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Record W4313557597 · doi:10.1103/physreva.107.012207

Quantum work extraction of an accelerated Unruh-DeWitt battery in relativistic motion

2023· article· en· W4313557597 on OpenAlexaff
Xiang Hao, Kai Yan, Jia Tan, Quanying Wu

Bibliographic record

VenuePhysical review. A/Physical review, A · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Electrodynamics and Casimir Effect
Canadian institutionsUniversity of British Columbia
FundersSponsoring Consortium for Open Access Publishing in Particle Physics
KeywordsPhysicsUnruh effectQuantumRelativistic speedRelativistic quantum chemistryMinkowski spaceClassical mechanicsQuantum electrodynamicsQuantum mechanicsRelativistic particleElectron

Abstract

fetched live from OpenAlex

We investigate the maximal amount of quantum work in a driven atom as a quantum battery which is coupled to a massless scalar field in a Minkowski vacuum. The relativistic thermodynamics of the quantum battery is explored from the prospective of quantum channels. It is found that quantum work extraction can be enhanced in the battery whose trajectory is characterized by a combination of a linear accelerated motion and a component of the four velocity. In the nonrelativistic case, the accelerated motion results in the attenuation of energy extraction, while the velocity component can prevent the degradation of quantum work to a certain extent. The work extraction can increase in the relativistic regime. Moreover, for ultrarelativistic velocities, the relativistic thermodynamics of the quantum battery can behave as if it were a closed system owing to the relativity correction associated with the velocity. The extractable work can be shielded from the impacts of vacuum fluctuations and relativistic motion. It is demonstrated that the work extraction relies on quantum coherence of the relativistic battery and nonclassical nature in the Minkowski vacuum.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.379
Teacher spread0.357 · 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 designSimulation or modeling
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

Citations13
Published2023
Admission routes1
Has abstractyes

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