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Record W4399986531 · doi:10.48550/arxiv.2406.14637

Derivative coupling enables genuine entanglement harvesting in causal communication

2024· preprint· en· W4399986531 on OpenAlexfundno aff
Adam Teixidó-Bonfill, Eduardo Martín-Martínez

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldComputer Science
TopicNeural Networks and Reservoir Computing
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Colleges and UniversitiesFundación Bancaria Caixa d'Estalvis i Pensions de BarcelonaInstitut Périmètre de physique théoriqueIndustry CanadaGovernment of Canada
KeywordsQuantum entanglementCoupling (piping)Derivative (finance)Computer sciencePhysicsQuantum mechanicsEngineeringEconomicsQuantum

Abstract

fetched live from OpenAlex

We show that particle detectors coupled to a massless quantum field through its derivative can genuinely harvest entanglement form the field even when they are in causal contact in flat spacetime. This is particularly relevant since the derivative coupling model captures some interesting experimentally realizable systems and since the harvested entanglement peaks at full light contact.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.008
Research integrity0.0000.001
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 head0.080
GPT teacher head0.207
Teacher spread0.127 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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