Physics from solar neutrinos in dark matter direct detection experiments
Bibliographic record
Abstract
The next generation of dark matter direct detection experiments will be sensitive to both coherent neutrino-nucleus and neutrino-electron scattering. This will enable them to explore aspects of solar physics, perform the lowest energy measurement of the weak angle sin2 θ W to date, and probe contributions from new theories with light mediators. In this article, we compute the projected nuclear and electron recoil rates expected in several dark matter direct detection experiments due to solar neutrinos, and use these estimates to quantify errors on future measurements of the neutrino fluxes, weak mixing angle and solar observables, as well as to constrain new physics in the neutrino sector. Our analysis shows that the combined rates of solar neutrino events in second generation experiments (SuperCDMS and LZ) can yield a measurement of the pp flux to 2.5% accuracy via electron recoil, and slightly improve the 8B flux determination. Assuming a low-mass argon phase, projected tonne-scale experiments like DARWIN can reduce the uncertainty on both the pp and boron-8 neutrino fluxes to below 1%. Finally, we use current results from LUX, SuperCDMS and CDMSlite to set bounds on new interactions between neutrinos and electrons or nuclei, and show that future direct detection experiments can be used to set complementary constraints on the parameter space associated with light mediators.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".