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Quantum chemistry and materials science are among the most promising areas for demonstrating algorithmic quantum advantage and quantum utility due to their inherent quantum mechanical nature. Still, large-scale simulations of quantum…

Achieving high-performance computation on quantum systems presents a formidable challenge that necessitates bridging the capabilities between quantum hardware and classical computing resources. This study introduces an innovative…

Quantum Physics · Physics 2024-03-19 Kuan-Cheng Chen , Xiaoren Li , Xiaotian Xu , Yun-Yuan Wang , Chen-Yu Liu

Quantum computers hold promise to enable efficient simulations of the properties of molecules and materials; however, at present they only permit ab initio calculations of a few atoms, due to a limited number of qubits. In order to harness…

Materials Science · Physics 2020-07-07 He Ma , Marco Govoni , Giulia Galli

Quantum computation is a promising emerging technology which, compared to conventional computation, allows for substantial speed-ups e.g. for integer factorization or database search. However, since physical realizations of quantum…

Quantum Physics · Physics 2018-06-07 Alwin Zulehner , Robert Wille

The variational quantum eigensolver (VQE) is a promising algorithm for demonstrating quantum advantage in the noisy intermediate-scale quantum (NISQ) era. However, optimizing VQE from random initial starting parameters is challenging due to…

Quantum Physics · Physics 2023-10-20 Abid Khan , Bryan K. Clark , Norm M. Tubman

Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The Variational Quantum Eigensolver (VQE) treats the case when the matrix is a Hamiltonian. Here, we…

Quantum Physics · Physics 2022-09-28 M. Cerezo , Kunal Sharma , Andrew Arrasmith , Patrick J. Coles

Ab initio wavefunction methods provide accurate molecular simulations but their computational scaling restricts applications to small systems. We develop a workflow combining quantum embedding to decompose a molecule into fragments with a…

Quantum computers are expected to be highly beneficial for chemistry simulations, promising significant improvements in accuracy and speed. The most prominent algorithm for chemistry simulations on NISQ devices is the Variational Quantum…

Quantum Physics · Physics 2022-09-27 Marita Oliv , Andrea Matic , Thomas Messerer , Jeanette Miriam Lorenz

Mapping out phase diagrams of quantum systems using classical simulations can be challenging or intractable due to the computational resources required to simulate even small quantum systems far away from the thermodynamic limit. We…

Quantum Physics · Physics 2024-06-05 Jan Lukas Bosse , Raul Santos , Ashley Montanaro

A novel parallel hybrid quantum-classical algorithm for the solution of the quantum-chemical ground-state energy problem on gate-based quantum computers is presented. This approach is based on the reduced density-matrix functional theory…

It is imperative that useful quantum computers be very difficult to simulate classically; otherwise classical computers could be used for the applications envisioned for the quantum ones. Perfect quantum computers are unarguably…

Quantum Physics · Physics 2020-11-26 Yiqing Zhou , E. Miles Stoudenmire , Xavier Waintal

A universal quantum computer can simulate diverse quantum systems, with electronic structure for chemistry offering challenging problems for practical use cases around the hundred-qubit mark. While current quantum processors have reached…

Solving quantum many-body problems is one of the fundamental challenges in quantum chemistry. While neural network quantum states (NQS) have emerged as a promising computational tool, its training process incurs exponentially growing…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-01 Hongtao Xu , Zibo Wu , Mingzhen Li , Weile Jia

Variational quantum eigensolvers (VQEs) are successful algorithms for studying physical systems on quantum computers. Recently, they were extended to the measurement-based model of quantum computing, bringing resource graph states and their…

Quantum Physics · Physics 2024-06-27 Albie Chan , Zheng Shi , Luca Dellantonio , Wolfgang Dür , Christine A. Muschik

Semi-empirical quantum chemical approaches are known to compromise accuracy for feasibility of calculations on huge molecules. However, the need for ultrafast calculations in interactive quantum mechanical studies, high-throughput virtual…

Chemical Physics · Physics 2023-04-12 Francesco Bosia , Peikun Zheng , Alain Vaucher , Thomas Weymuth , Pavlo O. Dral , Markus Reiher

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent…

Quantum Physics · Physics 2024-01-17 Tao Jiang , John Rogers , Marius S. Frank , Ove Christiansen , Yong-Xin Yao , Nicola Lanatà

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource…

Computing the electronic structure of molecules with high precision is a central challenge in the field of quantum chemistry. Despite the enormous success of approximate methods, tackling this problem exactly with conventional computers is…

Quantum Physics · Physics 2020-10-20 J. Argüello-Luengo , A. González-Tudela , T. Shi , P. Zoller , J. I. Cirac

Quantum hardware has the potential to efficiently solve computationally difficult problems in physics and chemistry to reap enormous practical rewards. Analogue quantum simulation accomplishes this by using the dynamics of a controlled…

Even a minor boost in solving combinatorial optimization problems can greatly benefit multiple industries. Quantum computers, with their unique information processing capabilities, hold promise for delivering such enhancements. The…

Quantum Physics · Physics 2025-05-15 Gabriel Marin-Sanchez , David Amaro
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