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Record W4285585921 · doi:10.1117/12.2630286

RF-ICE: large-scale gigahertz readout of frequency-multiplexed microwave kinetic inductance detectors

2022· article· en· W4285585921 on OpenAlexafffund
M. Rouble, G. Smecher, A. J. Anderson, P. S. Barry, K. R. Dibert, M. Dobbs, K. S. Karkare, J. Montgomery

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 institutionsThree-Speed Logic (Canada)Canadian Institute for Advanced ResearchMcGill University
FundersFermilabNatural Sciences and Engineering Research Council of CanadaMcGill UniversityCanadian Institute for Advanced ResearchU.S. Department of Energy
KeywordsDetectorMicrowaveMultiplexingPhysicsBandwidth (computing)Radio frequencyOptoelectronicsElectronic engineeringElectrical engineeringComputer scienceOpticsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

We present RF-ICE, a novel readout platform for microwave kinetic inductance detectors (MKIDs), optimized for use on millimeter-wavelength telescopes. The RF-ICE system extends ICE, a versatile, mature signal processing platform currently in use on telescopes around the world, into a new operational domain with MKIDs biased with gigahertz carriers. The system couples the FPGA-based ICE motherboard with a radio-frequency digitization daughterboard to enable direct digital synthesis from 0 to 6 GHz without the need for external mixing. The system operates two independent readout modules, each with 1024 frequency-multiplexed readout channels spaced across 500 MHz of carrier bandwidth. The system, which is under active development, is in operation with prototype detector wafers and will be deployed for the upcoming SPT-SLIM and SPT-3G+ experiments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

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