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Coherent quantum work extraction of a relativistic battery as a probe for acceleration-induced Unruh thermality

2025· article· en· W4414302626 on OpenAlexaff
Weiwei Zhang, Yin-Zhong Wu, Xiang Hao

Bibliographic record

VenueThe European Physical Journal C · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Electrodynamics and Casimir Effect
Canadian institutionsUniversity of British Columbia
FundersSponsoring Consortium for Open Access Publishing in Particle Physics
KeywordsUnruh effectQuantumWork (physics)Coherent statesThermalField (mathematics)Battery (electricity)Quantum field theory

Abstract

fetched live from OpenAlex

Abstract We propose a physical scheme of a uniformly accelerated Unruh–DeWitt battery and utilize quantum work extraction as a probe to witness the thermal nature of the Unruh effect induced by the accelerated motion. By employing the open quantum system approach, we analyze the coherent and incoherent components of the ergotropy which is the maximum amount of quantum work extraction of the relativistic battery driven by a coherent field. It has been proved that the steady values of coherent quantum work extraction in the asymptotic condition is only determined by the acceleration-dependent Unruh temperature. The asymptotic behavior of coherent ergotropy can demonstrate the thermal nature of the Unruh effect with respect to the Kubo–Martin–Schwinger condition. Under the circumstance of the Unruh effect, we explore the effect of the phase of the coherent charging field on the dynamics of coherent ergotropy when the battery approaches to the same thermal equilibrium state. The variation in the phase of the coherent driving field can improve the energy storage capacity of a relativistic battery. From viewpoint of energy transfer, the relativistic battery is helpful to examine the Unruh thermality.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0000.001
Open science0.0000.000
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 head0.018
GPT teacher head0.301
Teacher spread0.284 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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