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Record W2803781738 · doi:10.1103/physrevb.99.075162

Exploration of the existence of a distinct quasi many-body localized phase: Numerical study of a translationally invariant system in the thermodynamic limit

2019· article· en· W2803781738 on OpenAlexafffund
Jesko Sirker

Bibliographic record

VenuePhysical review. B./Physical review. B · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum many-body systems
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft
KeywordsPhysicsDephasingQuantum entanglementThermodynamic limitScalingErgodic theoryQuantum mechanicsExponential functionLogarithmAnderson localizationExponential decayBosonAmplitudeRenormalization groupQuantum

Abstract

fetched live from OpenAlex

We consider a quench in an infinite spin ladder describing a system with two species of bosons in the limit of strong interactions. If the heavy bosonic species has infinite mass, the model becomes a spin chain with quenched binary disorder which shows true Anderson localization (AL) or many-body localization (MBL). For finite hopping amplitude ${J}^{\ensuremath{'}}$ of the heavy particles, on the other hand, we find an exponential polarization decay with a relaxation rate which depends monotonically on ${J}^{\ensuremath{'}}$. Furthermore, the entanglement entropy changes from a constant (AL) or logarithmic (MBL) scaling in time $t$ for ${J}^{\ensuremath{'}}=0$ to a subballistic power law, ${S}_{\mathrm{ent}}\ensuremath{\sim}{t}^{\ensuremath{\alpha}}$ with $\ensuremath{\alpha}<1$, for finite ${J}^{\ensuremath{'}}$. We do not find a distinct regime in time where the dynamics for ${J}^{\ensuremath{'}}\ensuremath{\ne}0$ shows the characteristics of an MBL phase. Instead, we discover a time regime with distinct dephasing and entanglement times, leading to dynamics in this regime which is different both from a localized and from a fully ergodic phase.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.354
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2019
Admission routes2
Has abstractyes

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