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Record W3210533671 · doi:10.1103/physrevd.105.042004

The Atacama Cosmology Telescope: Modeling bulk atmospheric motion

2022· article· en· W3210533671 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsUniversity of Toronto
FundersScience and Technology Facilities CouncilAgencia Nacional de Investigación y DesarrolloUniversidad de ConcepciónUniversity of TorontoCanada Foundation for InnovationGordon and Betty Moore FoundationPrinceton UniversityUniversity of California, Santa CruzUniversity of PennsylvaniaNational Science Foundation
KeywordsPhysicsCosmic microwave backgroundTelescopeAstrophysicsWind speedNoise (video)Atmosphere (unit)AnisotropyComputational physicsOpticsMeteorology

Abstract

fetched live from OpenAlex

Fluctuating atmospheric emission is a dominant source of noise for ground-based millimeter-wave observations of the cosmic microwave background (CMB) temperature anisotropy at angular scales $\ensuremath{\gtrsim}0.5\ifmmode^\circ\else\textdegree\fi{}$. We present a model of the atmosphere as a discrete set of emissive turbulent layers that move with respect to the observer with a horizontal wind velocity. After introducing a statistic derived from the time-lag dependent correlation function for detector pairs in an array, referred to as the pair-lag, we use this model to estimate the aggregate angular motion of the atmosphere derived from time-ordered data from the Atacama Cosmology Telescope (ACT). We find that estimates derived from ACT's CMB observations alone agree with those derived from satellite weather data that additionally include a height-dependent horizontal wind velocity and water vapor density. We also explore the dependence of the measured atmospheric noise spectrum on the relative angle between the wind velocity and the telescope scan direction. In particular, we find that varying the scan velocity changes the noise spectrum in a predictable way. Computing the pair-lag statistic opens up new avenues for understanding how atmospheric fluctuations impact measurements of the CMB anisotropy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.027
GPT teacher head0.357
Teacher spread0.330 · 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