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Related papers: Measurement-induced phase transitions in quantum i…

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We establish an intriguing connection between quantum phase transitions and bifurcations in the reduced fidelity between two different reduced density matrices for quantum lattice many-body systems with symmetry-breaking orders. Our finding…

Strongly Correlated Electrons · Physics 2009-05-20 Jin-Hua Liu , Qian-Qian Shi , Jian-Hui Zhao , Huan-Qiang Zhou

Relevant metrological scenarios involve the simultaneous estimation of multiple parameters. The fundamental ingredient to achieve quantum-enhanced performances is based on the use of appropriately tailored quantum probes. However, reaching…

Critical metrology relies on the precise preparation of a system in its ground state near a quantum phase transition point where quantum correlations get very strong. Typically this increases the quantum Fisher information with respect to…

Quantum Physics · Physics 2024-02-12 Christoph Hotter , Helmut Ritsch , Karol Gietka

Quantum phase estimation is a central primitive in quantum algorithms and sensing, where performance is governed by the sensitivity of measurement signals to the target parameter. While existing methods have developed increasingly…

Quantum Physics · Physics 2026-04-02 Zikang Jia , Suying Liu , Yulong Dong

Quantum systems subject to random unitary evolution and measurements at random points in spacetime exhibit entanglement phase transitions which depend on the frequency of these measurements. Past work has experimentally observed…

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the…

Quantum Physics · Physics 2024-12-19 Kevin Lively , Tim Bode , Jochen Szangolies , Jian-Xin Zhu , Benedikt Fauseweh

A key component of a quantum machine learning model operating on classical inputs is the design of an embedding circuit mapping inputs to a quantum state. This paper studies a transfer learning setting in which classical-to-quantum…

Quantum Physics · Physics 2022-12-01 Sharu Theresa Jose , Osvaldo Simeone

The competition between unitary quantum dynamics and dissipative stochastic effects, as emerging from continuous-monitoring processes, can culminate in measurement-induced phase transitions. Here, a many-body system abruptly passes, when…

Statistical Mechanics · Physics 2025-02-04 Moritz Eissler , Igor Lesanovsky , Federico Carollo

The rapid progress in quantum computing (QC) and machine learning (ML) has attracted growing attention, prompting extensive research into quantum machine learning (QML) algorithms to solve diverse and complex problems. Designing…

Quantum Physics · Physics 2025-01-13 Samuel Yen-Chi Chen , Huan-Hsin Tseng , Hsin-Yi Lin , Shinjae Yoo

Environment-induced decoherence has long been recognised as being of crucial importance in the study of chaos in quantum systems. In particular, the exact form and strength of the system-environment interaction play a major role in the…

Quantum Physics · Physics 2017-08-02 Jessica K. Eastman , Joseph J. Hope , André R. R. Carvalho

Predicting the outcomes of quantum measurements is a cornerstone of quantum information theory and a key resource for quantum technologies. Here, we introduce a comprehensive framework for quantifying the predictability of measurements on a…

Quantum Physics · Physics 2026-01-28 Dennis I. Martínez-Moreno , Miguel Castillo-Celeita , Diego G. Bussandri

In this paper, we discuss the connection between two genuinely quantum phenomena --- the discontinuity of quantum maximum entropy inference and quantum phase transitions at zero temperature. It is shown that the discontinuity of the maximum…

Quantum Physics · Physics 2015-08-14 Jianxin Chen , Zhengfeng Ji , Chi-Kwong Li , Yiu-Tung Poon , Yi Shen , Nengkun Yu , Bei Zeng , Duanlu Zhou

This paper presents a mathematical framework for causal nonlinear prediction in settings where observations are generated from an underlying hidden Markov model (HMM). Both the problem formulation and the proposed solution are motivated by…

Machine Learning · Computer Science 2026-03-16 Heng-Sheng Chang , Prashant G. Mehta

Understanding the physical significance and probing the global invariants characterizing quantum topological phases in extended systems is a main challenge in modern physics with major impact in different areas of science. Here, a…

Quantum Physics · Physics 2019-10-08 Gian Luca Giorgi , Stefano Longhi , Albert Cabot , Roberta Zambrini

Symmetry is a powerful tool for understanding phases of matter in equilibrium. Quantum circuits with measurements have recently emerged as a platform for novel states of matter intrinsically out of equilibrium. Can symmetry be used as an…

Quantum Physics · Physics 2025-06-18 Zhi Li , Zhu-Xi Luo

A usual assumption in quantum estimation is that the unknown parameter labels the possible states of the system, while it influences neither the sample space of outcomes nor the measurement aimed at extracting information on the parameter…

Quantum Physics · Physics 2017-01-18 Luigi Seveso , Matteo A. C. Rossi , Matteo G. A. Paris

Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been developed for solving classification problems, such as…

Quantum Physics · Physics 2025-01-24 Andrey Kardashin , Yerassyl Balkybek , Vladimir V. Palyulin , Konstantin Antipin

Quantum phase transitions occur when the ground state of a quantum system undergoes a qualitative change when an external control parameter reaches a critical value. Here, we demonstrate a technique for studying quantum systems undergoing a…

Quantum Physics · Physics 2008-03-14 Jingfu Zhang , Xinhua Peng , Nageswaran Rajendran , Dieter Suter

We explore a previously unknown connection between two important problems in physics, i.e., quantum macroscopicity and the quantum phase transition. We devise a general and computable measure of quantum macroscopicity that can be applied to…

Quantum Physics · Physics 2016-11-30 Chae-Yeun Park , Minsu Kang , Chang-Woo Lee , Jeongho Bang , Seung-Woo Lee , Hyunseok Jeong

We present a study of the phase diagram of a random optimization problem in presence of quantum fluctuations. Our main result is the characterization of the nature of the phase transition, which we find to be a first-order quantum phase…

Disordered Systems and Neural Networks · Physics 2010-05-24 T. Jorg , F. Krzakala , G. Semerjian , F. Zamponi