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The quantum-selected configuration interaction (QSCI) method is a promising approach for large-scale quantum chemical calculations on currently available quantum hardware. However, its naive implementation lacks size consistency, which is…

Quantum Physics · Physics 2026-01-06 Kenji Sugisaki

Recent results have established dramatic advantages in learning properties of quantum states when a quantum computer is available to process or jointly measure multiple copies of the unknown quantum state. Learning tasks can be accomplished…

Quantum Physics · Physics 2026-05-08 Spencer Dimitroff , John Kallaugher , Ashe Miller , Mohan Sarovar

We detail a quantum circuit capable of efficiently encoding analytical approximations to gravitational wave signal waveforms of compact binary coalescences into the amplitudes of quantum bits using both quantum arithmetic operations and…

Quantum Physics · Physics 2023-06-21 Fergus Hayes , Sarah Croke , Chris Messenger , Fiona Speirits

A quantum eigensolver is designed under a multi-layer cluster mean-field (CMF) algorithm by partitioning a quantum system into spatially-separated clusters. For each cluster, a reduced Hamiltonian is obtained after a partial average over…

Despite advances in the development of quantum computers, the practical application of quantum algorithms requiring deep circuit depths or high-fidelity transformations remains outside the current range of the so-called noisy…

Accurately determining ground-state properties of quantum many-body systems remains one of the major challenges of quantum simulation. In this work, we present a protocol for estimating the ground-state energy using only global time…

We implement a hybrid quantum-classical model for image classification that compresses MNIST digit images into a low-dimensional feature space and then maps these features onto a 5-qubit quantum state. First, an autoencoder compresses each…

Quantum Physics · Physics 2025-08-01 Soumyadip Sarkar

We demonstrate a compressive normalized ghost imaging system with entangled photons employing complementary compressive imaging (CCI) technique. The quantum ghost image reconstruction was achieved at only 19.53% sampling ratio of raster…

Quantum Physics · Physics 2017-03-14 Dawei Liu , Lifei Li

Quantum state tomography (QST) is an essential technique for reconstructing the density matrix of an unknown quantum state from measurement data, crucial for quantum information processing. However, conventional QST requires an…

Quantum Physics · Physics 2025-06-05 Yoshiyuki Kakihara , Daisuke Yamamoto , Giacomo Marmorini

Quantum simulations are bound to be one of the main applications of near-term quantum computers. Quantum chemistry and condensed matter physics are expected to benefit from these technological developments. Several quantum simulation…

Quantum Physics · Physics 2018-01-04 Pierre-Luc Dallaire-Demers , Jonathan Romero , Libor Veis , Sukin Sim , Alán Aspuru-Guzik

Entanglement is the quintessential quantum phenomenon and a key enabler of quantum algorithms. The ability to faithfully entangle many distinct particles is often used as a benchmark for the quality of hardware and control in a quantum…

Quantum Physics · Physics 2025-10-13 Ali Javadi-Abhari , Simon Martiel , Alireza Seif , Maika Takita , Ken X. Wei

Estimating the eigenstate properties of quantum systems is a long-standing, challenging problem for both classical and quantum computing. Existing universal quantum algorithms typically rely on ideal and efficient query models (e.g. time…

Quantum Physics · Physics 2026-01-21 Jinzhao Sun , Pei Zeng , Tom Gur , M. S. Kim

The Gottesman-Kitaev-Preskill (GKP) encoding of a qubit within an oscillator provides a number of advantages when used in a fault-tolerant architecture for quantum computing, most notably that Gaussian operations suffice to implement all…

Quantum Physics · Physics 2017-05-09 Keith R. Motes , Ben Q. Baragiola , Alexei Gilchrist , Nicolas C. Menicucci

Variational quantum algorithms are promising tools whose efficacy depends on their optimisation method. For noise-free unitary circuits, the quantum generalisation of natural gradient descent has been introduced and shown to be equivalent…

Quantum Physics · Physics 2023-09-12 Bálint Koczor , Simon C. Benjamin

Quantum state tomography is an essential tool for the characterization and verification of quantum states. However, as it cannot be directly applied to systems with more than a few qubits, efficient tomography of larger states on mid-sized…

Quantum Physics · Physics 2023-02-01 Yotam Y. Lifshitz , Eyal Bairey , Eli Arbel , Gadi Aleksandrowicz , Haggai Landa , Itai Arad

Quantum computers hold promise to enable efficient simulations of the properties of molecules and materials; however, at present they only permit ab initio calculations of a few atoms, due to a limited number of qubits. In order to harness…

Materials Science · Physics 2020-07-07 He Ma , Marco Govoni , Giulia Galli

Near-term quantum devices require wavefunction ans\"atze that are expressive while also of shallow circuit depth in order to both accurately and efficiently simulate molecular electronic structure. While unitary coupled cluster (e.g.,…

Quantum computing is one of the most promising technologies of the near future, and the simulation of quantum many-body systems is a natural application. In this work, we present classical simulations of the ground states of light atomic…

The quantum circuit model is the de-facto way of designing quantum algorithms. Yet any level of abstraction away from the underlying hardware incurs overhead. In the era of near-term, noisy, intermediate-scale quantum (NISQ) hardware with…

Quantum Physics · Physics 2021-08-27 Laura Clinton , Johannes Bausch , Toby Cubitt

We propose an efficient quantum state tomography method inspired by compressed sensing and threshold quantum state tomography that can drastically reduce the number of measurement settings to reconstruct the density matrix of an $N$-qudit…

Quantum Physics · Physics 2025-04-01 Giovanni Garberoglio , Maurizio Dapor , Diego Maragnano , Marco Liscidini , Daniele Binosi
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