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Squashing Models for Optical Measurements in Quantum Communication

2008· article· en· W2963646058 on OpenAlexaff
Normand J. Beaudry, Tobias Moroder, Norbert Lütkenhaus

Bibliographic record

VenuePhysical Review Letters · 2008
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBB84Formalism (music)Mathematical proofPhysicsPhotonProtocol (science)Hilbert spaceFock spaceComputer scienceCommunications protocolQuantum cryptographyMeasurement deviceQuantum measurementQuantumQuantum mechanicsMathematicsQuantum informationComputer networkAcoustics

Abstract

fetched live from OpenAlex

Measurements with photodetectors are naturally described in the infinite dimensional Fock space of one or several modes. For some measurements, a model has been postulated which describes the full measurement as a composition of a mapping (squashing) of the signal into a small dimensional Hilbert space followed by a specified target measurement. We present a formalism to investigate whether a given measurement pair of full and target measurements can be connected by a squashing model. We show that a measurement used in the Bennett-Brassard 1984 (BB84) protocol does allow a squashing description, although the corresponding six-state protocol measurement does not. As a result, security proofs for the BB84 protocol can be based on the assumption that the eavesdropper forwards at most one photon, while the same does not hold for the six-state protocol.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0030.009
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.092
GPT teacher head0.314
Teacher spread0.222 · 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

Citations151
Published2008
Admission routes1
Has abstractyes

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