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Record W1995272738 · doi:10.1007/jhep09(2010)082

Boundary entropy of supersymmetric Janus solutions

2010· article· en· W1995272738 on OpenAlexafffund
Marco Chiodaroli, Michael Gutperle, Ling-Yan Hung

Bibliographic record

VenueJournal of High Energy Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsPerimeter Institute
FundersInstitut Périmètre de physique théoriqueIndustry CanadaGovernment of CanadaNational Science Foundation
KeywordsDilatonPhysicsHolographyOrbifoldEntropy (arrow of time)TwistSupergravityMathematical physicsJanusBoundary (topology)Theoretical physicsSupersymmetryQuantum mechanicsGeometryMathematical analysisMathematics

Abstract

fetched live from OpenAlex

In this paper we compute the holographic boundary entropy for half-BPS Janus deformations of the AdS 3 × S 3 × T 4 vacuum of type IIB supergravity. Previous work [24] has shown that there are two independent deformations of this sort. In one case, the six-dimensional dilaton jumps across the interface, while the other case displays a jump of axion and four-form potential. In case of a jump of the six-dimensional dilaton, it is possible to compare the holographic result with the weak-coupling result for a two-dimensional interface CFT where the radii of the compactified bosons jump across the interface. We find exact agreement between holographic and CFT results. This is to be contrasted with the holographic calculation for the non-supersymmetric Janus solution, which agrees with the CFT result only at the leading order in the jump parameter. We also examine the implications of the holographic calculation in case of a solution with a jump in the axion, which can be associated with a deformation of the CFT by the Z 2-orbifold twist operator.

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)0.002
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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

Citations43
Published2010
Admission routes2
Has abstractyes

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