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In this paper, we explore (2+1)D quantum electrodynamics (QED) at finite density on a quantum computer, including two fermion flavors. Our method employs an efficient gauge-invariant ansatz together with a quantum circuit structure that…

High Energy Physics - Lattice · Physics 2025-09-26 Emil Otis Rosanowski , Arianna Crippa , Lena Funcke , Paulo Vitor Itaborai , Karl Jansen , Simran Singh

Quantum harmonic oscillators, or qumodes, provide a promising and versatile framework for quantum computing. Unlike qubits, which are limited to two discrete levels, qumodes have an infinite-dimensional Hilbert space, making them…

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized…

Quantum Physics · Physics 2025-03-27 Muqing Zheng , Bo Peng , Ang Li , Xiu Yang , Karol Kowalski

A multiscale approach was adopted for the calculation of confined states in self-assembled semiconductor quantum dots (QDs). While results close to experimental data have been obtained with a combination of atomistic strain and…

Mesoscale and Nanoscale Physics · Physics 2014-09-16 Parijat Sengupta , Sunhee Lee , Sebastian Steiger , Hoon Ryu , Gerhard Klimeck

Quantum state tomography is an essential component of modern quantum technology. In application to continuous-variable harmonic-oscilator systems, such as the electromagnetic field, existing tomography methods typically reconstruct the…

Quantum Physics · Physics 2023-01-09 Ekaterina Fedotova , Nikolai Kuznetsov , Egor Tiunov , A. E. Ulanov , A. I. Lvovsky

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 hybrid quantum-classical eigensolver to address the computational challenges of simulating strongly correlated quantum many-body systems, where the exponential growth of the Hilbert space and extensive entanglement render…

Quantum Physics · Physics 2025-10-23 Lei Xu , Ling Wang

We describe a semidefinite relaxation method which finds lower bounds to the ground state energy of a quantum Hamiltonian subject to Hermitian linear constraints along with approximations of ground state expectation values. We show that…

Strongly Correlated Electrons · Physics 2026-05-29 Michael G. Scheer

A previously developed quantum reduced-order model is revised and applied, together with the domain decomposition, to develop the quantum element method (QEM), a methodology for fast and accurate simulation of quantum eigenvalue problems.…

Computational Physics · Physics 2023-04-18 Ming-C. Cheng

Motivated by recent quantum gas microscope experiments for fermions in optical lattices, we present proof of principle calculations showing that it is possible to obtain the complete information about the quantum state on a small subsystem…

Strongly Correlated Electrons · Physics 2019-09-16 Stephan Humeniuk

The Fermi-Hubbard model is a plausible target to be solved by a quantum computer using the variational quantum eigensolver algorithm. However, problem sizes beyond the reach of classical exact diagonalisation are also beyond the reach of…

Quantum Physics · Physics 2020-06-22 Ashley Montanaro , Stasja Stanisic

A quantum computer will use the properties of quantum physics to solve certain computational problems much faster than otherwise possible. One promising potential implementation is to use superconducting quantum bits in the circuit quantum…

Quantum Physics · Physics 2013-12-01 Matthew Reed

Estimating the ground-state energy of a quantum system is one of the most promising applications for quantum algorithms. Here we propose a variational quantum eigensolver (VQE) \emph{Ansatz} for finding ground state configuration…

Quantum Physics · Physics 2026-02-10 Koray Aydoğan , Anna R. Spak , Kade Head-Marsden , Anthony W. Schlimgen

Recent research has shown that wavefunction evolution in real- and imaginary-time can generate quantum subspaces with significant utility for obtaining accurate ground state energies. Inspired by these methods, we propose combining quantum…

The field of Electronic Design Automation (EDA) is crucial for microelectronics, but the increasing complexity of Integrated Circuits (ICs) poses challenges for conventional EDA: Corresponding problems are often NP-hard and are therefore in…

Quantum Physics · Physics 2025-04-25 Matthias Jung , Sven O. Krumke , Christof Schroth , Elisabeth Lobe , Wolfgang Mauerer

Key properties of physical systems can be described by the eigenvalues of matrices that represent the system. Computational algorithms that determine the eigenvalues of these matrices exist, but they generally suffer from a loss of…

Quantum Physics · Physics 2023-10-31 T. Powers , R. M. Rajapakse

We introduce the Qumode Subspace Variational Quantum Eigensolver (QSS-VQE), a hybrid quantum-classical algorithm for computing molecular excited states using the Fock basis of bosonic qumodes in circuit quantum electrodynamics (cQED)…

The self-field approach to quantum electrodynamics (QED) is used to study the bound state problem in light-front two-dimensional QED with massive matter fields. A composite matter field describing bound states is introduced and the…

High Energy Physics - Theory · Physics 2009-10-31 Fuad M. Saradzhev

We demonstrate a method that merges the quantum filter diagonalization (QFD) approach for hybrid quantum/classical solution of the time-independent electronic Schr\"odinger equation with a low-rank double factorization (DF) approach for the…

Quantum Physics · Physics 2022-03-21 Jeffrey Cohn , Mario Motta , Robert M. Parrish

Variational quantum algorithms (VQAs) have emerged in recent years as a promise to obtain quantum advantage. These task-oriented algorithms work in a hybrid loop combining a quantum processor and classical optimization. Using a specific…

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