Reduction Du Bruit De Fond En Vue De La Detection De La Matiere Sombre Avec Le Projet Picasso (french Text)
Bibliographic record
Abstract
According to the new standard cosmological model ACDM (dark energy and cold dark matter), the present Universe is composed of 27% gravitational matter, of which 4% is baryonic and 23% exotic; the rest is accounted for by the so-called dark energy. One attractive candidate for the dark matter is the neutralino (χ 0), a supersymmetric particle of mass in the range 50–600 GeV, which would solve the problem of the extension of the Standard Model in particle physics. The PICASSO Project uses bubble detectors (BDs), which are made out of a gel in which thousands of carbofluoride (CxFy) droplet's are dispersed. Because of their short range, α's coming from the environment are harmless, although the natural U, Th, Ra contamination of all materials is an important background source. The purification techniques developed for the SNO detector, MnOx resins and HTiO ion exchangers, were tested and proven to have a very high efficiency (98–100%) for the removal of U, Th and Ra. A standard procedure of HTiO extraction was developed in order to measure the extremely weak activities leftover after purification. A purification criterion was established to be 10 −13 g of U,Th per g of gel in order to reach a sensitivity of 1 count/kg/d. The purification and fabrication techniques developed in this thesis have in principle the potential to reach this goal. Neutrons are the most critical background to any dark matter experiment, as their signature is the same as that for χ0's. The PICASSO setup was therefore installed in the underground environment of SNO, in Creighton mine (Sudbury, Ontario, Canada), where the neutron flux from μ spallation is reduced by 7 orders of magnitude. The setup was also surrounded by water cubes to absorb neutrons emitted from the rock by a factor of a 100. In order to prevent Rn from contaminating the BDs, a new container was designed, emanating 12 times less Rn atoms than the regular containers. A setup holding 6 BDs was installed in SNO in August 2002, with a background level 10 times smaller and an active mass 40 times greater than the previous limit published by PICASSO. The χ0 cross-section exclusion curve presented in this thesis is based on a total exposure of ∼0.5 kg·d, the best limit being 7 pb for a 30 GeV χ0. This proves the potential for PICASSO to become a major project in dark matter detection. (Abstract shortened by UMI.)
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.009 |
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".