Journal article
Extreme digitization for ground-based cosmic microwave background experiments
L Balkenhol, CL Reichardt
Monthly Notices of the Royal Astronomical Society | Oxford University Press (OUP) | Published : 2019
Abstract
The large size of the time ordered data of cosmic microwave background experiments presents challenges for mission planning and data analysis. These issues are particularly significant for Antarctica- and space-based experiments, which depend on satellite links to transmit data. We explore the viability of reducing the time ordered data to few bit numbers to address these challenges. Unlike lossless compression, few bit digitisation introduces additional noise into the data. We present a set of one, two, and three bit digitisation schemes and measure the increase in noise in the cosmic microwave background temperature and polarisation power spectra. The digitisation noise is independent of a..
View full abstractRelated Projects (2)
Grants
Awarded by U.S. Department of Energy
Funding Acknowledgements
We are indebted to Nathan Whitehorn for the details about SPT data compression provided by him We are grateful for insightful discussions about the prospects of extreme digitization for CMB experiments with Andrew Melatos and Patrick Clearwater. We thank the referee as well as Nikhel Gupta, Srinivasan Raghunathan, Federico Bianchini, Andrew Melatos, and Patrick Clearwater for valuable feedback on the manuscript. We acknowledge support from an Australian Research Council Future Fellowship (FT150100074), and also from the University of Melbourne. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC.02-05CH11231. We acknowledge the use of the Legacy Archive for Microwave Background Data Analysis (LAMBDA). Support for LAMBDA is provided by the NASA Office of Space Science. This research made use of the NUMPY (Travis H. Oliphant 2006), SCIPY (Jones et al. 2001), MATPLOTLIB (Hunter 2007), and ASTROPY (Astropy Collaboration et al. 2013) packages.