Photometry Extraction

The following workflow describes how the photometry is extracted using SwiftPhotom.

Pre-extraction

  1. Input interpreting - The first steps consists in interpreting the input provided by the User (see the Input types section for more details on what is an accepted input). A list of file is then created.

  2. Checking aspect correction - Each file is checked if an aspect correction has been executed on it or not. This is done by checking the ASPCORR label in the header of each extension. An aspect corrected file will have ASPCORR=DIRECT. If this is not the case, a WARNING is printed out on the terminal, notifying that astrometry could be off. This does not necessarily mean that the astrometry will be wrong, but there is a higher chance it will be. The User must also be aware though the ASPCORR=DIRECT does not guarantee that the astrometry is going to be good either. Future improvement to the script will try to actively check and possibly correct the astrometry.

  3. Co-add multiple extensions - Some UVOT exposures will be split in multiple extension inside the same file. In order to increase the signal to noise, the script will co-add all the extensions in each file. In this way, every file will corresponds to an epoch in the final photometry. The combined filed are saved in the mid-products folder for each filter inside the reduction directory. Some Users will want to prioritize the number of epochs over the signal to noise, so this step can be skipped with the --no_combine flag. Doing so, every extension in every file will count as an epoch in the final photometry.

  4. Creating a product file - All the epochs are then appended to a single file, which will then contain all the epochs for a specific filter. This is saved as a .img file in each filter folder inside the reduction directory. This file will be redundant with all the raw data downloaded from the archive (as well as the co-added files created from the previous step), so although it is useful to have all the dataset for one filter gathered into a single file, this is definitely not memory efficient.

First extraction

Template subtraction

#RAW_TOT_RATE -> Rate from the radius in sn.reg #RAW_STD_RATE -> Rate from 5” radius #COI_STD_FACTOR -> coincidence loss factor corrected for the aperture in sn.reg #COI_TOT_RATE = COI_STD_FACTOR * RAW_TOT_RATE -> total rate coincidence-loss-corrected #COI_SRC_RATE = COI_TOT_RATE-COI_BKG_RATE*SRC_AREA -> only source, background-subtracted

#AP_COI_SRC_RATE = COI_SRC_RATE * AP_FACTOR #LSS_RATE = AP_COI_SRC_RATE / LSS_FACTOR -> large scale sensitivity #When photometry is done on coadded images the correction is not done, and a systematic uncertainty of 2.3% of the count rate is added in quadrature to the photometric error #SENSCORR_RATE = LSS_RATE * SENSCORR_FACTOR -> long-term sensitivity lost of the sensor