Large-scale retrospective relative spectrophotometric self-calibration in space

作者：Markovic Katarina^*; Percival Will J; Scodeggio Marco; Ealet Anne; Wachter Stefanie; Garilli Bianca; Guzzo Luigi; Scaramella Roberto; Maiorano Elisabetta; Amiaux Jerome

来源：Monthly Notices of the Royal Astronomical Society, 2017, 467(3): 3677-3698.

DOI：10.1093/mnras/stx283

• instrumentation: detectors
• methods: statistical
• cosmology: observations
• large-scale structure of Universe.

We consider the application of relative self-calibration using overlap regions to spectroscopic galaxy surveys that use slitless spectroscopy. This method is based on that developed for the Sloan Digital Sky Survey by Padmanabhan et al. in that we consider jointly fitting and marginalizing over calibrator brightness, rather than treating these as free parameters. However, we separate the calibration of the detector to detector from the full-focal-plane exposure-toexposure calibration. To demonstrate how the calibration procedure will work, we simulate the procedure for a potential implementation of the spectroscopic component of the wide Euclid survey. We study the change of coverage and the determination of relative multiplicative errors in flux measurements for different dithering configurations. We use the new method to study the case where the flat-field across each exposure or detector is measured precisely and only exposure-to-exposure or detector-to-detector variation in the flux error remains. We consider several base dither patterns and find that they strongly influence the ability to calibrate, using this methodology. To enable self-calibration, it is important that the survey strategy connects different observations with at least a minimum amount of overlap, and we propose an ' S ' pattern for dithering that fulfils this requirement. The final survey strategy adopted by Euclid will have to optimize for a number of different science goals and requirements. The large-scale calibration of the spectroscopic galaxy survey is clearly cosmologically crucial, but is not the only one. We make our simulation code public on github. com/didamarkovic/ubercal.

• 出版日期2017-6