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A programmable quantum device that has a large number of qubits without fault-tolerance has emerged recently. Variational Quantum Eigensolver (VQE) is one of the most promising ways to utilize the computational power of such devices to…

We develop an extension of the variational quantum eigensolver (VQE) algorithm - multistate, contracted VQE (MC-VQE) - that allows for the efficient computation of the transition energies between the ground state and several low-lying…

Quantum Physics · Physics 2019-06-19 Robert M. Parrish , Edward G. Hohenstein , Peter L. McMahon , Todd J. Martinez

The realization of quantum advantage with noisy-intermediate-scale quantum (NISQ) machines has become one of the major challenges in computational sciences. Maintaining coherence of a physical system with more than ten qubits is a critical…

The weighted subspace-search variational quantum eigensolver (SSVQE) is a prominent algorithm for calculating excited-state properties of molecular quantum systems. In this work, we elaborate on some of its fundamental features with the aim…

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm for computing ground state energies of molecular systems. We implement VQE to calculate the potential energy surface of the hydrogen molecule (H$_2$) across…

Quantum Physics · Physics 2026-01-16 Rylan Malarchick , Ashton Steed

Variational quantum eigensolvers (VQE) are among the most promising approaches for solving electronic structure problems on near-term quantum computers. A critical challenge for VQE in practice is that one needs to strike a balance between…

Variational quantum eigensolver (VQE) is a promising algorithm suitable for near-term quantum machines. VQE aims to approximate the lowest eigenvalue of an exponentially sized matrix in polynomial time. It minimizes quantum resource…

The variational quantum eigensolver (VQE) remains one of the most popular near-term quantum algorithms for solving the electronic structure problem. Yet, for its practicality, the main challenge to overcome is improving the quantum…

Quantum Physics · Physics 2023-05-11 Seonghoon Choi , Artur F. Izmaylov

Variational-Quantum-Eigensolver(VQE) method on a quantum computer is a well-known hybrid algorithm to solve the eigenstates and eigenvalues that uses both quantum and classical computers. This method has the potential to solve quantum…

Quantum Physics · Physics 2021-10-15 Hikaru Wakaura , Takao Tomono , Shoya Yasuda

Unitary Coupled Cluster (UCC) approaches are an appealing route to utilising quantum hardware to perform quantum chemistry calculations, as quantum computers can in principle perform UCC calculations in a polynomially scaling fashion, as…

Quantum Physics · Physics 2022-06-15 Maria-Andreea Filip , Nathan Fitzpatrick , David Muñoz Ramo , Alex J. W. Thom

In quantum chemistry, the variational quantum eigensolver (VQE) is a promising algorithm for molecular simulations on near-term quantum computers. However, VQEs using hardware-efficient circuits face scaling challenges due to the barren…

Quantum Physics · Physics 2024-09-27 Rui Mao , Guojing Tian , Xiaoming Sun

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore…

Quantum Physics · Physics 2022-02-17 Feng Zhang , Niladri Gomes , Yongxin Yao , Peter P. Orth , Thomas Iadecola

The cascaded variational quantum eigensolver (CVQE) circumvents the need for iterative communication between the quantum and classical processing units that is necessary in the conventional VQE algorithm. While CVQE offers complete freedom…

Quantum Physics · Physics 2026-05-04 Yi-Hua Lai , John P. T. Stenger , Gloria Bazargan , Igor V. Schweigert , Daniel Gunlycke

The Variational Quantum Algorithms (VQAs) are hybrid quantum-classical algorithms and they can be used in the Nosiy Intermadiate Scale Quantum (NISQ) devises. The Variational Quantum Eigensolver (VQE) was suggested as a first VQA. VQE is…

Quantum Physics · Physics 2026-03-09 Murat Kurt , Ayda Kaltehei , Selçuk Çakmak , Azmi Gençten

Quantum chemistry is one of the most promising applications of quantum computers in the near future. For noisy intermediate-scale quantum devices, the quantum-classical hybrid framework based on the variational quantum eigensolver (VQE) has…

The Variational Quantum Eigensolver (VQE) is one the most perspective algorithms for simulation of quantum many body physics that have recently attached a lot of attention and believed would be practical for implementation on the near term…

Quantum Physics · Physics 2021-05-03 Belozerova Polina , Shangareev Arthur , Zotov Yuriy , Yung Manhong , lv Dingshun

We propose a momentum-space based variational quantum eigensolver (VQE) framework for simulating quasiparticle excitations in interacting quantum many-body systems on near-term quantum devices. Leveraging translational invariance and other…

Strongly Correlated Electrons · Physics 2025-11-24 Saavanth Velury , Yuxuan Wang

The accurate prediction and understanding of molecular energy and chemical reactivity are fundamental pursuits in the field of molecular quantum chemistry. With the limitations of the current noisy intermediate scale quantum computer (NISQ)…

Chemical Physics · Physics 2023-04-04 Abdul Kalam , Ashok Kumar , Prasanta K. Panigrahi

Variational Quantum Eigensolver (VQE) is a hybrid algorithm for finding the minimum eigenvalue/vector of a given Hamiltonian by optimizing a parametrized quantum circuit (PQC) using a classical computer. Sequential optimization methods,…

Quantum Physics · Physics 2024-05-17 Katsuhiro Endo , Yuki Sato , Rudy Raymond , Kaito Wada , Naoki Yamamoto , Hiroshi C. Watanabe

The variational quantum eigensolver (VQE) is an attracting possible application of near-term quantum computers. Originally, the aim of the VQE is to find a ground state for a given specific Hamiltonian. It is achieved by minimizing the…

Quantum Physics · Physics 2019-04-30 Kosuke Mitarai , Tennin Yan , Keisuke Fujii