Results and Limits of Time Division Multiplexing for the BICEP Array High Frequency Receivers
Bibliographic record
Abstract
Abstract Time-Division Multiplexing is the readout architecture of choice for many groundand space experiments, as it is a very mature technology with proven outstandinglow-frequency noise stability, which represents a central challenge in multiplex-ing. Once fully populated, each of the two BICEP Array high frequency receivers,observing at 150GHz and 220/270GHz, will have 7776 TES detectors tiled on thefocal plane. The constraints set by these two receivers required a redesign of thewarm readout electronics. The new version of the standard Multi Channel Elec-tronics, developed and built at the University of British Columbia, is presentedhere for the first time. BICEP Array operates Time Division Multiplexing readouttechnology to the limits of its capabilities in terms of multiplexing rate, noise andcrosstalk, and applies them in rigorously demanding scientific application requir-ing extreme noise performance and systematic error control. Future experimentslike CMB-S4 plan to use TES bolometers with Time Division/SQUID-basedreadout for an even larger number of detectors.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".