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Record W4380995089 · doi:10.1007/jhep06(2023)052

Early Dark Energy in Type IIB String Theory

2023· article· en· W4380995089 on OpenAlexaff
Michele Cicoli, Matteo Licheri, Ratul Mahanta, Evan McDonough, Francisco G. Pedro, Marco Scalisi

Bibliographic record

VenueJournal of High Energy Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsPhysicsAxionDark energyModuliCompactification (mathematics)Theoretical physicsParticle physicsEffective field theorySuperpotentialHierarchy problemQuintessenceSupersymmetryString theoryDark matterMathematical physicsAstrophysicsQuantum mechanicsCosmology

Abstract

fetched live from OpenAlex

A bstract Early Dark Energy (EDE) is a promising model to resolve the Hubble Tension, that, informed by Cosmic Microwave Background data, features a generalization of the potential energy usually associated with axion-like particles. We develop realizations of EDE in type IIB string theory with the EDE field identified as either a C 4 or C 2 axion and with full closed string moduli stabilization within the framework of either KKLT or the Large Volume Scenario. We explain how to achieve a natural hierarchy between the EDE energy scale and that of the other fields within a controlled effective field theory. We argue that the data-driven EDE energy scale and decay constant can be achieved without any tuning of the microscopic parameters for EDE fields that violate the weak gravity conjecture, while for states that respect the conjecture it is necessary to introduce a fine-tuning. This singles out as the most promising EDE candidates, amongst several working models, the C 2 axions in LVS with 3 non-perturbative corrections to the superpotential generated by gaugino condensation on D7-branes with non-zero world-volume fluxes.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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
Published2023
Admission routes1
Has abstractyes

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