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Record W4321853468 · doi:10.48550/arxiv.2302.10940

Dynamical mean-field theory for Rényi entanglement entropy and mutual Information in Hubbard Model

2023· preprint· en· W4321853468 on OpenAlexaff
Surajit Bera, Arijit Haldar, Sumilan Banerjee

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum many-body systems
Canadian institutionsUniversity of Toronto
FundersScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsQuantum entanglementPhysicsPath integral formulationEntropy (arrow of time)Mutual informationConformal field theoryStatistical physicsQuantum discordFermionQuantum mechanicsSquashed entanglementQuantum relative entropyJoint quantum entropyGeneralized relative entropyTopological entropy in physicsQuantum mutual informationQuantumConformal mapMathematicsStatisticsMathematical analysis

Abstract

fetched live from OpenAlex

Quantum entanglement, lacking any classical counterpart, provides a fundamental new route to characterize the quantum nature of many-body states. In this work, we discuss an implementation of a new path integral method [Phys. Rev. Res. 2, 033505 (2020)] for fermions to compute entanglement for extended subsystems in the Hubbard model within dynamical mean field theory (DMFT) in one and two dimensions. The new path integral formulation measures entanglement by applying a ``kick" to the underlying interacting fermions. We show that the Rényi entanglement entropy can be extracted efficiently within the DMFT framework by integrating over the strength of the kick term. Using this method, we compute the second Rényi entropy as a function of subsystem size for metallic and Mott insulating phases of the Hubbard model. We explore the thermal entropy to entanglement crossover in the subsystem Rényi entropy in the correlated metallic phase. We show that the subsystem-size scaling of second Rényi entropy is well described by the crossover formula which interpolates between the volume-law thermal Rényi entropy and the universal boundary-law Rényi entanglement entropy with logarithmic violation, as predicted by conformal field theory. We also study the mutual information across the Mott metal-insulator transition.

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)0.000
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 score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.045
GPT teacher head0.201
Teacher spread0.156 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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