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Quantum information theory has considerably helped in the understanding of quantum many-body systems. The role of quantum correlations and in particular, bipartite entanglement, has become crucial to characterise, classify and simulate…

Quantum Physics · Physics 2018-07-27 Gabriele De Chiara , Anna Sanpera

We present several refinements and extensions of the statistical quantum phase estimation (SQPE) framework to address some of its key practical limitations, improving its applicability to realistic cases. Recently, a family of statistical…

Quantum Physics · Physics 2026-05-20 Amit Surana , Brandon Allen

Quantum phase estimation (QPE) is one of the most important subroutines in quantum computing. In general applications, current QPE algorithms either suffer an exponential time overload or require a set of - notoriously quite fragile - GHZ…

Quantum Physics · Physics 2021-10-04 Luca Pezzè , Augusto Smerzi

A numerically implementable Multi-scale Many-Body approach to strongly correlated electron systems is introduced. An extension to quantum cluster methods, it approximates correlations on any given length-scale commensurate with the strength…

Strongly Correlated Electrons · Physics 2012-01-04 C. Slezak , M. Jarrell , Th. Maier , J. Deisz

With the evolution of numerical methods, we are now aiming at not only qualitative understanding but also quantitative prediction and design of quantum many-body phenomena. As a novel numerical approach, machine learning techniques have…

Strongly Correlated Electrons · Physics 2024-12-20 Yusuke Nomura , Masatoshi Imada

Learning many-body quantum states and quantum phase transitions remains a major challenge in quantum many-body physics. Classical machine learning methods offer certain advantages in addressing these difficulties. In this work, we propose a…

Quantum Physics · Physics 2026-02-03 Xin Li , Zhang-Qi Yin

In a quantum computation with pure states, the generation of large amounts of entanglement is known to be necessary for a speedup with respect to classical computations. However, examples of quantum computations with mixed states are known,…

Quantum Physics · Physics 2007-05-23 Animesh Datta , Guifre Vidal

Multitime quantum correlation functions are central objects in physical science, offering a direct link between experimental observables and the dynamics of an underlying model. While experiments such as 2D spectroscopy and quantum control…

Chemical Physics · Physics 2024-07-10 Thomas Sayer , Andrés Montoya-Castillo

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the…

Quantum computing promises to provide the next step up in computational power for diverse application areas. In this review, we examine the science behind the quantum hype, and the breakthroughs required to achieve true quantum advantage in…

Quantum Physics · Physics 2025-09-26 R. Au-Yeung , B. Camino , O. Rathore , V. Kendon

Estimation of physical observables for unknown quantum states is an important problem that underlies a wide range of fields, including quantum information processing, quantum physics, and quantum chemistry. In the context of quantum…

Quantum Physics · Physics 2024-05-21 Yuma Nakamura , Yoshichika Yano , Nobuyuki Yoshioka

A common situation in quantum many-body physics is that the underlying theories are known but too complicated to solve efficiently. In such cases one usually builds simpler effective theories as low-energy or large-scale alternatives to the…

Quantum Physics · Physics 2023-09-07 Yongdan Yang , Zongkang Zhang , Xiaosi Xu , Bing-Nan Lu , Ying Li

We investigate the quantum equation of motion (qEOM), a hybrid quantum-classical algorithm for computing excitation properties of a fermionic many-body system, with a particular emphasis on the strong-coupling regime. The method is designed…

Nuclear Theory · Physics 2023-09-20 Manqoba Q. Hlatshwayo , John Novak , Elena Litvinova

Determination of the quantum nature of correlations between two spatially separated systems plays a crucial role in quantum information science. Of particular interest is the questions of if and how these correlations enable quantum…

Quantum Physics · Physics 2017-09-27 Farid Shahandeh , Austin P. Lund , Timothy C. Ralph

Quantum computers are special purpose machines that are expected to be particularly useful in simulating strongly correlated chemical systems. The quantum computer excels at treating a moderate number of orbitals within an active space in a…

Quantum coherence quantifies the amount of superposition a quantum state can have in a given basis. Since there is a difference in the structure of eigenstates of the ergodic and many-body localized systems, we expect them also to differ in…

Strongly Correlated Electrons · Physics 2020-07-29 Sayandip Dhara , Alioscia Hamma , Eduardo R. Mucciolo

The characterization of many-body correlations provides a powerful tool for analyzing correlated quantum materials. However, experimental extraction of quantum entanglement in correlated electronic systems remains an open problem in…

Strongly Correlated Electrons · Physics 2023-04-21 Faluke Aikebaier , Teemu Ojanen , Jose L. Lado

Estimating a quantum phase is a necessary task in a wide range of fields of quantum science. To accomplish this task, two well-known methods have been developed in distinct contexts, namely, Ramsey interferometry (RI) in atomic and…

We introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems, with a focus on molecular systems. The method combines classical preparation of a perturbed…

Quantum Physics · Physics 2025-10-30 Alessandro Santini , Stefano Barison , Filippo Vicentini

The classical simulation of quantum systems typically requires exponential resources. Recently, the introduction of a machine learning-based wavefunction ansatz has led to the ability to solve the quantum many-body problem in regimes that…

Disordered Systems and Neural Networks · Physics 2019-10-24 Joseph Gomes , Keri A. McKiernan , Peter Eastman , Vijay S. Pande