Characterizing dynamical criticality of many-body localization transitions from a Fock-space perspective

Characterizing the nature of many-body localization transitions (MBLTs) and their potential critical behaviors has remained a challenging problem. In this work, we study the dynamics of the displacement, quantifying the spread of the radial probability distribution in the Fock space, for three systems with MBLTs, i.e., the Hamiltonian models with quasiperiodic and random fields, as well as a random-circuit Floquet model of a MBLT. We then perform a finite-size scaling analysis of the long-time averaged displacement by considering two types of ansatz for MBLTs, i.e., continuous and Berezinskii-Kosterlitz-Thouless (BKT) transitions. The data collapse based on the assumption of a continuous phase transition with power-law correlation length reveals that the scaling exponent of the MBLT induced by random field is close to that of the Floquet model, but significantly differs from the quasiperiodic model. Additionally, we find that the BKT-type scaling provides a more accurate description of the MBLTs in the random model and the Floquet model, yielding larger (finite-size) critical points compared to those obtained from power-law scaling. Our work highlights that the displacement is a valuable tool for studying MBLTs, and is relevant to ongoing experimental efforts.

Authors

Institutions

Publication Details

Journal
Physical review. B./Physical review. B
Published
2025-03-27
DOI
https://doi.org/10.1103/physrevb.111.094210
Citations
1
Primary Topic
Quantum many-body systems
Type
article
Field-Weighted Citation Impact
1.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterizing dynamical criticality of many-body localization transitions from a Fock-space perspective

Jian Cui, Markus Heyl, Yong-Yi Wang, Zheng‐Hang Sun et al.
1 citations
Physical review. B./Physical review. B
Quantum many-body systems
1.25
article

Characterizing dynamical criticality of many-body localization transitions from a Fock-space perspective

Jian Cui, Markus Heyl, Yong-Yi Wang, Zheng‐Hang Sun, Heng Fan
article en
1 citations

Abstract

Characterizing the nature of many-body localization transitions (MBLTs) and their potential critical behaviors has remained a challenging problem. In this work, we study the dynamics of the displacement, quantifying the spread of the radial probability distribution in the Fock space, for three systems with MBLTs, i.e., the Hamiltonian models with quasiperiodic and random fields, as well as a random-circuit Floquet model of a MBLT. We then perform a finite-size scaling analysis of the long-time averaged displacement by considering two types of ansatz for MBLTs, i.e., continuous and Berezinskii-Kosterlitz-Thouless (BKT) transitions. The data collapse based on the assumption of a continuous phase transition with power-law correlation length reveals that the scaling exponent of the MBLT induced by random field is close to that of the Floquet model, but significantly differs from the quasiperiodic model. Additionally, we find that the BKT-type scaling provides a more accurate description of the MBLTs in the random model and the Floquet model, yielding larger (finite-size) critical points compared to those obtained from power-law scaling. Our work highlights that the displacement is a valuable tool for studying MBLTs, and is relevant to ongoing experimental efforts.

Physical review. B./Physical review. BVol. 111(9)
University of Augsburg (DE), Chinese Academy of Sciences (CN), Hefei University (CN), Songshan Lake Materials Laboratory (CN), Beijing Academy of Quantum Information Sciences (CN), University of Chinese Academy of Sciences (CN), Beihang University (CN)
European Commission, Deutsche Forschungsgemeinschaft, National Natural Science Foundation of China, Chinese Academy of Sciences, Natural Science Foundation of Beijing Municipality, European Research Council, Horizon 2020, National Key Research and Development Program of China
Openalex Percentile: Top 23%
Quantum many-body systems
1.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.