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Record W2973134362 · doi:10.1063/1.5108649

Sub-Kelvin cooling for two kilopixel bolometer arrays in the PIPER receiver

2019· article· en· W2973134362 on OpenAlexaff

Bibliographic record

VenueReview of Scientific Instruments · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of British Columbia
FundersScience and Technology Facilities CouncilGoddard Space Flight CenterNational Aeronautics and Space Administration
KeywordsBolometerTelescopeGravitational waveRefrigerator carDetectorLiquid heliumAdiabatic processPlanetRefrigeration

Abstract

fetched live from OpenAlex

The Primordial Inflation Polarization Explorer (PIPER) is a balloon-borne telescope mission to search for inflationary gravitational waves from the early universe. PIPER employs two 32 × 40 arrays of superconducting transition-edge sensors, which operate at 100 mK. An open bucket Dewar of liquid helium maintains the receiver and telescope optics at 1.7 K. We describe the thermal design of the receiver and sub-Kelvin cooling with a continuous adiabatic demagnetization refrigerator (CADR). The CADR operates between 70 and 130 mK and provides ≈10 μW cooling power at 100 mK, nearly five times the loading of the two detector assemblies. We describe electronics and software to robustly control the CADR, overall CADR performance in flightlike integrated receiver testing, and practical considerations for implementation in the balloon float environment.

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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