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Record W4399663692 · doi:10.1117/12.3020557

CCAT: detector noise limited performance of the RFSoC-based readout electronics for mm/sub-mm/far-IR KIDs

2024· article· en· W4399663692 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsUniversity of VictoriaHerzberg Institute of AstrophysicsUniversity of British Columbia
Fundersnot available
KeywordsDetectorElectronicsNoise (video)Electrical engineeringOptoelectronicsMaterials scienceComputer sciencePhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The Fred Young Submillimeter Telescope (FYST), on Cerro Chajnantor in the Atacama desert of Chile, will conduct wide-field and small deep-field surveys of the sky with more than 100,000 detectors on the Prime-Cam instrument. Kinetic inductance detectors (KIDs) were chosen as the primary sensor technology for their high density focal plane packing. Additionally, they benefit from low cost, ease of fabrication, and simplified cryogenic readout, which are all beneficial for successful deployment at scale. The cryogenic multiplexing complexity is pulled out of the cryostat and is instead pushed into the digital signal processing of the room temperature electronics. Using the Xilinx Radio Frequency System on a Chip (RFSoC), a highly multiplexed KID readout was developed for the first light Prime-Cam and commissioning Mod-Cam instruments. We report on the performance of the RFSoC-based readout with multiple detector arrays in various cryogenic setups. Specifically we demonstrate detector noise limited performance of the RFSoC-based readout under the expected optical loading conditions.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.217
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it