Sparsely Sampling the Sky: Regular vs Random Sampling
P. Paykari, S. Pires, J. -L. Starck, A. H. Jaffe

TL;DR
This paper compares regular and random sparse sampling strategies for galaxy surveys, showing that random sampling avoids periodic correlations and offers flexibility without sacrificing the accuracy of cosmological parameter estimation.
Contribution
It introduces a Bayesian experimental design approach to evaluate the effects of random sparse sampling on galaxy surveys, highlighting the advantages over regular sampling.
Findings
Random sampling distributes correlations evenly across scales.
No significant difference in constraining power between regular and random sampling.
Flexibility in sampling strategies can be adopted without compromising survey goals.
Abstract
The next generation of galaxy surveys, aiming to observe millions of galaxies, are expensive both in time and cost. This raises questions regarding the optimal investment of this time and money for future surveys. In a previous work, it was shown that a sparse sampling strategy could be a powerful substitute for the contiguous observations. However, in this previous paper a regular sparse sampling was investigated, where the sparse observed patches were regularly distributed on the sky. The regularity of the mask introduces a periodic pattern in the window function, which induces periodic correlations at specific scales. In this paper, we use the Bayesian experimental design to investigate a random sparse sampling, where the observed patches are randomly distributed over the total sparsely sampled area. We find that, as there is no preferred scale in the window function, the induced…
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