Survey strategy optimization for the Atacama Cosmology Telescope
Bibliographic record
Abstract
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over 2000 sq. deg. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24 hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
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".