MétaCan
Menu
Back to cohort
Record W4386897341 · doi:10.1103/prxquantum.4.030338

Tailoring Three-Dimensional Topological Codes for Biased Noise

2023· article· en· W4386897341 on OpenAlexafffund
Eric J. Huang, Arthur Pesah, Christopher T. Chubb, Michael Vasmer, Arpit Dua

Bibliographic record

VenuePRX Quantum · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversité de SherbrookeUniversity of WaterlooPerimeter Institute
FundersGovernment of CanadaInstitute for Quantum Information and Matter, California Institute of TechnologyMinistry of Colleges and UniversitiesEngineering and Physical Sciences Research CouncilEidgenössische Technische Hochschule ZürichNational Centres of Competence in Research SwissMAPSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science FoundationInstitut Périmètre de physique théoriqueNational Science Foundation of Sri LankaInnovation, Science and Economic Development CanadaSimons Foundation
KeywordsNoise (video)Topology (electrical circuits)Noise reductionMathematicsReduction (mathematics)Pauli exclusion principleComputer sciencePhysicsCombinatoricsQuantum mechanicsAcousticsArtificial intelligenceGeometry

Abstract

fetched live from OpenAlex

A weight-reduction technique allows the tailoring of various three-dimensional topological codes for enhanced storage performance and demystifies the occurrence of a 50 percent threshold for infinitely biased Pauli noise.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.272
Teacher spread0.237 · 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

Citations18
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePRX QuantumSame topicQuantum and electron transport phenomenaFrench-language works237,207