MétaCan
Menu
Back to cohort
Record W2037099667 · doi:10.1103/physreva.70.052306

Quantum state targeting

2004· article· en· W2037099667 on OpenAlexaff
Terry Rudolph, Robert W. Spekkens

Bibliographic record

VenuePhysical Review A · 2004
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsPerimeter Institute
Fundersnot available
KeywordsComputer scienceQuantum cryptographyCoin flippingCryptographyTheoretical computer scienceState (computer science)Context (archaeology)GeneralizationQuantumProtocol (science)Computer securityIdentity (music)Task (project management)Quantum stateFidelityQuantum informationMathematicsQuantum mechanicsAlgorithmPhysics

Abstract

fetched live from OpenAlex

We introduce a primitive for quantum cryptography that we term ``state targeting.'' We show that increasing one's probability of success in this task above a minimum amount implies an unavoidable increase in the probability of a particular kind of failure. This is analogous to the unavoidable disturbance to a quantum state that results from gaining information about its identity, and can be shown to be a purely quantum effect. We solve various optimization problems for state targeting that are useful for the security analysis of two-party cryptographic tasks implemented between remote antagonistic parties. Although we focus on weak coin flipping, the results are significant for other two-party protocols, such as strong coin flipping, partially binding and concealing bit commitment, and bit escrow. Furthermore, the results have significance not only for the traditional notion of security in cryptography, that of restricting a cheater's ability to bias the outcome of the protocol, but also for a different notion of security that arises only in the quantum context, that of cheat sensitivity. Finally, our analysis leads to some interesting secondary results, namely, a generalization of Uhlmann's theorem and an operational interpretation of the fidelity between two mixed states.

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 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 score0.942
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.283
Teacher spread0.270 · 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.

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

Citations14
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review ASame topicQuantum Information and CryptographyFrench-language works237,207