The Atacama Cosmology Telescope: Quantifying atmospheric emission above Cerro Toco
Bibliographic record
Abstract
At frequencies below 1 Hz, fluctuations in atmospheric emission in the Chajnantor region in northern Chile are the primary source of interference for bolometric millimeter-wave observations. This paper focuses on characterizing the statistics of these fluctuations using measurements from the Atacama Cosmology Telescope (ACT) and the Atacama Pathfinder Experiment (APEX) water vapor radiometer. We show that the total precipitable water vapor (PWV) is not in general an accurate estimator of the level of fluctuations in millimeter-wave atmospheric emission. We also show that the microwave frequency spectrum of atmospheric fluctuations is in good agreement with predictions by the am code for frequency bands above 90 GHz. We introduce a new method for separating atmospheric and systematic fluctuations, allowing us to fit a robust atmospheric flat field, as well as to study in the atmosphere in greater detail than previous works. We present a direct measurement of the temporal outer scale of turbulence of ${\ensuremath{\tau}}_{0}\ensuremath{\approx}50\text{ }\text{ }\mathrm{s}$ corresponding to a spatial scale of ${L}_{0}\ensuremath{\approx}500\text{ }\text{ }\mathrm{m}$. Lastly, we show the variance of fluctuations in ACT's mm-wave bands correlate with the variance of fluctuations in PWV measured by APEX, even though the observatories are 6 km apart and observe different lines of sight.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".