Energetic neutron identification with pulse shape discrimination in pure CsI crystals
Bibliographic record
Abstract
Abstract Pulse shape discrimination with pure CsI scintillators is investigated as a method for separating energy deposits by energetic neutrons and photons at particle physics experiments. Using neutron data collected near the European XFEL XS1 beam window the pulse shape discrimination capabilities of pure CsI are studied and compared to CsI(Tl) using near-identical detector setups, which were operated in parallel. The inelastic interactions of 100 MeV neutrons are observed to produce a slower scintillation emission in pure CsI relative to energy deposits from cosmic muons. By employing a charge-ratio method for pulse shape characterization, pulse shape discrimination with pure CsI is shown to be effective for identifying energy deposits from neutrons vs. cosmic muons, however, pure CsI was not able resolve the specific type of neutron inelastic interactions as can be done with CsI(Tl). Using pulse shape discrimination, the rate of energetic neutron interactions in a pure CsI detector is measured as a function of time and shown to be correlated with the European XFEL beam power. The results demonstrate that pulse shape discrimination with pure CsI has significant potential to improve electromagnetic vs. hadronic shower identification at future particle physics experiments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".