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Record W1978626829 · doi:10.1117/12.925658

Improved performance of TES bolometers using digital feedback

2012· article· en· W1978626829 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsThree-Speed Logic (Canada)McGill University
Fundersnot available
KeywordsMultiplexingBolometerDynamic rangeElectrical impedancePhysicsLinearityElectronic engineeringVoltageField-programmable gate arrayElectrical engineeringComputer scienceEngineeringComputer hardwareDetectorOptics

Abstract

fetched live from OpenAlex

Voltage biased, frequency multiplexed TES bolometers have become a widespread tool in mm-wave astrophysics. However, parasitic impedance and dynamic range issues can limit stability, performance, and multiplexing factors. Here, we present novel methods of overcoming these challenges, achieved through digital feedback, implemented on a Field-Programmable Gate Array (FPGA). In the first method, known as Digital Active Nulling (DAN), the current sensor (e.g. SQUID) is nulled in a separate digital feedback loop for each bolometer frequency. This nulling removes the dynamic range limitation on the current sensor, increases its linearity, and reduces its effective input impedance. Additionally, DAN removes constraints on wiring lengths and maximum multiplexing frequency. DAN has been fully implemented and tested. Integration for current experiments, including the South Pole Telescope, will be discussed. We also present a digital mechanism for strongly increasing stability in the presence of large series impedances, known as Digitally Enhanced Voltage Bias (DEVB).

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.

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 score0.159
Threshold uncertainty score0.849

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 studies0.0000.000
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 head0.227
Teacher spread0.214 · 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