Difference image analysis (DIA)#
DIA refers to the process of image subtraction and difference-image source detection. All measurements are stored in the catalog Data products.
Key terminology:
DiaSource: a detection, positive or negative, in a single difference imageDiaObject: the astrophysical transient or variable object at a static sky coordinatelight curve : photometric measurements of a
DiaObjectas a function of time; Forced photometry should be used for light curves.
Image subtraction#
Template coadd images are warped, scaled, and PSF-matched to a visit image (also called the “direct” or “science” image), and then subtracted from the visit image to create a Difference image.
Image subtraction uses the decorrelated Alard and Lupton (1998) algorithm, as described in “Implementation of Image Difference Decorrelation” (dmtn-021.lsst.io) and in the LSST Science Pipelines documentation for the Alard-Lupton implementation.
DIA source detection#
DIA source detection refers to the process of finding regions (“footprints”) with above-threshold absolute flux in difference images, where the threshold is a signal-to-noise ratio of 5.
Difference images contain sources of residual flux from the subtraction, both positive and negative.
Real astrophysical transients, variables, and moving objects appear as sources with a flux that is equal to the difference between their flux in the template and visit images.
Spurious sources are also detected due to unavoidably imperfect template matching.
Deblending is not run on difference image sources.
The results of DIA source detection are stored in the DiaSource catalog.
Reliability score#
Both real and spurious DIA sources can be detected with a signal-to-noise ratio of 5.
Bright stars and correlated noise are the main sources of spurious detections.
An estimate of how likely a source is to be real is provided to enable filtering of DIA sources by users.
The technical note “Performance of Machine-Learned Reliability Scoring for Image Differencing” (DMTN-337) documents the architecture and performance of each model version and provides details about, e.g., the training set.
The reliability value is stored in the reliability column of the DiaSource catalog.
DP2 reliability scores were accidentally calculated with the v0.1 model. This is the same model as used for DP1.
Dipoles#
Sources with footprints containing both positive and negative peaks were fit with a dipole centroid code. Dipoles represent sources that have moved only slightly (e.g., less than the PSF) between template and visit image.
Pixel flags#
If the footprint contains one or more flagged pixels, e.g., for cosmic rays, detector edge, bad pixels, known artifacts, non-astrophysical trails, the source is also flagged (see Catalog flag columns).
DIA object association#
DIA sources are associated into DIA objects using a radius of 1 arcsecond.
The DIA objects are stored in the DiaObject catalog.
DIA source can instead be associated with a moving object (an SS object), as described in Solar System processing (SSP).
Variability characterization#
Light curve characterization parameters are calculated for all DIA objects, such as the minimum, mean, maximum, standard deviation, and slope of the difference image fluxes.
Forced photometry#
In general, “forced” photometry means a measurement made at a fixed coordinate in an image, regardless of whether an above-threshold region was detected in that particular image.
Forced PSF photometry measurements are made on all visit and difference images at the locations of all DIA objects.
The results are stored in the ForcedSourceOnDiaObject catalog.
Difference imaging in DP2 benefits from new masking features, including a SPIKE mask plane for diffraction spikes and a HIGH_VARIANCE mask plane in template detectors (see Mask planes).
Deblending on the difference image is not yet implemented, and detection and measurement with preconvolution needs further development.