processes. They allow us to quantify molecular recognition mechanisms, which determine a wide ran…
A Perspective on Quantum Computing Applications in Quantum Chemistry using 25--100 Logical Qubits
Yuri Alexeev, Victor S. Batista, Nicholas Bauman +27
The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owin…
QCMaquis 4.0: Multi-Purpose Electronic, Vibrational, and Vibronic Structure and Dynamics Calculations with the Density Matrix Renormalization Group
Kalman Szenes, Nina Glaser, Mihael Erakovic +6
QCMaquis is a quantum chemistry software package for general molecular structure calculations in a matrix product state/matrix product operator formalism of the density matrix reno…
phase2: Full-State Vector Simulation of Quantum Time Evolution at Scale
Marek Miller, Jakob Günther, Freek Witteveen +5
Classical simulation of quantum computers is essential for designing and benchmarking quantum algorithms. Here we present phase2, a full-state-vector simulator optimised for sequen…
Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations
Marco Eckhoff, Markus Reiher
Recent developments in computational chemistry facilitate the automated quantum chemical exploration of chemical reaction networks for the in-silico prediction of synthesis pathway…
Machine Learning Enhanced Calculation of Quantum-Classical Binding Free Energies
Moritz Bensberg, Marco Eckhoff, F. Emil Thomasen +10
Binding free energies are a key element in understanding and predicting the strength of protein--drug interactions. While classical free energy simulations yield good results for m…
Hierarchical quantum embedding by machine learning for large molecular assemblies
Moritz Bensberg, Marco Eckhoff, Raphael T. Husistein +9
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…
Classification of electronic structures and state preparation for quantum computation of reaction chemistry
Maximilian Mörchen, Guang Hao Low, Thomas Weymuth +3
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…
Multiscale Embedding for Quantum Computing
Leah P. Weisburn, Minsik Cho, Moritz Bensberg +3
We present a novel multi-scale embedding scheme that links conventional QM/MM embedding and bootstrap embedding (BE) to allow simulations of large chemical systems on limited quant…
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
Raphael T. Husistein, Markus Reiher, Marco Eckhoff
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 recogni…
Non-iterative Triples for Transcorrelated Coupled Cluster Theory
Maximilian Mörchen, Alberto Baiardi, Michał Lesiuk +1
We present an implementation of a perturbative triples correction for the coupled cluster ansatz including single and double excitations based on the transcorrelated Hamiltonian. T…
High ground state overlap via quantum embedding methods
Mihael Erakovic, Freek Witteveen, Dylan Harley +7
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. Fo…
Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks
Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber +6
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 complexit…
Vibrational Entanglement through the Lens of Quantum Information Measures
Nina Glaser, Alberto Baiardi, Annina Z. Lieberherr +1
We introduce a quantum information analysis of vibrational wave functions to understand complex vibrational spectra of molecules with strong anharmonic couplings and vibrational re…
Renormalized Internally-Contracted Multireference Coupled Cluster with Perturbative Triples
Robin Feldmann, Markus Reiher
In this work, we combine the many-body formulation of the internally contracted multireference coupled cluster (ic-MRCC) method with Evangelista's multireference formulation of the…
Striking the Right Balance of Encoding Electron Correlation in the Hamiltonian and the Wavefunction Ansatz
Kalman Szenes, Maximilian Moerchen, Paul Fischill +1
Multi-configurational electronic structure theory delivers the most versatile approximations to many-electron wavefunctions, flexible enough to deal with all sorts of transformatio…
SCINE -- Software for Chemical Interaction Networks
Thomas Weymuth, Jan P. Unsleber, Paul L. Tuertscher +11
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 calculati…