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Record W4366548587 · doi:10.1007/jhep04(2023)075

The Panorama of Spin Matrix theory

2023· article· en· W4366548587 on OpenAlexfundno aff
Stefano Baiguera, Troels Harmark, Yang Lei

Bibliographic record

VenueJournal of High Energy Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsUniversity of Chinese Academy of SciencesAzrieli FoundationIsrael Science Foundation
KeywordsPhysicsPanoramaMatrix (chemical analysis)Theoretical physicsSpin (aerodynamics)Matrix modelParticle physics

Abstract

fetched live from OpenAlex

A bstract Spin Matrix theory describes near-BPS limits of $$ \mathcal{N} $$ N = 4 SYM theory, which enables us to probe finite N effects like D-branes and black hole physics. In previous works, we have developed the spherical reduction and spin chain methods to construct Spin Matrix theory for various limits. In this paper, by considering a supercharge $$ \mathcal{Q} $$ Q which is cubic in terms of the letters, we construct the Hamiltonian of the largest Spin Matrix theory of $$ \mathcal{N} $$ N = 4 SYM, called the PSU(1 , 2|3) Spin Matrix theory, as $$ H=\left\{\mathcal{Q},{\mathcal{Q}}^{\dagger}\right\} $$ H = Q Q † . We show the resulting Hamiltonian is automatically positive definite and manifestly invariant under supersymmetry. The Hamiltonian is made of basic blocks which transform as supermultiplets. A novel feature of this Hamiltonian is its division into D-terms and F-terms that are separately invariant under PSU(1 , 2|3) symmetry and positive definite. As all the other Spin Matrix theories arising from $$ \mathcal{N} $$ N = 4 SYM can be acquired by turning off certain letters in the theory, we consider our work as revealing the “Panorama” of Spin Matrix theory.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.006
GPT teacher head0.239
Teacher spread0.233 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of High Energy Physics→Same topicBlack Holes and Theoretical Physics→French-language works237,207→