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Despite tremendous theoretical efforts to understand subtleties of the many-body localization (MBL) transition, many questions remain open, in particular concerning its critical properties. Here we make the key observation that MBL in one…

Disordered Systems and Neural Networks · Physics 2020-12-01 Nicolas Laflorencie , Gabriel Lemarié , Nicolas Macé

Quantum simulation elucidates properties of quantum many-body systems by mapping its Hamiltonian to a better-controlled system. Being less stringent than a universal quantum computer, noisy small- and intermediate-scale quantum simulators…

Recent theoretical work has shown that the competition between coherent unitary dynamics and stochastic measurements, performed by the environment, along wavefunction trajectories can give rise to transitions in the entanglement scaling. In…

Quantum Physics · Physics 2021-12-01 Thomas Botzung , Sebastian Diehl , Markus Müller

We study the many-body localization of spin chain systems with quasiperiodic fields. We identify the lower bound for the critical disorder necessary to drive the transition between the thermal and many-body localized phase to be $W_{cl}\sim…

Disordered Systems and Neural Networks · Physics 2017-08-30 Mac Lee , Thomas R. Look , D. N. Sheng , S. P. Lim

Disorder free many-body localization (MBL) can occur in interacting systems that can dynamically generate their own disorder. We address the thermal-MBL phase transition of two isotropic Heisenberg spin chains that are quasi-periodically…

Disordered Systems and Neural Networks · Physics 2024-09-04 K. G. S. H. Gunawardana , Bruno Uchoa

In ergodic many-body quantum systems, locally encoded quantum information becomes, in the course of time evolution, inaccessible to local measurements. This concept of "scrambling" is currently of intense research interest, entailing a deep…

Quantum Information scrambling (QI-scrambling) is a pivotal area of inquiry within the study of quantum many-body systems. This research derives mathematical upper and lower bounds for the scrambling rate by applying the Maligranda…

Quantum Physics · Physics 2025-07-25 Ahmed Zahia , M. Y. Abd-Rabbou , Atta ur Rahman , Cong Feng Qiao

Closed quantum systems exhibit different dynamical regimes, like Many-Body Localization or thermalization, which determine the mechanisms of spread and processing of information. Here we address the impact of these dynamical phases in…

Operators in ergodic spin-chains are found to grow according to hydrodynamical equations of motion. The study of such operator spreading has aided our understanding of many-body quantum chaos in spin-chains. Here we initiate the study of…

Statistical Mechanics · Physics 2019-03-29 Sanjay Moudgalya , Trithep Devakul , C. W. von Keyserlingk , S. L. Sondhi

Current quantum simulation experiments are starting to explore non-equilibrium many-body dynamics in previously inaccessible regimes in terms of system sizes and time scales. Therefore, the question emerges which observables are best suited…

Quantum Gases · Physics 2022-05-24 A. Bohrdt , S. Kim , A. Lukin , M. Rispoli , R. Schittko , M. Knap , M. Greiner , J. Léonard

We investigate the trends of information backflow associated with the dynamics of a sub-part of a disordered spin-1/2 transverse field Heisenberg chain for different regimes of the Hamiltonian. Towards this aim, the decay profile of…

Quantum Physics · Physics 2020-03-16 Sudipto Singha Roy , Utkarsh Mishra , Debraj Rakshit

Operator scrambling, which governs the spread of quantum information in many-body systems, is a central concept in both condensed matter and high-energy physics. Accurately capturing the emergent properties of these systems remains a…

Quantum Physics · Physics 2025-07-01 Tianfeng Feng , Yue Cao , Qi Zhao

Dephasing of spins is a major roadblock to scaling up the size of quantum computing systems. We explore the possibility of utilizing highly disordered environments which are in the Many-Body Localized phase to arrest this dephasing. We…

Disordered Systems and Neural Networks · Physics 2022-08-30 Shreyas Raman , Subroto Mukerjee

Avalanches are believed to be the mechanism behind the transition from many-body localization to the thermal phase. We utilize spin chains with constraints to study the physics of quantum avalanches by exact diagonalization of disordered…

Disordered Systems and Neural Networks · Physics 2025-08-04 Shuangyuan Lu

As strength of disorder enhances beyond a threshold value in many-body systems, a fundamental transformation happens through which the entire spectrum localizes, a phenomenon known as many-body localization. This has profound implications…

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy $E$ is bounded by a…

Disordered Systems and Neural Networks · Physics 2019-02-26 Wei Zhang , Lei Wang , Ziqiang Wang

We use exact diagonalization to explore the many-body localization transition in a random-field spin-1/2 chain. We examine the correlations within each many-body eigenstate, looking at all states and thus effectively working at infinite…

Disordered Systems and Neural Networks · Physics 2015-03-13 Arijeet Pal , David A. Huse

Random transformations are typically good at "scrambling" information. Specifically, in the quantum setting, scrambling usually refers to the process of mapping most initial pure product states under a unitary transformation to states which…

Quantum Physics · Physics 2013-07-04 Winton Brown , Omar Fawzi

Isolated interacting quantum systems generally thermalize, yet there are several examples for the breakdown of ergodicity, such as many-body localization and quantum scars. Recently, ergodicity breaking has been observed in systems…

Ergodic quantum many-body systems satisfy the eigenstate thermalization hypothesis (ETH). However, strong disorder can destroy ergodicity through many-body localization (MBL) -- at least in one dimensional systems -- leading to a clear…

Disordered Systems and Neural Networks · Physics 2020-08-18 Luis Colmenarez , Paul A. McClarty , Masudul Haque , David J. Luitz
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