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Variational quantum eigensolvers (VQEs) represent a powerful class of hybrid quantum-classical algorithms for computing molecular energies. Various numerical issues exist for these methods, however, including barren plateaus and large…

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…

Finding the ground state of a Hamiltonian system is of great significance in many-body quantum physics and quantum chemistry. We propose an improved iterative quantum algorithm to prepare the ground state of a Hamiltonian. The crucial point…

Quantum Physics · Physics 2022-10-25 Jin-Min Liang , Qiao-Qiao Lv , Shu-Qian Shen , Ming Li , Zhi-Xi Wang , Shao-Ming Fei

The vacuum of the lattice Schwinger model is prepared on up to 100 qubits of IBM's Eagle-processor quantum computers. A new algorithm to prepare the ground state of a gapped translationally-invariant system on a quantum computer is…

Quantum Physics · Physics 2024-04-23 Roland C. Farrell , Marc Illa , Anthony N. Ciavarella , Martin J. Savage

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one…

Quantum Physics · Physics 2023-09-28 James B. Larsen , Matthew D. Grace , Andrew D. Baczewski , Alicia B. Magann

The variational quantum eigensolver is one of the most promising approaches for performing chemistry simulations using noisy intermediate-scale quantum (NISQ) processors. The efficiency of this algorithm depends crucially on the ability to…

A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding is that achieving quantum advantage in this area will…

Quantum Physics · Physics 2023-11-08 Guoming Wang , Daniel Stilck França , Ruizhe Zhang , Shuchen Zhu , Peter D. Johnson

Quantum algorithms require accurate representations of electronic states on a quantum device, yet the approximation of electronic wave functions for strongly correlated systems remains a profound theoretical challenge, with existing methods…

Quantum Physics · Physics 2025-04-29 Dipanjali Halder , Dibyendu Mondal , Rahul Maitra

Approximating the ground states of strongly interacting electron systems in quantum chemistry and condensed matter physics is expected to be one of the earliest applications of quantum computers. In this paper, we prepare highly accurate…

Quantum Physics · Physics 2022-11-09 Gaurav Gyawali , Michael J. Lawler

In recent years, Variational Quantum Algorithms (VQAs) have emerged as a promising approach for solving optimization problems on quantum computers in the NISQ era. However, one limitation of VQAs is their reliance on fixed-structure…

Quantum Physics · Physics 2026-03-03 Gloria Turati , Maurizio Ferrari Dacrema , Paolo Cremonesi

We propose a method for constructing $\texttt{PREPARE}$ circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of quantum circuits solely on classical computers. The…

Quantum Physics · Physics 2025-05-02 Hayata Morisaki , Kosuke Mitarai , Keisuke Fujii , Yuya O. Nakagawa

Quantum simulation of chemical systems is one of the most promising near-term applications of quantum computers. The variational quantum eigensolver, a leading algorithm for molecular simulations on quantum hardware, has a serious…

Quantum Physics · Physics 2019-07-16 Harper R. Grimsley , Sophia E. Economou , Edwin Barnes , Nicholas J. Mayhall

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.…

A novel class of hybrid quantum-classical algorithms based on the variational approach have recently emerged from separate proposals addressing, for example, quantum chemistry and combinatorial problems. These algorithms provide an…

Quantum Physics · Physics 2017-01-09 Gian Giacomo Guerreschi , Mikhail Smelyanskiy

Preparing the ground state of a Hamiltonian is a problem of great significance in physics with deep implications in the field of combinatorial optimization. The adiabatic algorithm is known to return the ground state for sufficiently long…

Quantum Physics · Physics 2023-08-02 Benjamin F. Schiffer , Jordi Tura , J. Ignacio Cirac

Variational quantum circuits characterise the state of a quantum system through the use of parameters that are optimised using classical optimisation procedures that typically rely on gradient information. The circuit-execution complexity…

Quantum Physics · Physics 2023-07-28 Sayantan Pramanik , Chaitanya Murti , M Girish Chandra

We consider the question of how correlated the system hardness is between classical algorithms of electronic structure theory in ground state estimation and quantum algorithms. To define the system hardness for classical algorithms we…

We propose a modification of the Variational Quantum Eigensolver algorithm for electronic structure optimization using quantum computers, named non-unitary Variational Quantum Eigensolver (nu-VQE), in which a non-unitary operator is…

We propose a scheme to restore spatial symmetry of Hamiltonian in the variational-quantum-eigensolver (VQE) algorithm for which the quantum circuit structures used usually break the Hamiltonian symmetry. The symmetry-adapted VQE scheme…

Quantum Physics · Physics 2020-06-01 Kazuhiro Seki , Tomonori Shirakawa , Seiji Yunoki

We present a comparative study of two implementations of a variational quantum algorithm aimed at minimizing the energy of a complex quantum system. In one implementation, we extract the information of the energy gradient by projective…

Quantum Physics · Physics 2025-04-01 Dario Melegari , Rabia Abdul Razaq , Giovanni Minuto , Paolo Solinas