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Record W2503736762 · doi:10.1117/12.2232190

CryoPAF4: a cryogenic phased array feed design

2016· article· en· W2503736762 on OpenAlexaff
Lisa Locke, Dominic Garcia, Mark Halman, Doug Henke, Gary Hovey, Nianhua Jiang, L. B. G. Knee, Gordon Lacy, David Loop, M. P. Rupen, B. Veidt, Ramunas Wierzbicki

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsNoise temperatureOpticsPhased arrayAmplifierRadio telescopeRadio astronomyCryogenicsPhysicsAcousticsAntenna (radio)Materials scienceElectrical engineeringEngineeringBandwidth (computing)Phase noiseTelecommunications

Abstract

fetched live from OpenAlex

Phased array feed (PAF) receivers used on radio astronomy telescopes offer the promise of increased fields of view while maintaining the superlative performance attained with traditional single pixel feeds (SPFs). However, the much higher noise temperatures of room temperature PAFs compared to cryogenically-cooled SPFs have prevented their general adoption. Here we describe a conceptual design for a cryogenically cooled 2.8 – 5.18 GHz dual linear polarization PAF with estimated receiver temperature of 11 K. The cryogenic PAF receiver will comprise a 140 element Vivaldi antenna array and low-noise amplifiers housed in a 480 mm diameter cylindrical dewar covered with a RF transparent radome. A broadband two-section coaxial feed is integrated within each metal antenna element to withstand the cryogenic environment and to provide a 50 ohm impedance for connection to the rest of the receiver. The planned digital beamformer performs digitization, frequency band selection, beam forming and array covariance matrix calibration. Coupling to a 15 m offset Gregorian dual-reflector telescope, cryoPAF4 can expect to form 18 overlapping beams increasing the field of view by a factor of ~8x compared to a single pixel receiver of equal system temperature.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.384
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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 teacher head, 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicRadio Astronomy Observations and TechnologyFrench-language works237,207