English
Related papers

Related papers: Computation of molecular excited states on IBM qua…

200 papers

Quantum computing opens up new possibilities for the simulation of many-body nuclear systems. As the number of particles in a many-body system increases, the size of the space if the associated Hamiltonian increases exponentially. This…

Quantum Physics · Physics 2022-09-19 Isaac Hobday , Paul Stevenson , James Benstead

The variational quantum eigensolver (VQE) is one of the most promising algorithms for low-lying eigenstates calculation on Noisy Intermediate-Scale Quantum (NISQ) computers. Specifically, VQE has achieved great success for ground state…

Numerical Analysis · Mathematics 2025-12-19 Hengzhun Chen , Yingzhou Li , Bichen Lu , Jianfeng Lu

The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited state energy of quantum many-body systems. A key component of the algorithm and an active research area is the construction of a parametrized trial…

The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver (VQE) algorithm aims to prepare the ground state of a…

Quantum Physics · Physics 2022-12-16 Nikita Astrakhantsev , Guglielmo Mazzola , Ivano Tavernelli , Giuseppe Carleo

Quantum computing brings a promise of new approaches into computational quantum chemistry. While universal, fault-tolerant quantum computers are still not available, we want to utilize today's noisy quantum processors. One of their flagship…

Finding the ground-state energy of molecules is an important and challenging computational problem for which quantum computing can potentially find efficient solutions. The variational quantum eigensolver (VQE) is a quantum algorithm that…

Quantum Physics · Physics 2023-02-15 Daniel Yoffe , Amir Natan , Adi Makmal

Variational quantum eigensolver(VQE) typically minimizes energy with hybrid quantum-classical optimization, which aims to find the ground state. Here, we propose a VQE by minimizing energy variance, which is called as variance-VQE(VVQE).…

Quantum Physics · Physics 2020-06-30 Dan-Bo Zhang , Zhan-Hao Yuan , Tao Yin

The computation of molecular excitation energies is essential for predicting photo-induced reactions of chemical and technological interest. While the classical computing resources needed for this task scale poorly, quantum algorithms…

Quantum computers have the potential to deliver speed-ups for solving certain important problems that are intractable for classical counterparts, making them a promising avenue for advancing modern computation. However, many quantum…

Quantum Physics · Physics 2025-12-23 Kang-Min Hu , Min Namkung , Hyang-Tag Lim

Calculating excited states in chemistry is crucial to provide insight into photoinduced molecular behavior beyond the ground state, enabling innovations in spectroscopy, material sciences, and drug design. While several approaches have been…

Quantum Physics · Physics 2025-10-14 Akilan Rajamani , Martin Beseda , Benjamin Lasorne , Bruno Senjean

Within the evolving domain of quantum computational chemistry, the Variational Quantum Eigensolver (VQE) has been developed to explore not only the ground state but also the excited states of molecules. In this study, we compare the…

Quantum Physics · Physics 2024-06-18 I-Chi Chen , Nouhaila Innan , Suman Kumar Roy , Jason Saroni

Quantum computing has emerged as a promising technology for solving problems that are intractable for classical computers. In this study, we introduce quantum computing and implement the Variational Quantum Eigensolver (VQE) algorithm using…

Quantum Physics · Physics 2023-05-12 Maomin Qing , Wei Xie

The Variational Quantum Eigensolver (VQE) algorithm has been developed to target near term Noisy Intermediate Scale Quantum (NISQ) computers as a method to find the eigenvalues of Hamiltonians. Unlike fully quantum algorithms such as…

Quantum Physics · Physics 2026-02-13 Taylor Harville , Rishu Khurana , Vitor F. Grizzi , Cong Liu

Variational quantum algorithms aim at harnessing the power of noisy intermediate-scale quantum computers, by using a classical optimizer to train a parameterized quantum circuit to solve tractable quantum problems. The variational quantum…

The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-classical computational approach to find eigenvalues and eigenvalues of a Hamiltonian. VQE has been proposed as an alternative to fully quantum algorithms such…

Quantum Physics · Physics 2021-09-01 Dmitry A. Fedorov , Bo Peng , Niranjan Govind , Yuri Alexeev

Calculating the energy spectrum of a quantum system is an important task, for example to analyse reaction rates in drug discovery and catalysis. There has been significant progress in developing algorithms to calculate the ground state…

Quantum Physics · Physics 2019-06-12 Suguru Endo , Tyson Jones , Sam McArdle , Xiao Yuan , Simon Benjamin

Excited states of molecules lie in the heart of photochemistry and chemical reactions. The recent development in quantum computational chemistry leads to inventions of a variety of algorithms that calculate the excited states of molecules…

Quantum Physics · Physics 2020-11-05 Hiroki Kawai , Yuya O. Nakagawa

The computation of excited electronic states is an important application for quantum computers. In this work, we simulate the excited state spectra of four aromatic heterocycles on IBM superconducting quantum computers, focusing on active…

Quantum Physics · Physics 2023-09-19 Maria A. Castellanos , Mario Motta , Julia E. Rice

This paper presents a hybrid quantum-classical approach to prime factorization. The proposed algorithm is based on the Variational Quantum Eigensolver (VQE), which employs a classical optimizer to find the ground state of a given…

Quantum Physics · Physics 2025-03-21 Mona Sobhani , Yahui Chai , Tobias Hartung , Karl Jansen

Harnessing the full power of nascent quantum processors requires the efficient management of a limited number of quantum bits with finite lifetime. Hybrid algorithms leveraging classical resources have demonstrated promising initial results…