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Record W2019402082 · doi:10.1103/physrevlett.85.2925

Better Schemes for Quantum Interrogation in Lossy Experiments

2000· article· en· W2019402082 on OpenAlexaff
Terry Rudolph

Bibliographic record

VenuePhysical Review Letters · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Mechanics and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLossy compressionInterrogationScheme (mathematics)PhysicsPhotonQuantumSpace (punctuation)Statistical physicsQuantum mechanicsFree spaceTheoretical physicsComputer scienceOpticsMathematicsLawMathematical analysis

Abstract

fetched live from OpenAlex

We show that several schemes exist for improving the efficiency of quantum interrogations (or "interaction-free" measurements), which in principle are limited by lossy experimental components. We show how one new scheme (the "Helstrom" scheme) can efficiently detect the presence of a bomb which has been designed to foil standard quantum interrogations by arming itself when there is high probability of a photon being in the region. This particular new scheme can probe a region of space with a greater probability of success than a person in that region determining they are being probed.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0030.011
Open science0.0020.004
Research integrity0.0020.004
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 head0.023
GPT teacher head0.332
Teacher spread0.309 · 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

Citations17
Published2000
Admission routes1
Has abstractyes

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