Solar Seismic Models and the Neutrino Predictions
Bibliographic record
Abstract
This paper focuses on the solar neutrino fluxes, the g -mode predictions, and the possible impact of the magnetic fields on the neutrino emission and transport. The Solar and Heliospheric Observatory ( SOHO ) spacecraft has allowed astrophysicists to achieve a major breakthrough in the knowledge of the solar core. Both GOLF and MDI instruments on SOHO have significantly improved the accuracy of the sound speed profile, mainly by the detection of low-degree low-order p -modes. Our study (Turck-Chièze and coworkers) has lead to precise neutrino predictions through constructing a seismic solar model that is in good agreement with the sound speed profile inferred by helioseismology in the radiative interior of the Sun. In this paper we present the details of this study and investigate new solar models validated by the acoustic modes. These new models are primarily used to derive the emitted neutrino fluxes. We show that these fluxes do not depend strongly on the modified physics as far as the model is consistent with the helioseismic observations in the core. We also show that an internal large-scale magnetic field cannot exceed a maximum strength of ≃3 × 10 7 G in the radiative zone and may increase the emitted 8 B neutrino flux only by ≃2%. All the neutrino predictions here are compatible with the Sudbury Neutrino Observatory results, assuming three neutrino flavors. We deduce the electron and neutron radial densities that are needed to calculate the neutrino oscillation properties. Finally, we discuss how the magnetic fields may influence the neutrino transport through the RSFP process, for different values of Δ m 2 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".