Design and testing of tuning algorithms for the E and B EXperiment (EBEX)
Bibliographic record
Abstract
Detection of B-mode polarization from the cosmic microwave background would provide compelling evidence for the inflationary paradigm and has thus become a principal goal for experimental cosmologists during the last 5-10 years. A number of high sensitivity experiments have been developed and many are under construction, including the E and B EXperiment (EBEX), a balloon-borne experiment scheduled to take data in 2010. The design of EBEX is presented here, including the scientific motivation for the experiment, and an overview of all its components, with particular attention paid to the read out electronics for its array of over 1300 biometries detectors. In the read out of such a large array of bolometers, which must be kept at ~250mK, running many signals down the same wire (i.e. multiplexing) is vital. The digital frequency multiplexing (dfmux) electronics designed and tested at McGill addresses this as well as providing the control required to tune the bolometers and super conducting quantum interference devices (SQUIDs) used in readout. How these electronics accomplish both of these goals is described with an in-depth description of the recently designed tuning algorithms required to take the detectors from initialization to fully-operational. Finally, some tests of the readout system on cold bolometers in a test cryostat are presented. These measurements are encouraging with 98% success rate of automated tuning on a test sample of 47 bolometers. Improvements to achieve a 100% success rate have been proposed and will be implemented for the upcoming integration of the bolometer camera with the telescope in November 2008. A test-flight for the experiment is planned for spring 2009, and the science flight for 2010 from Antarctica.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".