CCAT: design and performance of densely packed, high-frequency, dual-polarization kinetic inductance detectors for the Prime-Cam 850 GHz module
Bibliographic record
Abstract
Prime-Cam is a first-generation instrument designed for the Fred Young Submillimeter Telescope (FYST) in the Cerro Chajnantor Atacama Telescope (CCAT) Facility. Among the instrument modules being developed for the Prime-Cam receiver, the highest frequency 850 GHz module presents unique challenges in optical design, coupling, detection, and readout. The 850 GHz module will incorporate approximately 45,000 polarization-sensitive, lumped-element microwave kinetic inductance detectors (KIDs), which will represent the most KIDs on sky in a single instrument to date. We present the critical aspects of the detector design and discuss solutions to the challenges of efficient optical coupling and a multioctave readout band. Specifically, the designs will include a feature which reduces the inductance across a portion of the detectors by shorting pairs of inductor lines to allow the KIDs to be tuned across four distinct bands across the readout range, all with minimal impact to the responsivity of the detector. Thus, the resonators will be coarsely tuned via the inductance shorts, and finely tuned by etching away small portions of the interdigital capacitors. We further present a comparison between simulations and preliminary results of thermal responsivity. The results of this work will directly inform the design of microwave KIDs for the multi-octave readout architecture as part of the development of densely packed arrays for the Prime-Cam instrument.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".