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تسجيل مستخدم جديدSPIRE Map-Making Test Report
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The photometer section of SPIRE is one of the key instruments on board of Herschel. Its legacy depends very much on how well the scanmap observations that it carried out during the Herschel mission can be converted to high quality maps. In order to have a comprehensive assessment on the current status of SPIRE map-making, as well as to provide guidance for future development of the SPIRE scan-map data reduction pipeline, we carried out a test campaign on SPIRE map-making. In this report, we present results of the tests in this campaign.
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We present a description of the data reduction and mapmaking pipeline used for the 2008 observing season of the Atacama Cosmology Telescope (ACT). The data presented here at 148 GHz represent 12% of the 90 TB collected by ACT from 2007 to 2010. In 20
08 we observed for 136 days, producing a total of 1423 hours of data (11 TB for the 148 GHz band only), with a daily average of 10.5 hours of observation. From these, 1085 hours were devoted to a 850 deg^2 stripe (11.2 hours by 9.1 deg) centered on a declination of -52.7 deg, while 175 hours were devoted to a 280 deg^2 stripe (4.5 hours by 4.8 deg) centered at the celestial equator. We discuss sources of statistical and systematic noise, calibration, telescope pointing, and data selection. Out of 1260 survey hours and 1024 detectors per array, 816 hours and 593 effective detectors remain after data selection for this frequency band, yielding a 38% survey efficiency. The total sensitivity in 2008, determined from the noise level between 5 Hz and 20 Hz in the time-ordered data stream (TOD), is 32 micro-Kelvin sqrt{s} in CMB units. Atmospheric brightness fluctuations constitute the main contaminant in the data and dominate the detector noise covariance at low frequencies in the TOD. The maps were made by solving the least-squares problem using the Preconditioned Conjugate Gradient method, incorporating the details of the detector and noise correlations. Cross-correlation with WMAP sky maps, as well as analysis from simulations, reveal that our maps are unbiased at multipoles ell > 300. This paper accompanies the public release of the 148 GHz southern stripe maps from 2008. The techniques described here will be applied to future maps and data releases.
CCAT is a large submillimetre telescope to be built near the ALMA site in northern Chile. A large-format KID camera, with up to 48,000 detectors at a single waveband sampled at about 1 kHz, will have a data rate about 50 times larger than SCUBA-2, th
e largest existing submillimetre camera. Creating a map from this volume of data will be a challenge, both in terms of memory and processing time required. We investigate how to extend SMURF, the iterative map-maker used for reducing SCUBA-2 observations, to a distributed-node parallel system, and estimate how the processing time scales with the number of nodes in the system.
Map-making is an important step for the data analysis of Cosmic Microwave Background (CMB) experiments. It consists of converting the data, which are typically a long, complex and noisy collection of measurements, into a map, which is an image of the
observed sky. We present in this paper a new map-making code named PICASSO (Polarization and Intensity CArtographer for Scanned Sky Observations), which was implemented to construct intensity and polarization maps from the Multi Frequency Instrument (MFI) of the QUIJOTE (Q-U-I Joint TEnerife) CMB polarization experiment. PICASSO is based on the destriping algorithm, and is suited to address specific issues of ground-based microwave observations, with a technique that allows the fit of a template function in the time domain, during the map-making step. This paper describes the PICASSO code, validating it with simulations and assessing its performance. For this purpose, we produced realistic simulations of the QUIJOTE-MFI survey of the northern sky (approximately $sim 20,000,$deg$^2$), and analysed the reconstructed maps with PICASSO, using real and harmonic space statistics. We show that, for this sky area, PICASSO is able to reconstruct, with high fidelity, the injected signal, recovering all the scales with $ell>10$ in TT, EE and BB. The signal error is better than 0.001% at $20<ell<200$. Finally, we validated some of the methods that will be applied to the real wide-survey data, like the detection of the CMB anisotropies via cross-correlation analyses. Despite that the implementation of PICASSO is specific for QUIJOTE-MFI data, it could be adapted to other experiments.
We present a Gibbs sampling solution to the map-making problem for CMB measurements, building on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps; noise filtering and map binn
ing. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods, and allows us for the first time to bring the destriping baseline length to a single sample. We apply the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we may compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction, and this methodology forms the conceptual basis for the map-making algorithm employed in the BeyondPlanck framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations.
With the temperature power spectrum of the cosmic microwave background (CMB) at least four orders of magnitude larger than the B-mode polarisation power spectrum, any instrumental imperfections that couple temperature to polarisation must be carefull
y controlled and/or removed. Here we present two new map-making algorithms that can create polarisation maps that are clean of temperature-to-polarisation leakage systematics due to differential gain and pointing between a detector pair. Where a half wave plate is used, we show that the spin-2 systematic due to differential ellipticity can also by removed using our algorithms. The algorithms require no prior knowledge of the imperfections or temperature sky to remove the temperature leakage. Instead, they calculate the systematic and polarisation maps in one step directly from the time ordered data (TOD). The first algorithm is designed to work with scan strategies that have a good range of crossing angles for each map pixel and the second for scan strategies that have a limited range of crossing angles. The first algorithm can also be used to identify if systematic errors that have a particular spin are present in a TOD. We demonstrate the use of both algorithms and the ability to identify systematics with simulations of TOD with realistic scan strategies and instrumental noise.
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