TES imaging array technology for C ℓ OVER
Bibliographic record
Abstract
CℓOVER is an experiment which aims to detect the signature of gravitational waves from inflation by measuring the B-mode polarization of the cosmic microwave background. CℓOVER consists of three telescopes operating at 97, 150, and 220 GHz. The 97-GHz telescope has 160 horns in its focal plane while the 150 and 220-GHz telescopes have 256 horns each. The horns are arranged in a hexagonal array and feed a polarimeter which uses finline-coupled TES bolometers as detectors. To detect the two polarizations the 97-GHz telescope has 320 detectors while the 150 and 220-GHz telescopes have 512 detectors each. To achieve the required NEPs the detectors are cooled to 100 mK for the 97 and 150-GHz polarimeters and 230 mK for the 220-GHz polarimeter. Each detector is fabricated as a single chip to guarantee fully functioning focal planes. The detectors are contained in linear modules made of copper which form split-block waveguides. The detector modules contain 16 or 20 detectors each for compatibility with the hexagonal arrays of horns in the telescopes' focal planes. Each detector module contains a time-division SQUID multiplexer to read out the detectors. Further amplification of the multiplexed signals is provided by SQUID series arrays. The first prototype detectors for CℓOVER operate with a bath temperature of 230 mK and are used to validate the detector design as well as the polarimeter technology. We describe the design of the CℓOVER detectors, detector blocks, and readout, and give an update on the detector development.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.082 | 0.038 |
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".