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Record W3133568250 · doi:10.3847/1538-4365/ac0db7

The Simons Observatory Large Aperture Telescope Receiver

2021· article· en· W3133568250 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of Toronto
FundersSimons Foundation
KeywordsObservatoryTelescopeBolometerAperture (computer memory)DetectorSkyOptical telescopeCosmic microwave background

Abstract

fetched live from OpenAlex

Abstract The Simons Observatory is a ground-based cosmic microwave background experiment that consists of three 0.4 m small-aperture telescopes and one 6 m Large Aperture Telescope, located at an elevation of 5300 m on Cerro Toco in Chile. The Simons Observatory Large Aperture Telescope Receiver (LATR) is the cryogenic camera that will be coupled to the Large Aperture Telescope. The resulting instrument will produce arcminute-resolution millimeter-wave maps of half the sky with unprecedented precision. The LATR is the largest cryogenic millimeter-wave camera built to date, with a diameter of 2.4 m and a length of 2.6 m. The coldest stage of the camera is cooled to 100 mK, the operating temperature of the bolometric detectors with bands centered around 27, 39, 93, 145, 225, and 280 GHz. Ultimately, the LATR will accommodate 13 40 cm diameter optics tubes, each with three detector wafers and a total of 62,000 detectors. The LATR design must simultaneously maintain the optical alignment of the system, control stray light, provide cryogenic isolation, limit thermal gradients, and minimize the time to cool the system from room temperature to 100 mK. The interplay between these competing factors poses unique challenges. We discuss the trade studies involved with the design, the final optimization, the construction, and ultimate performance of the system.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0420.020

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 head0.012
GPT teacher head0.244
Teacher spread0.231 · 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
GenreMethods

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

Citations47
Published2021
Admission routes1
Has abstractyes

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