Modelling the Point Spread Function of ILMT images

@misc{dukiya2026modelling,
  title = {{Modelling the Point Spread Function of ILMT images}},
  author = {Naveen Dukiya and Bhavya Ailawadhi and Talat Akhunov and Monalisa Dubey and Sara Filali and Paul Hickson and Priyanshi Kumari and Gokul Singh Mehra and Kuntal Misra and Vibhore Negi and Kumar Pranshu and Jean Surdej and Sarvesh Kumar Yadav and Archana Gupta},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.14819},
  eprint = {2610.14819},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.14819},
  note = {CC BY 4.0},
}

TY  - UNPB
TI  - Modelling the Point Spread Function of ILMT images
AU  - Naveen Dukiya
AU  - Bhavya Ailawadhi
AU  - Talat Akhunov
AU  - Monalisa Dubey
AU  - Sara Filali
AU  - Paul Hickson
AU  - Priyanshi Kumari
AU  - Gokul Singh Mehra
AU  - Kuntal Misra
AU  - Vibhore Negi
AU  - Kumar Pranshu
AU  - Jean Surdej
AU  - Sarvesh Kumar Yadav
AU  - Archana Gupta
PY  - 2026
DA  - 2026/10/10
PB  - arXiv
DO  - 10.48550/arxiv.2610.14819
UR  - https://arxiv.org/abs/2610.14819
AB  - We have devised an approach to model the empirical Point Spread Function (PSF) of the images taken with the 4-meter International Liquid Mirror Telescope (ILMT). The characteristics of the ILMT PSF are influenced by the nature of the Liquid Mirror, as well as by instrument specific and atmospheric factors. As the telescope uses Time Delay Integration (TDI) mode for tracking the passing objects, the PSF varies along the declination axis due to differential motion and star-trail curvature. The 5-element optical corrector homogenizes the PSF to some degree, but does not completely eliminate the disturbing effects mentioned above. The PSF in the RA direction is changing due to the sky conditions. We show that we can successfully model the PSF of 4k×4k chunks using PSFEx, accounting for second-order X-Y variability. Our software robustly reproduces the PSF and its variation across the field.
ER  -