MétaCan
Menu
Back to cohort
Record W4386070171 · doi:10.1103/physrevb.108.l081119

Particle current statistics in driven mesoscale conductors

2023· article· en· W4386070171 on OpenAlexafffund
Marlon Brenes, Giacomo Guarnieri, Archak Purkayastha, Jens Eisert, Dvira Segal, Gabriel T. Landi

Bibliographic record

VenuePhysical review. B./Physical review. B · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsUniversity of Toronto
FundersHorizon 2020H2020 Marie Skłodowska-Curie ActionsUniversity of TorontoCanada Foundation for InnovationDeutsche ForschungsgemeinschaftNational Research FoundationNatural Sciences and Engineering Research Council of CanadaEuropean CommissionDanmarks GrundforskningsfondGovernment of OntarioFoundational Questions Institute
KeywordsMesoscopic physicsStatistical physicsPhysicsMaster equationNon-equilibrium thermodynamicsQuadratic equationMesoscale meteorologyCharge (physics)Noise (video)QuantumQuantum mechanicsComputer scienceMathematicsMeteorology

Abstract

fetched live from OpenAlex

We propose a highly scalable method to compute the statistics of charge transfer in driven conductors. The framework can be applied in situations of nonzero temperature, strong coupling to terminals, and in the presence of nonperiodic light-matter interactions, away from equilibrium. The approach combines the so-called mesoscopic leads formalism with full counting statistics. It results in a generalized quantum master equation that dictates the dynamics of current fluctuations and higher order moments of the probability distribution function of charge exchange. For generic time-dependent quadratic Hamiltonians, we provide closed-form expressions for computing noise in the nonperturbative regime of the parameters of the system, reservoir, or system-reservoir interactions. Having access to the full dynamics of the current and its noise, the method allows us to compute the variance of charge transfer over time in nonequilibrium configurations. The dynamics reveal that in driven systems, the average noise should be defined operationally with care over which period of time is covered.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.024
GPT teacher head0.407
Teacher spread0.383 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePhysical review. B./Physical review. BSame topicAdvanced Thermodynamics and Statistical MechanicsFrench-language works237,207