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Record W3187769770 · doi:10.21468/scipostphys.13.2.014

Conformal bootstrap bounds for the $U(1)$ Dirac spin liquid and $N=7$ Stiefel liquid

2022· article· lv· W3187769770 on OpenAlexafffund
Yin-Chen He, Junchen Rong, Ning Su

Bibliographic record

VenueSciPost Physics · 2022
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsPerimeter Institute
FundersMinistry of Colleges and UniversitiesInstitut Périmètre de physique théoriqueIndustry CanadaDeutsche ForschungsgemeinschaftEuropean CommissionEuropean Research CouncilGovernment of Canada
KeywordsPhysicsDirac operatorMathematical physicsOperator (biology)Magnetic monopoleScalingConformal mapSpin (aerodynamics)Dirac (video compression format)Quantum mechanicsMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

We apply the conformal bootstrap technique to study the U(1) U ( 1 ) Dirac spin liquid (i.e. N_f=4 N f = 4 QED _3 3 ) and the newly proposed N=7 N = 7 Stiefel liquid (i.e. a conjectured 3d non-Lagrangian CFT without supersymmetry). For the N_f=4 N f = 4 QED _3 3 , we focus on the monopole operator and ( SU(4) S U ( 4 ) adjoint) fermion bilinear operator. We bootstrap their single correlators as well as the mixed correlators between them. We first discuss the bootstrap kinks from single correlators. Some exponents of these bootstrap kinks are close to the expected values of QED _3 3 , but we provide clear evidence that they should not be identified as the QED _3 3 . By requiring the critical phase to be stable on the triangular and the kagome lattice, we obtain rigorous numerical bounds for the U(1) U ( 1 ) Dirac spin liquid and the Stiefel liquid. For the triangular and kagome Dirac spin liquid, the rigorous lower bounds of the monopole operator’s scaling dimension are 1.046 1.046 and 1.105 1.105 , respectively. These bounds are consistent with the latest Monte Carlo results.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.002

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 head0.024
GPT teacher head0.284
Teacher spread0.261 · 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

Citations28
Published2022
Admission routes2
Has abstractyes

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