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Record W4410846754 · doi:10.1117/1.jatis.11.2.026005

280-GHz aluminum MKID arrays for the Fred Young Submillimeter Telescope

2025· article· en· W4410846754 on OpenAlexaff
Anna Vaskuri, Jordan Wheeler, Jason E. Austermann, Michael R. Vissers, James A. Beall, James Burgoyne, Victoria Butler, S. C. Chapman, Steve K. Choi, A. T. Crites, Cody J. Duell, Rodrigo Freundt, Anthony I. Huber, Zachary B. Huber, Johannes Hubmayr, J. Imrek, Ben Keller, Lawrence Lin, Alicia Middleton, Michael D. Niemack, Thomas Nikola, D. Scott, Adrian K. Sinclair, Ema Smith, G. J. Stacey, Joel Ullom, Jeffrey van Lanen, Eve M. Vavagiakis, Samantha Walker, Bugao Zou

Bibliographic record

VenueJournal of Astronomical Telescopes Instruments and Systems · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersRheinische Friedrich-Wilhelms-Universität BonnUniversität zu KölnCornell University
KeywordsTelescopeSubmillimeter waveAstronomyOpticsTerahertz radiationPhysicsMaterials scienceOptoelectronicsMillimeter

Abstract

fetched live from OpenAlex

First light observations of the 280-GHz instrument module of the Fred Young Submillimeter Telescope in the CCAT Collaboration are expected in 2026. The focal plane of this module will consist of three superconducting microwave kinetic inductance detector (MKID) arrays: two aluminum-based arrays and one titanium nitride array with a similar layout. We have designed, microfabricated, assembled, and characterized a large-format aluminum-based MKID array. The responsivity of the detectors matches design expectation and scales at various optical loading levels as expected for aluminum. We have determined the internal quality factors and optical efficiency of the detectors, feedhorn beam shape, and the detector band pass. The detectors are photon noise limited with the majority of the noise being white photon noise down to 1 Hz. The array matches simulated expectations and is ready for sensitive astronomical observations for CCAT.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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