Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published July 10, 2018 | Published + Submitted
Book Section - Chapter Open

Testing of the LSST's photometric calibration strategy at the CTIO 0.9 meter telescope

Abstract

The calibration hardware system of the Large Synoptic Survey Telescope (LSST) is designed to measure two quantities: a telescope's instrumental response function versus wavelength and atmospheric transmission. First of all, a "collimated beam projector," which projects monochromatic light, monitored with a NIST-traceable photodiode, through a mask and a collimating optic onto the telescope, is designed to measure the instrumental response function. This method does not suffer from stray light effects and the reflections/ghosting present when using a flat-field screen illumination, which has a systematic source of uncertainty from uncontrolled reflections. It allows for an independent measurement of the throughput of the telescope's optical train as well as each filter's transmission as a function of position on the primary mirror. Second, CALSPEC stars can be used as calibrated light sources to illuminate the atmosphere and measure its transmission. To produce spectrophotometry necessary to measure the atmosphere's transfer function, we use the telescope's imager with a Ronchi grating in place of a filter to configure it as a low resolution slitless spectrograph. In this paper, we describe this calibration strategy, focusing on results from this prototype system at the Cerro Tololo Inter-American Observatory (CTIO) 0.9 meter telescope. We compare the instrumental throughput measurements to nominal values from the vendor. We describe measurements of the atmosphere made via CALSPEC standard stars during the same run.

Additional Information

© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE). MC was supported by the David and Ellen Lee Postdoctoral Fellowship at the California Institute of Technology. CWS is grateful to the DOE Office of Science for their support under award DE-SC0007881. NM is supported by National Science Foundation Graduate Research Fellowship Program, under NSF grant number DGE 1745303. NM thanks the LSSTC Data Science Fellowship Program, his time as a Fellow has benefited this work.

Attached Files

Published - 1070420.pdf

Submitted - 1806.02422.pdf

Files

1070420.pdf
Files (5.1 MB)
Name Size Download all
md5:8b52d757570666b389228c252afec8bf
2.5 MB Preview Download
md5:ced72dec633e1e2595d4c1e31c4595f4
2.5 MB Preview Download

Additional details

Created:
August 19, 2023
Modified:
January 14, 2024