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Record W4396881569 · doi:10.48550/arxiv.2405.06019

BBN catalysis by doubly charged particles

2024· preprint· en· W4396881569 on OpenAlexfundno aff
Evgeny Akhmedov, Maxim Pospelov

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCold Fusion and Nuclear Reactions
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueGovernment of CanadaU.S. Department of Energy
KeywordsCatalysisChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We consider primordial nucleosynthesis in the presence of hypothetical quasi-stable doubly charged particles. Existence of $X^{--}$ with macroscopic lifetimes will lead to the formation of its bound states with $^4$He and other light elements, significantly facilitating the subsequent formation of lithium nuclei. From observational constraints on maximum allowable amount of lithium, that we update in this work, we derive strong constraints on the abundance and lifetime of $X^{--}$. In a likely cosmological freeze-out scenario with temperatures initially exceeding the mass of $X^{--}$, the BBN constrains the lifetime of these particles to be less than about 100 seconds. For parametrically long lifetimes, lithium abundance data constrain $X^{--}$ abundance to be less than $10^{-9}$ relative to protons, regardless of whether these particles decay or remain stable. Stable particles could saturate the dark matter density only if their mass is comparable to or in excess of $10^{10}$ GeV, and most of $X^{--}$ will be found in bound states with beryllium nuclei, so that chemically they would appear as abnormally heavy helium isotopes.

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)0.002
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.054
GPT teacher head0.163
Teacher spread0.109 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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