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Record W4386897341 · doi:10.1103/prxquantum.4.030338

Tailoring Three-Dimensional Topological Codes for Biased Noise

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.583

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)0.0010.000

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