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Record W3175982374 · doi:10.3847/1538-4365/ac374f

The Design and Integrated Performance of SPT-3G

2022· preprint· en· W3175982374 on OpenAlexafffund
J. A. Sobrin, A. J. Anderson, B. A. Benson, D. Dutcher, A. Foster, N. Goeckner-Wald, J. Montgomery, A. Nadolski, A. Rahlin, P. A. R. Ade, Zeeshan Ahmed, Ethan Anderes, M. Archipley, Jason E. Austermann, J. S. Avva, K. Aylor, L. Balkenhol, P. S. Barry, R. Basu Thakur, K. Benabed, F. Bianchini, L. E. Bleem, F. R. Bouchet, Lincoln Bryant, K. Byrum, J. E. Carlstrom, F. W. Carter, T. Cecil, C. L. Chang, P. Chaubal, G. Chen, H.-M. Cho, T.-L. Chou, J. F. Cliche, T. M. Crawford, A. Cukierman, C. Daley, T. de Haan, E. V. Denison, K. R. Dibert, J. Ding, M. Dobbs, W. Everett, C. Feng, K. R. Ferguson, J. Fu, S. Galli, A. E. Gambrel, R. W. Gardner, R. Gualtieri, S. Guns, N. Gupta, R. Guyser, N. W. Halverson, A. H. Harke-Hosemann, N. L. Harrington, J. W. Henning, G. C. Hilton, E. Hivon, G. P. Holder, W. L. Holzapfel, J. C. Hood, D. Howe, N. Huang, K. D. Irwin, O. B. Jeong, M. Jonas, A. Jones, Trupti Khaire, L. Knox, Anna M. Kofman, M. Korman, D. L. Kubik, S. E. Kuhlmann, C. L. Kuo, A. T. Lee, E. M. Leitch, A. E. Lowitz, C. Lu, S. S. Meyer, Daniel Michalik, M. Millea, T. Natoli, Hồ Nam Nguyễn, G. I. Noble, V. Novosad, Y. Omori, S. Padin, Z. Pan, P. Paschos, John E. Pearson, C. M. Posada, K. Prabhu, Wei Quan, C. L. Reichardt, D. Riebel, Benedikt Riedel, M. Rouble, J. E. Ruhl, B. R. Saliwanchik, J. T. Sayre, E. Schiappucci, E. Shirokoff, Graeme Smecher, A. A. Stark, J. B. Stephen, K. T. Story, A. Suzuki, C. Tandoi, K. L. Thompson, B. Thorne, C. Tucker, C. Umiltà, L. R. Vale, K. Vanderlinde, J. D. Vieira, G. Wang, N. Whitehorn, W. L. K. Wu, V. Yefremenko, K. W. Yoon, M. R. Young

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoThree-Speed Logic (Canada)Canadian Institute for Advanced ResearchMcGill University
FundersArgonne National LaboratoryNatural Sciences and Engineering Research Council of CanadaOffice of ScienceKavli FoundationAlfred P. Sloan FoundationFermilabHigh Energy PhysicsMcGill UniversityU.S. Department of EnergyUniversity of ChicagoNational Science Foundation
KeywordsCosmic microwave backgroundSouth Pole TelescopePhysicsSkyBroadbandDetectorTelescopeGalaxyPolarization (electrochemistry)OpticsCardinal pointPixelMicrowaveDual-polarization interferometryAstrophysicsMultiplexingFirst lightAnisotropyTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Abstract SPT-3G is the third survey receiver operating on the South Pole Telescope dedicated to high-resolution observations of the cosmic microwave background (CMB). Sensitive measurements of the temperature and polarization anisotropies of the CMB provide a powerful data set for constraining cosmology. Additionally, CMB surveys with arcminute-scale resolution are capable of detecting galaxy clusters, millimeter-wave bright galaxies, and a variety of transient phenomena. The SPT-3G instrument provides a significant improvement in mapping speed over its predecessors, SPT-SZ and SPTpol. The broadband optics design of the instrument achieves a 430 mm diameter image plane across observing bands of 95, 150, and 220 GHz, with 1.2′ FWHM beam response at 150 GHz. In the receiver, this image plane is populated with 2690 dual-polarization, trichroic pixels (∼16,000 detectors) read out using a 68× digital frequency-domain multiplexing readout system. In 2018, SPT-3G began a multiyear survey of 1500 deg2 of the southern sky. We summarize the unique optical, cryogenic, detector, and readout technologies employed in SPT-3G, and we report on the integrated performance of the instrument.

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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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