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Testing Quantum States for Purity

2012· article· en· W1790537050 on OpenAlexafffund
Peter E. Jupp, Peter T. Kim, Ja‐Yong Koo, Aron Pasieka

Bibliographic record

VenueJournal of the Royal Statistical Society Series C (Applied Statistics) · 2012
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaNational Research Foundation of Korea
KeywordsMathematicsStatisticPoisson distributionStatisticsQuantum stateDeviance (statistics)QuantumStatistical physicsQuantum mechanicsPhysics

Abstract

fetched live from OpenAlex

Summary The simplest states of finite quantum systems are the pure states. The paper is motivated by the need to test statistically whether or not a given physical state is pure. Because the pure states lie in the boundary of the set of all states, the usual regularity conditions that justify the standard large sample approximations to the null distributions of the deviance and the score statistic are not satisfied. For a large class of quantum experiments that produce Poisson count data, the paper uses an enlargement of the parameter space of all states to develop likelihood ratio and score tests of purity. The asymptotic null distributions of the corresponding statistics are χ2. The tests are illustrated by the analysis of some quantum experiments involving unitarily correctable codes.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.689
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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
GenreMethods

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

Citations4
Published2012
Admission routes2
Has abstractyes

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