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We investigate data compression schemes for proposed all-sky diffraction-limited visible/NIR sky surveys aimed at the dark-energy problem. We show that lossy square-root compression to 1 bit pixel-1 of noise, followed by standard lossless compression algorithms, reduces the images to 2.5–4 bits pixel-1, depending primarily upon the level of cosmic-ray contamination of the images. Compression to this level adds noise equivalent to ≤ 10% penalty in observing time. We derive an analytic correction to flux biases inherent to the square-root compression scheme. Numerical tests on simple galaxy models confirm that galaxy fluxes and shapes are measured with systematic biases ≲10-4 induced by the compression scheme, well below the requirements of supernova and weak gravitational lensing dark-energy experiments. In a related investigation, Vanderveld and coworkers bound the shape biases using realistic simulated images of the high-Galactic–latitude sky. The square-root preprocessing step has advantages over simple (linear) decimation when there are many bright objects or cosmic rays in the field, or when the background level will vary.
data analysis and techniques
Bernstein, G. M., Bebek, C., Rhodes, J., Stoughton, C., Vanderveld, R. A., & Yeh, P. (2010). Noise and Bias in Square-Root Compression Schemes. Retrieved from https://repository.upenn.edu/physics_papers/295
Date Posted: 28 August 2013
This document has been peer reviewed.