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Thermality, causality, and the quantum-controlled Unruh–deWitt detector

2021· preprint· en· W3021798348 on OpenAlexafffund
Joshua Foo, Sho Onoe, Robert B. Mann, Magdalena Zych

Bibliographic record

VenuePhysical Review Research · 2021
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum Electrodynamics and Casimir Effect
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersCentre of Excellence for Quantum Computation and Communication Technology, Australian Research CouncilAustralian Research CouncilNatural Sciences and Engineering Research Council of CanadaAsian Office of Aerospace Research and Development
KeywordsUnruh effectPhysicsDetectorSuperposition principleSpacetimeQuantum entanglementCausality (physics)QuantumQuantum field theoryCurvatureQuantum mechanicsClassical mechanicsTheoretical physicsOptics

Abstract

fetched live from OpenAlex

Particle detector models such as the Unruh--deWitt detector are widely used in relativistic quantum information and field theory to probe the global features of spacetime and quantum fields. These detectors are typically modeled as coupling locally to the field along a classical worldline. In this paper, we utilize a recent framework that enables us to prepare the detector in a quantum-controlled superposition of trajectories and study its response to a massless scalar field in finite-temperature Minkowski spacetime and an expanding de Sitter universe. Unlike a detector on a classical path, which cannot distinguish these spacetimes, the superposed detector can do so by acquiring nonlocal information about the geometric and causal structure of its environment, demonstrating its capability as a probe of these global properties.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0000.003
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 head0.048
GPT teacher head0.424
Teacher spread0.376 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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