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Record W3019420620 · doi:10.1088/1402-4896/ab8c16

Transforming quantum states between reference frames

2020· article· en· W3019420620 on OpenAlexafffund
J. Ben-Benjamin, Marlan O. Scully, W. G. Unruh

Bibliographic record

VenuePhysica Scripta · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Electrodynamics and Casimir Effect
Canadian institutionsUniversity of British Columbia
FundersAir Force Office of Scientific ResearchOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced ResearchKing Abdulaziz City for Science and TechnologyWelch Foundation
KeywordsUnruh effectMinkowski spacePhysicsReference frameQuantum stateQuantumClassical mechanicsQuantum mechanicsTheoretical physicsMathematical physicsFrame (networking)Computer science

Abstract

fetched live from OpenAlex

Abstract In the 1970s, Fulling, Davis, and Unruh have shown that a quantum mechanical state must be described differently in different reference frames; otherwise, quantum mechanics would contain contradictions. We present a simple method for transforming any quantum state between the Minkowski and Rindler reference frames. We show that a Wigner-like distribution, commonly used in quantum optics, is useful for treating this problem. To illustrate our method, we transform the Minkowski vacuum and number states into Rindler space, and transform the Rindler vacuum into Minkowski space, as examples. Our method could be generalized to other cases as well.

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)0.001
metaresearch head score (Gemma)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.257
Teacher spread0.235 · 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".

Quick stats

Citations9
Published2020
Admission routes2
Has abstractyes

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