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Record W4294132375 · doi:10.1117/12.2629766

ALMA band-1 receiver: first light, performance, and road to completion

2022· article· en· W4294132375 on OpenAlexaff
Teddy Huang, Yuh-Jing Hwang, Chau-Ching Chiong, Hsi-Wei Yen, Patrick M. Koch, Chi-Den Huang, Bill Liu, Cheng Lin Chen, Jwu Jiunn Tsai, Wei-Ling Hsiung, Li-Pin Chi, Chin-Ting Ho, Chao-Chin Wang, Chen Chien, You‐Hua Chu, Paul T. P. Ho, F. Kemper, Álvaro González, Satoru Iguchi, Yoshi Uzawa, Daisuke Iono, Hiroshi Nagai, John Effland, Kamaljeet Saini, M.W. Pospieszalski, Doug Henke, K. Yeung, Ricardo Finger, Valeria Tapia, Nicolás Reyes, G. Siringo, G. Marconi, Rodrigo Cabezas

Bibliographic record

VenueMillimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XI · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsMillimeterRedshiftSubmillimeter ArrayPhysicsComputer scienceAstronomyRemote sensingGeologyGalaxy

Abstract

fetched live from OpenAlex

The Atacama large millimeter/submillimeter array (ALMA) band-1 receiver covers the frequency band between 35-50 GHz. An extension of up to 52 GHz is on a best-effort basis. Covering the longest wavelengths visible with ALMA, this receiver is enabling studies of dust grain evolution in proto-planetary systems probing dust grain sizes close to 1 cm, and with multiple red-shifted molecular lines it will open up a new window in the high-redshift universe. The band-1 project has recently achieved first light and with this passed a major project milestone. We present the challenges, from initial development to prototype, to establishing the infrastructure, integration, and evaluation of 73 production receiver units, and to the final tasks to complete the project. We conclude with the initial performance and characterization of the first band-1 receivers installed on ALMA.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.222
Teacher spread0.210 · 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.

Study designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMillimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XISame topicSuperconducting and THz Device TechnologyFrench-language works237,207