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Record W4399663563 · doi:10.1117/12.3020522

Integration and testing of a cryogenic receiver for the Exoplanet Climate Infrared Telescope (EXCITE)

2024· article· en· W4399663563 on OpenAlexaff
Annalies Kleyheeg, Lee Bernard, Andrea Bocchieri, N. Butler, Quentin Changeat, Azzurra D'Alessandro, Billy Edwards, John Gamaunt, Qian Gong, John Hartley, Kyle Helson, Logan Jensen, Dan Kelly, Kanchita Klangboonkrong, Ed Leong, Nikole Lewis, Steven Li, Michael R. Line, Steve Maher, Ryan McClelland, Laddawan Miko, Lorenzo V. Mugnai, Peter C. Nagler, C. B. Netterfield, Vivien Parmentier, E. Pascale, Jennifer Patience, Tim Rehm, Javier Romualdez, Subhajit Sarkar, Paul A. Scowen, Greg Tucker, Augustyn Waczynski, I. Waldmann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Thermodynamic Systems and Engines
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExoplanetTelescopeInfraredRemote sensingInfrared telescopeCryogenic temperatureCryogenicsAstronomyOpticsEnvironmental sciencePhysicsAstrobiologyMaterials sciencePlanetGeology

Abstract

fetched live from OpenAlex

The EXoplanet Climate Infrared TElescope (EXCITE) is an instrument designed to measure spectroscopic phase curves of extrasolar hot Jupiters from a long duration balloon platform. EXCITE will fly a moderate resolution spectrometer housed inside of a cryogenic receiver actively cooled by two linear pulse tube cryocoolers. Here we provide the current status of the design and performance of the cryogenic receiver, its heat rejection mechanism, and associated control electronics. A recirculating methanol fluid loop rejects heat from the cryocoolers and transports it to sky-facing radiator panels mounted to the gondola. The cryocoolers are controlled by drive electronics with active vibration reduction functionality to minimize the impact of vibrations on pointing stability. We discuss the thermal and vibrational performance of the cryogenic receiver during ground-based pointing tests in its 2023 field campaign in Ft. Sumner, NM and present its current status as EXCITE prepares for its 2024 test flight campaign.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.219
Teacher spread0.205 · 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 designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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