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Quantum Computing is a rapidly developing field with the potential to tackle the increasing computational challenges faced in high-energy physics. In this work, we explore the potential and limitations of variational quantum algorithms in…

The variational quantum eigensolver has been proposed as a low-depth quantum circuit that can be employed to examine strongly correlated systems on today's noisy intermediate-scale quantum computers. We examine details associated with the…

Quantum Physics · Physics 2020-08-26 Luogen Xu , Joseph T. Lee , J. K. Freericks

Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct with high fidelity,…

Quantum Physics · Physics 2022-12-21 Rishabh Gupta , Manas Sajjan , Raphael D. Levine , Sabre Kais

Accurately establishing the state of large-scale quantum systems is an important tool in quantum information science; however, the large number of unknown parameters hinders the rapid characterisation of such states, and reconstruction…

Quantum Physics · Physics 2014-07-30 Francesco Tonolini , Susan Chan , Megan Agnew , Alan Lindsay , Jonathan Leach

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

Variational quantum algorithms are hybrid quantum-classical approaches extensively studied for their potential to leverage near-term quantum hardware for computational advantages. In this work, we successfully execute two variational…

Quantum Physics · Physics 2025-01-03 Alessio Baldazzi , Matteo Sanna , Massimo Borghi , Stefano Azzini , Lorenzo Pavesi

The capacity for solving eigenstates with a quantum computer is key for ultimately simulating physical systems. Here we propose inverse iteration quantum eigensolvers, which exploit the power of quantum computing for the classical inverse…

Quantum Physics · Physics 2022-03-09 Min-Quan He , Dan-Bo Zhang , Z. D. Wang

Quantum state tomography provides a fundamental framework for reconstructing quantum states. When the measurement data are not informationally complete, the observed statistics admit multiple compatible density matrices, making the…

Quantum Physics · Physics 2026-05-01 V. A. Penas , M. Losada , D. Tielas , F. Holik

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the dimension of the problem space grows exponentially, finding the eigenvalues of certain…

We report the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation. We use a programmable array of superconducting qubits to compute the energy surface of molecular hydrogen…

Quantum state tomography, a process that reconstructs a quantum state from measurements on an ensemble of identically prepared copies, plays a crucial role in benchmarking quantum devices. However, brute-force approaches to quantum state…

The field of quantum information has been growing fast over the past decade. Optical quantum computation, based on the concepts of KLM and cluster states, has witnessed experimental realizations of larger and more complex systems in terms…

Quantum Physics · Physics 2014-11-11 Dikla Oren , Yoav Shechtman , Maor Mutzafi , Yonina C. Eldar , Mordechai Segev

Quantum machine learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure…

Chemical Physics · Physics 2021-10-29 Manas Sajjan , Shree Hari Sureshbabu , Sabre Kais

State-of-the-art noisy digital quantum computers can only execute short-depth quantum circuits. Variational algorithms are a promising route to unlock the potential of noisy quantum computers since the depth of the corresponding circuits…

We propose the variational quantum singular value decomposition based on encoding the elements of the considered { $N\times N$} matrix into the state of a quantum system of appropriate dimension. This method doesn't use the expansion of…

Quantum Physics · Physics 2025-08-05 Alexander I. Zenchuk , Wentao Qi , Junde Wu

We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance…

Quantum Physics · Physics 2022-01-25 Sanjaya Lohani , Thomas A. Searles , Brian T. Kirby , Ryan T. Glasser

Recently quantum tomography has been proposed as a fundamental tool for prototyping a few qubit quantum device. It allows the complete reconstruction of the state produced from a given input into the device. From this reconstructed density…

Quantum Physics · Physics 2009-11-07 R. T. Thew , K. Nemoto , A. G. White , W. J. Munro

We present a novel method for improving the quantum simulation of the ground state energy of molecules. We perform a pre-processing step classically, which reduces the dimensionality of the problem by generating a custom mapping which…

Quantum Physics · Physics 2023-03-03 Kaur Kristjuhan , Mark Nicholas Jones

Quantum interference is a central resource in many quantum-enhanced tasks, from computation to communication protocols. While it usually occurs between identical input photons, quantum interference can be enabled by projecting the quantum…

Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy variance, we propose a variational method for solving the…

Quantum Physics · Physics 2024-02-21 Xu-Dan Xie , Zheng-Yuan Xue , Dan-Bo Zhang