Simulation Study of Photon-to-Digital Converter (PDC) Timing Specifications for LoLX Experiment
Bibliographic record
Abstract
The Light-only Liquid Xenon (LoLX) experiment is a prototype detector aimed at studying liquid xenon (LXe) light properties and various photodetection technologies. LoLX is also aimed to quantify LXe’s time resolution as a potential scintillator for 10-ps time-of-flight positron emission tomography (TOF-PET). Another key goal of LoLX is to perform a time-based separation of Cerenkov and scintillation photons for new background rejection methods in LXe experiments. To achieve this separation, LoLX is set to be equipped with photon-to-digital converters (PDCs), a photosensor type that can provide a timestamp for each observed photon. To guide the PDC design, we explore the requirements and potential outcomes for time-based Cerenkov separation. We use a PDC simulator, whose input is the light information from the Geant4-based LoLX simulation model, and evaluate the separation quality against time-to-digital converter (TDC) parameters of the PDCs. Compared with the current filter-based approach, the simulations predict a few different configurations that offer a Cerenkov separation level increase from 50% to 66% when using PDCs and time-based separation. A separation of 65% is also achievable with just 16 TDCs for 14 400 micro-cells per PDC, or one TDC per 2.25 mm2. These simulation results will lead to a specification guide for the upcoming PDC design as well as expected results to compare against future PDC-based experimental measurements. In the longer term, the overall LoLX results will assist large LXe-based experiments and motivate the assembly of an LXe-based TOF-PET demonstrator system.
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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) | 0.000 | 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".