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Record W2083178647 · doi:10.1007/jhep02(2014)103

Exact partition functions on $ \mathbb{R}{{\mathbb{P}}^2} $ and orientifolds

2014· article· en· W2083178647 on OpenAlexfundno aff
Heeyeon Kim, Sungjay Lee, Piljin Yi

Bibliographic record

VenueJournal of High Energy Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilInstitut Périmètre de physique théoriqueNational Research Foundation of KoreaNational Research Foundation
KeywordsOrientifoldHolonomyPhysicsPartition function (quantum field theory)Central chargeBraneM-theoryParity (physics)Partition (number theory)SigmaMathematical physicsCombinatoricsTheoretical physicsBrane cosmologyQuantum mechanicsSupergravityMathematicsGeometrySupersymmetryConformal map

Abstract

fetched live from OpenAlex

We consider gauged linear sigma models (GLSM) on $ \mathbb{R}{{\mathbb{P}}^2} $ , obtained from a parity projection of S 2. The theories admit squashing deformation, much like GLSM on S 2, which allows us to interpret the partition function as the overlap amplitude between the vacuum state and crosscap states. From these, we extract the central charge of Orientifold planes, and observe that the Gamma class makes a prominent appearance as in the recent D-brane counterpart. We also repeat the computation for the mirror Landau-Ginzburg theory, which naturally brings out the θ-dependence as a relative sign between two holonomy sectors on $ \mathbb{R}{{\mathbb{P}}^2} $ . We also show how our results are consistent with known topological properties of D-brane and Orientifold plane world-volumes, and discuss what part of the wrapped D-brane/Orientifold central charge should be attributed to the quantum volumes.

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)0.001
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.004
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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