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Generalized Ising models, also known as cluster expansions, are an important tool in many areas of condensed-matter physics and materials science, as they are often used in the study of lattice thermodynamics, solid-solid phase transitions,…

Statistical Mechanics · Physics 2016-06-27 Wenxuan Huang , Daniil Kitchaev , Stephen Dacek , Ziqin Rong , Zhiwei Ding , Gerbrand Ceder

The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of…

Quantum computing offers transformative potential for simulating real-world materials, providing a powerful platform to investigate complex quantum systems across quantum chemistry and condensed matter physics. In this work, we leverage…

Quantum Physics · Physics 2025-09-08 Mohammad Mirzakhani , Kyungsun Moon

Ground State Energy Estimation (GSEE) is a central problem in quantum chemistry and condensed matter physics, demanding efficient algorithms to solve complex electronic structure calculations. This work introduces a structured benchmarking…

The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenvalues and eigenvectors of a given Hamiltonian on noisy intermediate-scale quantum (NISQ) devices. A particular application is to obtain ground…

Establishing the nature of the ground state of the Heisenberg antiferromagnet (HAFM) on the kagome lattice is well known to be a prohibitively difficult problem for classical computers. Here, we give a detailed proposal for a Variational…

Quantum Physics · Physics 2022-12-26 Joris Kattemölle , Jasper van Wezel

We study design challenges associated with realizing a ground state quantum computer. In such a computer, the energy gap between the ground state and first excited state must be sufficiently large to prevent disruptive excitations. Here, an…

Quantum Physics · Physics 2007-05-23 Ari Mizel , M. W. Mitchell , Marvin L. Cohen

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.…

We estimate the resource requirements for the quantum simulation of the ground state energy of the one dimensional quantum transverse Ising model (TIM), based on the surface code implementation of a fault tolerant quantum computer. The…

Quantum Physics · Physics 2013-04-02 Hao You , Michael R. Geller , P. C. Stancil

Determining ground state energies of quantum systems by hybrid classical/quantum methods has emerged as a promising candidate application for near-term quantum computational resources. Short of large-scale fault-tolerant quantum computers,…

Quantum Physics · Physics 2016-10-25 Nicholas C. Rubin

Quantum Computing allows, in principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register, offering a promising solution to overcome the limitations of traditional quantum chemistry…

Quantum Physics · Physics 2025-10-21 C. Feniou , O. Adjoua , B. Claudon , J. Zylberman , E. Giner , J. -P. Piquemal

We present a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian by proposing an adaptive construction of a quantum state for the quantum-selected configuration interaction…

Quantum Physics · Physics 2024-12-12 Yuya O. Nakagawa , Masahiko Kamoshita , Wataru Mizukami , Shotaro Sudo , Yu-ya Ohnishi

We present the results of the quantum calculation of the ground state energies and magnetic g-factors of two rare earth (RE) ions: Yb3+ in Y2Ti2O7 crystal and Er3+ in YPO4 crystal. The Variational Quantum Eigensolver (VQE) algorithm has…

Mesoscale and Nanoscale Physics · Physics 2021-01-18 K. M. Makushin , E. I. Baibekov

As a means to solve optimization problems using quantum computers, the problem is typically recast into a Ising spin model whose ground-state is the solution of the optimization problem. An alternative to the Ising formulation is the…

Quantum Physics · Physics 2021-09-22 Martin Lanthaler , Wolfgang Lechner

The Variational Quantum Eigensolver (VQE) is a promising algorithm for quantum computing applications in chemistry and materials science, particularly in addressing the limitations of classical methods for complex systems. This study…

Quantum Physics · Physics 2025-02-25 Nia Pollard , Kamal Choudhary

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

The negative hydrogen ion is the first three body quantum problem whose ground state energy is calculated using the `Chandrasekhar Wavefunction' that accounts for the electron-electron correlation. Solving multi-body systems is a daunting…

Quantum Physics · Physics 2019-05-31 Shubham Kumar , Rahul Pratap Singh , Bikash K. Behera , Prasanta K. Panigrahi

The recently developed Projective Quantum Eigensolver (PQE) has been demonstrated as an elegant methodology to compute the ground state energy of molecular systems in Noisy Intermdiate Scale Quantum (NISQ) devices. The iterative…

Quantum Physics · Physics 2023-03-21 Sonaldeep Halder , Chayan Patra , Dibyendu Mondal , Rahul Maitra

Computing ground-state properties of molecules is a promising application for quantum computers operating in concert with classical high-performance computing resources. Quantum embedding methods are a family of algorithms particularly…

Finding the ground state energy and wavefunction of a quantum many-body system is a key problem in quantum physics and chemistry. We study this problem for the long-range XY model by using the variational quantum eigensolver (VQE)…

Quantum Physics · Physics 2022-08-03 Jia-Bin You , Dax Enshan Koh , Jian Feng Kong , Wen-Jun Ding , Ching Eng Png , Lin Wu