Versatile XLM72S logic module for real-time event filtering in multi-detector systems: Implementation in Compton-suppressed gamma-ray spectroscopy
Bibliographic record
Abstract
The strong interaction, one of the four fundamental interactions governing the universe, does not directly act upon nucleons and nuclei but rather on their constituent quarks. As a result, understanding how the strong interaction manifests itself at nuclear length and energy scales is a complicated process. One manner used to study this so-called nuclear interaction is to detect emitted radiation from various nuclear processes such as radioactive decay. The energy and other observables such as angular momentum of emitted radiation can provide insight into the nuclear interaction itself. Multi-detector systems increase the range of studies that can be performed both by increasing the overall efficiency and by using time-correlated measurement techniques. With multi-detector systems, however, comes an increase in complexity, size, power consumption, and cost for data acquisition systems which can process and perform logical operations on raw signals. To combat this in the Nuclear Science Laboratory at Simon Fraser University, real-time event filtering has been implemented using a user programmable logic module called XLM72S. The logic module provides 72 emitter-coupled logic ports, configurable quartet-wise as inputs or outputs, an on-board 80 MHz clock, four digital clock managers capable of synthesizing additional clock frequencies, and two serial peripheral interface memories. In the current setup, the XLM72S allows for simultaneous and computer controlled logic to be performed on up to 20 Compton Suppressed Spectrometers used for the detection of gamma rays from nuclear decays, as well as up to 4 auxiliary signals used for filtering events which have coincident particle emission. The XLM72S module has been implemented and tested for a system containing five Compton Suppressed Spectrometers and a charged particle detector, demonstrating it's effectiveness at performing logic in real time for anti-coincident Compton Suppression and coincidence multi-fold events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".