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Understanding the collective behavior of a quantum many-body system, a system composed of a large number of interacting microscopic degrees of freedom, is a key aspect in many areas of contemporary physics. However, as a direct consequence…

Quantum Physics · Physics 2011-09-27 Glen Evenbly

Understanding quantum magic (i.e., nonstabilizerness) in many-body quantum systems is challenging but essential to the study of quantum computation and many-body physics. We investigate how noise affects magic properties in entangled…

Quantum Physics · Physics 2024-10-29 Fuchuan Wei , Zi-Wen Liu

Variational algorithms are a promising paradigm for utilizing near-term quantum devices for modeling electronic states of molecular systems. However, previous bounds on the measurement time required have suggested that the application of…

Advancements in quantum computing have spurred significant interest in harnessing its potential for speedups over classical systems. However, noise remains a major obstacle to achieving reliable quantum algorithms. In this work, we present…

Quantum Physics · Physics 2025-05-29 Lucas Tecot , Di Luo , Cho-Jui Hsieh

Topological properties of quantum systems are one of the most intriguing emerging phenomena in condensed matter physics. A crucial property of topological systems is the symmetry-protected robustness towards local noise. Experiments have…

Quantum Physics · Physics 2022-12-05 Guliuxin Jin , Eliska Greplova

The one-way quantum computing model introduced by Raussendorf and Briegel [Phys. Rev. Lett. 86 (22), 5188-5191 (2001)] shows that it is possible to quantum compute using only a fixed entangled resource known as a cluster state, and adaptive…

Quantum Physics · Physics 2009-11-10 Michael A. Nielsen , Christopher M. Dawson

Near-term quantum computers are noisy, and therefore must run algorithms with a low circuit depth and qubit count. Here we investigate how noise affects a quantum neural network (QNN) for state discrimination, applicable on near-term…

Quantum Physics · Physics 2021-01-27 Andrew Patterson , Hongxiang Chen , Leonard Wossnig , Simone Severini , Dan Browne , Ivan Rungger

Entanglement-based quantum networks exhibit a unique flexibility in the choice of entangled resource states that are then locally manipulated by the nodes to fulfill any request in the network. Furthermore, this manipulation is not uniquely…

Quantum Physics · Physics 2025-02-04 Maria Flors Mor-Ruiz , Julius Wallnöfer , Wolfgang Dür

We prove a new version of the quantum accuracy threshold theorem that applies to non-Markovian noise with algebraically decaying spatial correlations. We consider noise in a quantum computer arising from a perturbation that acts…

Quantum Physics · Physics 2009-11-11 Dorit Aharonov , Alexei Kitaev , John Preskill

Extracting useful information from noisy near-term quantum simulations requires error mitigation strategies. A broad class of these strategies rely on precise characterization of the noise source. We study the robustness of probabilistic…

Quantum Physics · Physics 2025-07-28 Pradeep Niroula , Sarang Gopalakrishnan , Michael J. Gullans

Efficiently characterizing large quantum states and processes is a central yet notoriously challenging task in quantum information science, as conventional tomography methods typically require resources that grow exponentially with system…

Quantum Physics · Physics 2026-03-03 Chenyang Li , Shengxin Zhuang , Yukun Zhang , Jingbo B. Wang , Xiao Yuan , Yusen Wu , Chuan Wang

A major goal of developing high-precision control of many-body quantum systems is to realise their potential as quantum computers. Probably the most significant obstacle in this direction is the problem of "decoherence": the extreme…

Motivated by the ground state structure of quantum models with all-to-all interactions such as mean-field quantum spin glass models and the Sachdev-Ye-Kitaev (SYK) model, we propose a tensor network architecture which can accomodate volume…

Quantum Physics · Physics 2024-05-29 Valérie Bettaque , Brian Swingle

Quantum machine learning uses principles from quantum mechanics to process data, offering potential advances in speed and performance. However, previous work has shown that these models are susceptible to attacks that manipulate input data…

Recently developed tensor network methods demonstrate great potential for addressing the quantum many-body problem, by constructing variational spaces with polynomially, instead of exponentially, scaled parameters. Constructing such an…

Strongly Correlated Electrons · Physics 2015-06-15 Zhen Wang , Yongjian Han , Guang-Can Guo , Lixin He

Transient stability assessment (TSA) is a cornerstone for resilient operations of today's interconnected power grids. This paper is a confluence of quantum computing, data science and machine learning to potentially address the power system…

Quantum Physics · Physics 2021-05-25 Yifan Zhou , Peng Zhang

Noiseless subsystems offer a general and efficient method for protecting quantum information in the presence of noise that has symmetry properties. A paradigmatic class of error models displaying non-trivial symmetries emerges under…

Quantum computation has been growing rapidly in both theory and experiments. In particular, quantum computing devices with a large number of qubits have been developed by IBM, Google, IonQ, and others. The current quantum computing devices…

Quantum Physics · Physics 2021-02-10 Rishabh Gupta , Rongxin Xia , Raphael D. Levine , Sabre Kais

This paper generalizes the results in [30] concerning feedback stabilization of target states for N-level quantum angular momentum systems undergoing quantum non-demolition measurements (QND) in absence of the knowledge about initial states…

Quantum Physics · Physics 2022-07-29 Weichao Liang , Nina H. Amini

Quantum many-body devices suffer from imperfections that destabilize dynamics and limit scalability. We show that the dynamical growth of entanglement can intrinsically protect generic quantum dynamics against coherent and perturbative…

Quantum Physics · Physics 2026-02-25 Tianfeng Feng , Yue Cao , Wenjun Yu , Junkai Zeng , Xiaopeng Li , Xiu-Hao Deng , Qi Zhao