Over the last 5 years, UVIT has completed observations of more than 500 proposals with $\sim$800 unique pointings. In addition, regular planned monitoring observations have been made and from their analysis various key parameters related to in orbit performance of UVIT have been quantified. The sensitivities of the UV channels have remained steady indicating no effect of potential molecular contamination confirming the adequacy of all the protocols implemented for avoiding contamination. The quality of the PSF through the years confirms adequacy of thermal control measures. The early calibrations obtained during the Performance Verification (PV) phase have been further revised for more subtle effects. These include flat fields and detector distortions with greater precision. The operations of UVIT have also evolved through inorbit experience, e.g. tweaking of operational sequencing, protocol for recovery from bright object detection (BOD) shutdowns, parameters for BOD thresholds, etc. Finally, some effects of charged particle hits on electronics led to optimised strategy for regular resetting. The Near-UV channel was lost in one of suchoperations. All the above in-orbit experiences are presented here.

Curvit is an open-source Python package that facilitates the creation of light curves from the data collected by the Ultra-Violet Imaging Telescope (UVIT) onboard AstroSat, India’s first multi-wavelength astronomical satellite. The input to Curvit is the calibrated events list generated by the UVIT-Payload Operation Center (UVIT-POC) and made available to the principal investigators through the Indian Space Science Data Center. The features of Curvit include: (i) automatically detecting sources and generating light curves for all the detected sources and (ii) custom generation of light curve for any particular source of interest. We present here the capabilities of Curvit and demonstrate its usability on the UVIT observations ofthe intermediate polar FO Aqr as an example. Curvit is publicly available on GitHub at https://github.com/prajwel/curvit.

Performance of the Level-2 pipeline, which translates the UVIT data created by the ISRO’s ground segment processing systems (Level-1) into astronomer ready scientific data products, is described. This pipeline has evolved significantly from experiences during the in orbit mission. With time, the detectormodules of UVIT developed certain defects which led to occasional corruption of imaging and timing data. This article will describe the improvements and mitigation plans incorporated in the pipeline and report its efficacy and quantify the performance.