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We propose a quantum algorithm, inspired by ADAPT-VQE, to variationally prepare the ground state of a quantum Hamiltonian, with the desirable property that if it fails to find the ground state, it still yields a physically meaningful…

Quantum Physics · Physics 2025-05-16 Shuchen Zhu , Yu Tong

Adaptive quantum variational algorithms are particularly promising for simulating strongly correlated systems on near-term quantum hardware, but they are not yet viable due, in large part, to the severe coherence time limitations on current…

Variational quantum algorithms (VQAs) are considered as one of the most promising candidates for achieving quantum advantages on quantum devices in the noisy intermediate-scale quantum (NISQ) era. They have been developed for numerous…

Quantum Physics · Physics 2023-01-26 Qin Li , Junyu Quan , Jinjing Shi , Shichao Zhang , Xuelong Li

Recent practical approaches for the use of current generation noisy quantum devices in the simulation of quantum many-body problems have been dominated by the use of a variational quantum eigensolver (VQE). These coupled quantum-classical…

Quantum Physics · Physics 2021-09-15 Hongxiang Chen , Max Nusspickel , Jules Tilly , George H. Booth

The problem of finding the ground state energy of a Hamiltonian using a quantum computer is currently solved using either the quantum phase estimation (QPE) or variational quantum eigensolver (VQE) algorithms. For precision $\epsilon$, QPE…

Quantum Physics · Physics 2019-04-16 Daochen Wang , Oscar Higgott , Stephen Brierley

We propose a qubit efficient scheme to study ground state properties of quantum many-body systems on near-term noisy intermediate scale quantum computers. One can obtain a tensor network representation of the ground state using a number of…

Quantum Physics · Physics 2019-10-02 Jin-Guo Liu , Yi-Hong Zhang , Yuan Wan , Lei Wang

We propose a variational quantum algorithm for estimating microcanonical expectation values in models obeying the eigenstate thermalization hypothesis. Using a relaxed criterion for convergence of the variational optimization loop, the…

Quantum Physics · Physics 2023-10-16 Klée Pollock , Peter P. Orth , Thomas Iadecola

Quantum computational chemistry has emerged as an important application of quantum computing. Hybrid quantum-classical computing methods, such as variational quantum eigensolvers (VQE), have been designed as promising solutions to quantum…

We explore a pulse-based variational quantum eigensolver (VQE) algorithm for Rydberg atoms in optical tweezer arrays and evaluate its performance on prototypical quantum spin models. We numerically demonstrate that the ground states of the…

Quantum Physics · Physics 2025-07-28 Kazuma Nagao , Sergi Julià-Farré , Joseph Vovrosh , Alexandre Dauphin , Seiji Yunoki

Preparing thermal states on a quantum computer can have a variety of applications, from simulating many-body quantum systems to training machine learning models. Variational circuits have been proposed for this task on near-term quantum…

Quantum Physics · Physics 2021-11-09 Jonathan Foldager , Arthur Pesah , Lars Kai Hansen

Recent advances in quantum information and quantum science have inspired the development of various compact dynamic structured ans\"{a}tze that are expected to be realizable in the Noisy Intermediate-Scale Quantum (NISQ) devices. However,…

Quantum Physics · Physics 2024-03-18 Dipanjali Halder , Dibyendu Mondal , Rahul Maitra

The Variational Quantum Eigensolver (VQE) is a method of choice to solve the electronic structure problem for molecules on near-term gate-based quantum computers. However, the circuit depth is expected to grow significantly with problem…

Variational approaches, such as variational Monte Carlo (VMC) or the variational quantum eigensolver (VQE), are powerful techniques to tackle the ground-state many-electron problem. Often, the family of variational states is not invariant…

Quantum Physics · Physics 2023-10-10 Javier Robledo Moreno , Jeffrey Cohn , Dries Sels , Mario Motta

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…

This work studies the variational quantum eigensolver algorithm, designed to determine the ground state of a quantum mechanical system by combining classical and quantum hardware. Methods of reducing the number of required qubit…

Quantum Physics · Physics 2022-03-01 R. J. P. T. de Keijzer , V. E. Colussi , B. Škorić , S. J. J. M. F. Kokkelmans

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

Accurately describing strongly correlated electronic systems remains a central challenge in quantum chemistry, as electron-electron interactions give rise to complex many-body wavefunctions that are difficult to capture with conventional…

This thesis explores the application of the Symmetry-Breaking/Symmetry-Restoration methodology on quantum computers to better approximate a Hamiltonian's ground state energy within a variational framework in many-body physics. This involves…

Quantum Physics · Physics 2023-11-10 Andres Ruiz

Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term…

Quantum Physics · Physics 2024-10-18 Ioannis Kolotouros , Ioannis Petrongonas , Miloš Prokop , Petros Wallden

We present a variational quantum thermalizer (VQT), called quantum-VQT (qVQT), which extends the variational quantum eigensolver (VQE) to finite temperatures. The qVQT makes use of an intermediate measurement between two variational…

Quantum Physics · Physics 2024-06-05 Johannes Selisko , Maximilian Amsler , Thomas Hammerschmidt , Ralf Drautz , Thomas Eckl