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Record W2593325282 · doi:10.3847/1538-4365/aae435

The EBEX Balloon-borne Experiment—Gondola, Attitude Control, and Control Software

2018· article· en· W2593325282 on OpenAlexaff
Asad M. Aboobaker, P. A. R. Ade, Derek Araujo, François Aubin, C. Baccigalupi, Chaoyun Bao, Daniel Chapman, Joy Didier, M. Dobbs, W. Grainger, Shaul Hanany, Kyle Helson, Seth Hillbrand, Johannes Hubmayr, A. H. Jaffe, Bradley R. Johnson, T. J. Jones, Jeff Klein, Andrei Korotkov, Adrian V. Lee, L. J. Levinson, M. Limon, Kevin MacDermid, Amber Miller, Michael Milligan, Lorenzo Moncelsi, E. Pascale, Kate Raach, Britt Reichborn-Kjennerud, Ilan Sagiv, C. Tucker, Gregory S. Tucker, Benjamin Westbrook, Karl Young, Kyle Zilic

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsMcGill UniversityCanadian Institute for Advanced Research
Fundersnot available
KeywordsSoftwareControl softwareControl (management)Attitude controlEnvironmental scienceAeronauticsEngineeringMarine engineeringComputer scienceAerospace engineeringOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The E and B Experiment (EBEX) was a long-duration balloon-borne instrument designed to measure the polarization of the cosmic microwave background (CMB) radiation. EBEX was the first balloon-borne instrument to implement a kilopixel array of transition edge sensor (TES) bolometric detectors and the first CMB experiment to use the digital version of the frequency domain multiplexing system for readout of the TES array. The scan strategy relied on 40 s peak-to-peak constant-velocity azimuthal scans. We discuss the unique demands on the design and operation of the payload that resulted from these new technologies and the scan strategy. We describe the solutions implemented, including the development of a power system designed to provide a total of at least 2.3 kW, a cooling system to dissipate 590 W consumed by the detectors’ readout system, software to manage and handle the data of the kilopixel array, and specialized attitude reconstruction software. We present flight performance data showing faultless management of the TES array, adequate powering and cooling of the readout electronics, and constraint of attitude reconstruction errors such that the spurious B-modes they induced were less than 10% of the CMB B-mode power spectrum with r = 0.05.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

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)0.0080.002

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 head0.005
GPT teacher head0.230
Teacher spread0.226 · 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
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

Citations34
Published2018
Admission routes1
Has abstractyes

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