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Record W4296605489 · doi:10.1103/physrevd.107.032006

Search for Majoron-like particles with CUPID-0

2023· article· en· W4296605489 on OpenAlexaff
O. Azzolini, J. W. Beeman, F. Bellini, M. Beretta, M. Biassoni, C. Brofferio, C. Bucci, S. Capelli, V. Caracciolo, L. Cardani, P. Carniti, N. Casali, E. Celi, D. Chiesa, M. Clemenza, I. Colantoni, O. Cremonesi, A. Cruciani, A. D’Addabbo, I. Dafinei, S. Di Domizio, V. Dompè, G. Fantini, F. Ferroni, L. Gironi, A. Giuliani, P. Gorla, C. Gotti, G. Keppel, J. Kotila, M. Martínez, S.S. Nagorny, M. Nastasi, S. Nisi, C. Nones, D. Orlandi, L. Pagnanini, M. Pallavicini, L. Pattavina, M. Pavan, G. Pessina, V. Pettinacci, S. Pirro, S. Pozzi, E. Previtali, A. Puiu, A. Ressa, C. Rusconi, K. Schäffner, C. Tomei, M. Vignati, A. Zolotarova

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsQueen's University
FundersFP7 Ideas: European Research CouncilAcademy of Finland
KeywordsPhysicsParticle physicsEnergy (signal processing)BosonNeutrinoDouble beta decayCoupling (piping)Quantum mechanics

Abstract

fetched live from OpenAlex

We present the first search for the Majoron-emitting modes of the neutrinoless double $\ensuremath{\beta}$ decay ($0\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}{\ensuremath{\chi}}_{0}$) using scintillating cryogenic calorimeters. We analyzed the CUPID-0 Phase I data using a Bayesian approach to reconstruct the background sources activities, and evaluate the potential contribution of the $^{82}\mathrm{Se}$ $0\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}{\ensuremath{\chi}}_{0}$. We considered several possible theoretical models which predict the existence of a Majoron-like boson coupling to the neutrino. The energy spectra arising from the emission of such bosons in the neutrinoless double $\ensuremath{\beta}$ decay have spectral indices $n=1$, 2, 3, or 7. We found no evidence of any of these decay modes, setting a lower limit (90% of credibility interval) on the half-life of $1.2\ifmmode\times\else\texttimes\fi{}{10}^{23}\text{ }\text{ }\mathrm{yr}$ in the case of $n=1$, $3.8\ifmmode\times\else\texttimes\fi{}{10}^{22}\text{ }\text{ }\mathrm{yr}$ for $n=2$, $1.4\ifmmode\times\else\texttimes\fi{}{10}^{22}\text{ }\text{ }\mathrm{yr}$ for $n=3$ and $2.2\ifmmode\times\else\texttimes\fi{}{10}^{21}\text{ }\text{ }\mathrm{yr}$ for $n=7$. These are the best limits on the $0\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}{\ensuremath{\chi}}_{0}$ half-life of the $^{82}\mathrm{Se}$, and demonstrate the potentiality of the CUPID-0 technology in this field.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.004

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 head0.044
GPT teacher head0.480
Teacher spread0.436 · 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.

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

Citations15
Published2023
Admission routes1
Has abstractyes

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