Shear Analysis For LSST Cuts To The Chase

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In its quest to understand dark energy - and many other enigmas of our Universe - the Large Synoptic Survey Telescope (LSST) will focus ten times more light than any other telescope and require SLAC to produce the largest digital camera ever constructed. Truly honing in on dark energy, however, requires much more than such impressive hardware. In order to precisely characterize dark energy, LSST will, among other techniques, use the subtle patterns in the shapes of up to a billion galaxies to map out the effect of weak gravitational lensing of galaxy light over the history of the Universe.

These shape patterns are referred to as "cosmic shear". Understanding such subtle patterns is one of the most challenging aspects of LSST's mission. The observed shapes of galaxies are the result of the combined effects of their actual intrinsic shapes, the effects of weak gravitational lensing due to structure between the galaxies and Earth, distortions created by light travelling through our atmosphere, and distortions created by light travelling through the telescopes mirrors, lenses, filters, and CCD detectors. The full systematic impact of all of the atmospheric and optics effects on the measured shape - the so-called 'point spread function' or PSF - must be thoroughly understood in order to deduce the weak lensing and dark energy parameters, and this represents one of the most fundamental challenges of LSST dark energy science, as well as that from smaller-scale projects such as the Dark Energy Survey.

An important step toward that understanding has been taken with recently presented work led by KIPAC graduate student Chihway Chang, along with Professor Steven Kahn, and scientists Kirk Gilmore, Andrew Rasmussen, and Marina Shmakova, along with colleagues from several other institutions. Chang, Kahn, and collaborators quantified the statistical properties of the systematic errors induced into shear measurements due to atmospheric and optics effects, and pointed toward strategies for minimizing their impact. A crucial tool was software pipeline known as the Photon Simulator or PhoSim - a part of the LSST Image Simulator system that was developed by scientists at KIPAC and elsewhere - that imprints the atmospheric, optics, and detector effects of the LSST system onto incoming light rays.

The analysis finds that the main additive systematic error on shear measurements comes from an inability to adequately characterize the atmospheric portion of the PSF due to its spatial variation on small scales. Essentially the atmosphere distorts the light over small angles in a way that is more complicated than current techniques to model the PSF can handle. They then apply an analysis scheme to derive dark energy parameters from 10 years worth of their simulated data that is currently being developed for real LSST sky data, and find that the resulting systematic errors from this small scale atmospheric-induced PSF variation are at a level comparable with the statistical errors, if the small scale PSF variations can be at least partially modeled in the data analysis procedure. This is good news in that it suggests that atmospheric-induced PSF effects will not fundamentally limit LSST's ability to characterize dark energy.

But to maximize the benefit of LSST's weak lensing measurements for dark energy science, the team's results call for better techniques for modeling small-scale PSF than are currently employed in such analysis algorithms. Motivated by these results, Chang and other scientists have developed a new algorithm based on maximum entropy data fitting methods to more adequately model the PSF variations over small angles, which will be the subject of a future KIPAC research highlight.

This work is described a paper submitted to the Monthly Notices of the Royal Astronomical Society and available from astro-ph at arXiv:1206.1378. Research at KIPAC is supported by the Department of Energy, the Kavli Foundation, the National Aeronautics and Space Administration, the National Science Foundation and Stanford University, as well as private donors. We are grateful to each of these sponsors for their trust and support.

Science Contact:
Chihway Chang
KIPAC
email: chihway@stanford.edu

Tidbit Author: Jack Singal