5 research outputs found
Control and systems software for the Cosmology Large Angular Scale Surveyor (CLASS)
The Cosmology Large Angular Scale Surveyor (CLASS) is an array of
polarization-sensitive millimeter wave telescopes that observes ~70% of the sky
at frequency bands centered near 40GHz, 90GHz, 150GHz, and 220GHz from the
Atacama desert of northern Chile. Here, we describe the architecture of the
software used to control the telescopes, acquire data from the various
instruments, schedule observations, monitor the status of the instruments and
observations, create archival data packages, and transfer data packages to
North America for analysis. The computer and network architecture of the CLASS
observing site is also briefly discussed. This software and architecture has
been in use since 2016, operating the telescopes day and night throughout the
year, and has proven successful in fulfilling its design goals.Comment: 19 pages, 8 figures, to appear in Proc. SPI
Two Year Cosmology Large Angular Scale Surveyor (CLASS) Observations: Long Timescale Stability Achieved with a Front-End Variable-delay Polarization Modulator at 40 GHz
The Cosmology Large Angular Scale Surveyor (CLASS) is a four-telescope array
observing the largest angular scales () of the
cosmic microwave background (CMB) polarization. These scales encode information
about reionization and inflation during the early universe. The instrument
stability necessary to observe these angular scales from the ground is achieved
through the use of a variable-delay polarization modulator (VPM) as the first
optical element in each of the CLASS telescopes. Here we develop a demodulation
scheme used to extract the polarization timestreams from the CLASS data and
apply this method to selected data from the first two years of observations by
the 40 GHz CLASS telescope. These timestreams are used to measure the
noise and temperature-to-polarization () leakage present in the
CLASS data. We find a median knee frequency for the pair-differenced
demodulated linear polarization of 15.12 mHz and a leakage of
(95\% confidence) across the focal plane. We examine the
sources of noise present in the data and find the component of due
to atmospheric precipitable water vapor (PWV) has an amplitude of for 1 mm of PWV when evaluated at 10 mHz;
accounting for of the noise in the central pixels of the focal
plane. The low level of leakage and noise achieved
through the use of a front-end polarization modulator enables the observation
of the largest scales of the CMB polarization from the ground by the CLASS
telescopes.Comment: Submitted to Ap
CLASS Data Pipeline and Maps for 40 GHz Observations through 2022
The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background over 75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. This paper describes the CLASS data pipeline and maps for 40 GHz observations conducted from 2016 August to 2022 May. We demonstrate how well the CLASS survey strategy, with rapid (∼10 Hz) front-end modulation, recovers the large-scale Galactic polarization signal from the ground: the mapping transfer function recovers ∼67% (85%) of EE and BB ( VV ) power at ℓ = 20 and ∼35% (47%) at ℓ = 10. We present linear and circular polarization maps over 75% of the sky. Simulations based on the data imply the maps have a white noise level of and correlated noise component rising at low- ℓ as ℓ ^−2.4 . The transfer-function-corrected low- ℓ component is comparable to the white noise at the angular knee frequencies of ℓ ≈ 18 (linear polarization) and ℓ ≈ 12 (circular polarization). Finally, we present simulations of the level at which expected sources of systematic error bias the measurements, finding subpercent bias for the Λ cold dark matter EE power spectra. Bias from E -to- B leakage due to the data reduction pipeline and polarization angle uncertainty approaches the expected level for an r = 0.01 BB power spectrum. Improvements to the instrument calibration and the data pipeline will decrease this bias