  Because of bright starlight leakage in coronagraphic raw images, faint
astrophysical objects such as exoplanets can only be detected using powerful
point spread function (PSF) subtraction algorithms. However, these algorithms
have strong effects on faint objects of interest, and often prevent precise
spectroscopic analysis and scattering property measurements of circumstellar
disks. For this reason, PSF-subtraction effects is currently the main
limitations to the precise characterization of exoplanetary dust with
scattered-light imaging. Forward-modeling techniques have long been developed
for point source objects. However, forward-modeling with disks is complicated
by the fact that the disk cannot be simplified using a simple point source
convolved by the PSF as the astrophysical model; all hypothetical disk
morphologies must be explored to understand the subtle and non-linear effects
of the PSF subtraction algorithm on the shape and local geometry of these
systems. Because of their complex geometries, the forward-modeling process has
to be repeated tens or hundred of thousands of times on disks with slightly
different physical properties. All of these geometries are then compared to the
PSF-subtracted image of the data, within an MCMC or a Chi-square wrapper. In
this paper, we present here DiskFM, a new open-source algorithm included in the
PSF subtraction algorithms package pyKLIP. This code allows to produce fast
forward-modeling for a variety of observation strategies (ADI, SDI, ADI+SDI,
RDI). pyKLIP has already been used for SPHERE/IRDIS and GPI data. It is readily
available on all instruments supported by pyKLIP (SPHERE/IFS, SCExAO/CHARIS),
and can be quickly adapted for other coronagraphic instruments.
