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Record W1904188337 · doi:10.1088/0264-9381/33/3/035007

AdS/CFT and the geometry of an energy gap

2016· article· en· W1904188337 on OpenAlexfundno aff
Andrew Hickling, Toby Wiseman

Bibliographic record

VenueClassical and Quantum Gravity · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilBanff International Research Station for Mathematical Innovation and Discovery
KeywordsPhysicsScalar curvatureScalar fieldScalar (mathematics)Conformal mapAnti-de Sitter spaceCurvatureConformal field theoryMathematical physicsTheoretical physicsGeometry

Abstract

fetched live from OpenAlex

We consider a CFT defined on a static metric that is the product of time with a smooth closed space of positive scalar curvature. We expect the theory to exhibit an energy gap and our aim is to investigate how that gap depends on the geometry of the space. For a free conformal scalar it is straightforward to show the gap normalised by the minimum value of the Ricci scalar of the space is minimized when the space is a sphere. Our main result is then to show using geometric arguments that precisely the same result holds for fluctuations of a scalar operator in any holographic CFT. We prove this under the assumption that the dual vacuum geometry is a smooth Einstein metric ending only on the conformal boundary, and then consider fluctuations of a minimally coupled massive scalar field about this. We also argue the holographic CFT will have states dual to small bulk black holes whose existence is related to the energy gap. We show the thermodynamic properties of these black holes obey a bound of a similar nature to that of the scalar fluctuations—the ratio of CFT energy to a power of entropy for the states dual to black holes in the ‘small’ limit is bounded from below when appropriately normalized by the minimum Ricci scalar of the boundary space. Again the bound is saturated for a sphere.

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 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 score0.070
Threshold uncertainty score0.396

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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 teacher head, 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

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