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Jerk Current: A Novel Bulk Photovoltaic Effect

2018· article· en· W2898407458 on OpenAlexafffund
Benjamin M. Fregoso, Rodrigo A. Muniz, J. E. Sipe

Bibliographic record

VenuePhysical Review Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsJerkPhysicsElectric fieldCurrent (fluid)Polarization (electrochemistry)Electric currentPerpendicularQuadratic growthCondensed matter physicsDrift currentSaturation (graph theory)AccelerationComputational physicsClassical mechanicsQuantum mechanicsMathematical analysisMathematicsGeometryThermodynamics

Abstract

fetched live from OpenAlex

We investigate a physical divergence of the third order polarization susceptibility representing a photoinduced current in biased crystalline insulators. This current grows quadratically with illumination time in the absence of momentum relaxation and saturation; we refer to it as the jerk current. Two contributions to the current are identified. The first is a hydrodynamic acceleration of optically injected carriers by the static electric field, and the second is the change in the carrier injection rate in the presence of the static electric field. The jerk current can have a component perpendicular to the static field, a feature not captured by standard hydrodynamic descriptions of carriers in electric fields. We suggest an experiment to detect the jerk current and some of its interesting features.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations44
Published2018
Admission routes2
Has abstractyes

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