arXiv subjects

Michael Baumer

Publications and source records attributed to Michael Baumer.

3 recordsLinked to original sources

arXiv2017

Is Flat Fielding Safe for Precision CCD Astronomy?

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand, as their foundation, precision CCD astronomy. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding--that a sensor's pixels comprise a uniform grid--invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat field images, incorporating the superposition of all electrostatic sensor effects--both known and unknown--present in flat field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat-fielding on these observables is negligible in nominal .7" seeing conditions. These errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.

astro-ph.IM↗

arXiv2015

Intrinsic Pixel Size Variation in an LSST Prototype Sensor

The ambitious science goals of the Large Synoptic Survey Telescope (LSST) have motivated a search for new and unexpected sources of systematic error in the LSST camera. Flat-field images are a rich source of data on sensor anomalies, although such effects are typically dwarfed by shot noise in a single flat field. After combining many ($\sim 500$) such images into `ultraflats' to reduce the impact of shot noise, we perform photon transfer analysis on a pixel-by-pixel basis and observe no spatial structure in pixel linearity or gain at light levels of 100 ke$^-$ and below. At 125 ke$^-$, a columnar structure is observed in the gain map--we attribute this to a flux-dependent charge transfer inefficiency. We also probe small-scale variations in effective pixel size by analyzing pixel-neighbor correlations in ultraflat images, where we observe clear evidence of intrinsic variation in effective pixel size in an LSST prototype sensor near the $\sim .3\%$ level.

astro-ph.IM↗

arXiv2015

Space Warps: I. Crowd-sourcing the Discovery of Gravitational Lenses

We describe Space Warps, a novel gravitational lens discovery service that yields samples of high purity and completeness through crowd-sourced visual inspection. Carefully produced colour composite images are displayed to volunteers via a web- based classification interface, which records their estimates of the positions of candidate lensed features. Images of simulated lenses, as well as real images which lack lenses, are inserted into the image stream at random intervals; this training set is used to give the volunteers instantaneous feedback on their performance, as well as to calibrate a model of the system that provides dynamical updates to the probability that a classified image contains a lens. Low probability systems are retired from the site periodically, concentrating the sample towards a set of lens candidates. Having divided 160 square degrees of Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging into some 430,000 overlapping 82 by 82 arcsecond tiles and displaying them on the site, we were joined by around 37,000 volunteers who contributed 11 million image classifications over the course of 8 months. This Stage 1 search reduced the sample to 3381 images containing candidates; these were then refined in Stage 2 to yield a sample that we expect to be over 90% complete and 30% pure, based on our analysis of the volunteers performance on training images. We comment on the scalability of the SpaceWarps system to the wide field survey era, based on our projection that searches of 10$^5$ images could be performed by a crowd of 10$^5$ volunteers in 6 days.

astro-ph.IM↗