High-Density Photon-Noise-Limited Multi-Octave Submillimeter Kinetic Inductance Detectors for the Prime-Cam 850 GHz Module
Bibliographic record
Abstract
The Prime-Cam instrument is a first generation instrument under development for the 6-m Fred Young Submillimeter Telescope (FYST), which will be sited on Cerro Chajnantor in the Chilean Atacama Desert at an elevation of 5600 m. Among the instrument modules planned for the Prime-Cam instrument, the 850 GHz module is the highest frequency and of particular importance to the astronomical community due to the absence of near-future proposals for instruments at similar wavelengths and at equivalent sites. Success of the 850 GHz module hinges on the development of state-of-the-art detector arrays. The 850 GHz module will consist of approximately 45,000 titanium-nitride, polarization-sensitive, lumped-element kinetic inductance detectors, meaning the module will field more microwave kinetic inductance detectors than any other millimeter-wave receiver to date. The detectors are being designed to be read out using a multi-octave readout architecture, allowing for approximately double the multiplexing of other CCAT modules. We present the parameter space explored in the development of these detectors, including testing a means of shorting inductors to modify the resonance with minimal changes to the absorber architecture and testing different volumes of the inductor. Results and optical characterization of the prototype pixels for the 850 GHz instrument module are presented. The 850 GHz module is expected to be observing in 2026.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".