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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…

Quantum chemistry is envisioned as an early and disruptive application for quantum computers. Yet, closer scrutiny of the proposed algorithms shows that there are considerable difficulties along the way. Here, we propose two criteria for…

Quantum Physics · Physics 2026-04-09 Thibaud Louvet , Thomas Ayral , Xavier Waintal

Quantum-classical hybrid algorithms are emerging as promising candidates for near-term practical applications of quantum information processors in a wide variety of fields ranging from chemistry to physics and materials science. We report…

In this work, we present the integration of Qiskit Nature's quantum chemistry solvers into the Atomic Simulation Environment (ASE), enabling hybrid quantum-classical workflows for force-driven atomistic simulations. This coupling allows the…

Quantum Physics · Physics 2026-02-04 Wilke Dononelli

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

Quantum computers have the potential to transform the ways in which we tackle some important problems. The efforts by companies like Google, IBM and Microsoft to construct quantum computers have been making headlines for years. Equally…

Quantum Physics · Physics 2018-12-05 Raffaele Miceli , Michael McGuigan

The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There…

Quantum Physics · Physics 2023-03-22 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

It is exponentially hard to simulate quantum systems by classical algorithms, while quantum computer could in principle solve this problem polynomially. We demonstrate such an quantum-simulation algorithm on our NMR system to simulate an…

Quantum Physics · Physics 2009-07-22 Jiangfeng Du , Nanyang Xu , Xinhua Peng , Pengfei Wang , Sanfeng Wu , Dawei Lu

The development of quantum algorithms to solve quantum chemistry problems has offered a promising new paradigm of performing computer simulations at the scale of atoms and molecules. Although majority of the research so far has focused on…

Quantum Physics · Physics 2022-09-29 Nirmal M R , Shampa Sarkar , Manoj Nambiar

Classical simulation of molecular systems is limited by exponential scaling, a hurdle quantum algorithms like Variational Quantum Eigensolvers (VQEs) aim to overcome. Although ADAPT-VQE enhances VQEs by dynamically building ans\"atze, it…

Quantum Physics · Physics 2025-06-23 Tatiana A. Bespalova , Oumaya Ladhari , Guido Masella

Variational quantum eigensolver (VQE) is an efficient computational method promising chemical accuracy in electronic structure calculations on a universal-gate quantum computer. However, such a simple task as computing the electronic energy…

Chemical Physics · Physics 2018-06-04 Ilya G. Ryabinkin , Scott N. Genin , Artur F. Izmaylov

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

Reflecting the increasing interest in quantum computing, the variational quantum eigensolver (VQE) has attracted much attentions as a possible application of near-term quantum computers. Although the VQE has often been applied to quantum…

Quantum Physics · Physics 2022-12-07 Yasutaka Nishida , Fumihiko Aiga

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is…

Quantum Physics · Physics 2021-06-29 Daniel Claudino , Jerimiah Wright , Alexander J. McCaskey , Travis S. Humble

Quantum mechanics has introduced a new theoretical framework for the study of molecules, enabling the prediction of properties and dynamics through the solution of the Schr\"odinger equation applied to these systems. However, solving this…

We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a massively parallel universal quantum computer…

Quantum Physics · Physics 2022-06-20 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

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 Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a quantum computer to simulate electronic structures with high…

The variational quantum eigensolver (VQE) algorithm combines the ability of quantum computers to efficiently compute expectation values with a classical optimization routine in order to approximate ground state energies of quantum systems.…

The variational quantum eigensolver (VQE), a type of variational quantum algorithm, is a hybrid quantum-classical algorithm to find the lowest-energy eigenstate of a particular Hamiltonian. We investigate ways to optimize the VQE solving…

Quantum Physics · Physics 2024-10-30 Adam Hutchings , Eric Yarnot , Xinpeng Li , Qiang Guan , Ning Xie , Shuai Xu , Vipin Chaudhary