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Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute power than any classical system. It offers new means of studying the…

Quantum Physics · Physics 2026-01-23 Maja Franz , Lukas Schmidbauer , Joshua Ammermann , Ina Schaefer , Wolfgang Mauerer

Ab initio methods for electronic structure of molecules have reached a satisfactory accuracy for calculation of static properties, but remain too expensive for quantum dynamical calculations. We propose an efficient semiclassical method for…

Chemical Physics · Physics 2015-05-13 Baiqing Li , Cesare Mollica , Jiri Vanicek

The ability to perform ab initio molecular dynamics simulations using potential energies calculated on quantum computers would allow virtually exact dynamics for chemical and biochemical systems, with substantial impacts on the fields of…

Quantum Mechanics/Molecular Mechanics (QM/MM) simulations are a popular approach to study various features of large systems. A common application of QM/MM calculations is in the investigation of reaction mechanisms in condensed-phase and…

Chemical Physics · Physics 2020-10-29 Jorge Nochebuena , Sehr Naseem-Khan , G. Andrés Cisneros

Quantum-classical Hybrid Machine Learning (QHML) models are recognized for their robust performance and high generalization ability even for relatively small datasets. These qualities offer unique advantages for anti-cancer drug response…

Machine Learning · Computer Science 2025-05-16 Takafumi Ito , Lysenko Artem , Tatsuhiko Tsunoda

Quantum computing enables parallelism through superposition and entanglement and offers advantages over classical computing architectures. However, due to the limitations of current quantum hardware in the noisy intermediate-scale quantum…

Quantum Physics · Physics 2025-09-09 Guolong Zhong , Yi Fan , Zhenyu Li

Quantum machine learning algorithms are expected to play a pivotal role in quantum chemistry simulations in the immediate future. One such key application is the training of a quantum neural network to learn the potential energy surface and…

Quantum Physics · Physics 2024-09-04 Gabriele Lo Monaco , Marco Bertini , Salvatore Lorenzo , G. Massimo Palma

Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations --- alongside impressive results using machine learning techniques for computation --- hybridizing…

Quantum Physics · Physics 2018-10-24 Rongxin Xia , Sabre Kais

Accurate modelling of electrostatic interactions and charge transfer is fundamental to computational chemistry, yet most machine learning interatomic potentials (MLIPs) rely on local atomic descriptors that cannot capture long-range…

We present a computational platform for modeling chemical reactions in complex molecular environments, focused on ligand-protein binding in drug discovery. The platform implements our new quantum-in-quantum-in-classical (QM/QM/MM)…

Quantum mechanical methods have been devised for the elucidation and clarification of reaction paths of chemical processes over decades. While they are typically deployed in routine calculations on systems for which some insights have…

The complexity of biological systems, governed by molecular interactions across hierarchical scales, presents a challenge for computational modeling. While advances in multiomic profiling have enabled precise measurements of biological…

Quantum Physics · Physics 2025-06-18 Michael Kubal , Sonika Johri

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 range of biological phenomena from how cells send and receive…

The design of electrically driven quantum dot devices for quantum optical applications asks for modeling approaches combining classical device physics with quantum mechanics. We connect the well-established fields of semi-classical…

Mesoscale and Nanoscale Physics · Physics 2017-11-06 Markus Kantner , Markus Mittnenzweig , Thomas Koprucki

Modern computational chemistry has reached a stage at which massive exploration into chemical reaction space with unprecedented resolution with respect to the number of potentially relevant molecular structures has become possible. Various…

Chemical Physics · Physics 2020-04-27 Jan P. Unsleber , Markus Reiher

This study develops an algorithm to reproduce reaction route maps (RRMs) in shape space from the outputs of potential search algorithms. To demonstrate this, GRRM is utilized as a potential search algorithm but the proposed algorithm should…

Quantum simulation, the simulation of quantum processes on quantum computers, suggests a path forward for the efficient simulation of problems in condensed-matter physics, quantum chemistry, and materials science. While the majority of…

Quantum Physics · Physics 2022-10-03 Paul K. Faehrmann , Mark Steudtner , Richard Kueng , Maria Kieferova , Jens Eisert

It is demonstrated that the reaction path for a polyatomic molecule (applied to the HCO molecule) is easily calculated via ab-initio configuration interaction (CI) total energies. This Hamiltonian not only reproduces the CI calculations…

Chemical Physics · Physics 2007-05-23 N. C. Bacalis , A. Metropoulos , D. A. Papaconstantopoulos

We report recent progress in computer simulations of quantum systems described in the path-integral formulation. For the example of the $\phi^4$ quantum chain we show that the accuracy of the simulation may greatly be enhanced by a…

Condensed Matter · Physics 2007-05-23 Wolfhard Janke , Tilman Sauer

Electronic structure simulation is an anticipated application for quantum computers. Due to high-dimensional quantum entanglement in strongly correlated systems, the quantum resources required to perform such simulations are far beyond the…

Quantum Physics · Physics 2022-01-25 Jie Liu , Zhenyu Li , Jinlong Yang