Assessment of the Cherenkov camera alignment through Variance images for the ASTRI telescope
Simone Iovenitti, Giorgia Sironi, Enrico Giro, Alberto Segreto,, Osvaldo Catalano, Milvia Capalbi

TL;DR
This paper presents a novel method using Variance images to precisely assess the alignment of the Cherenkov camera in the ASTRI telescope, overcoming the challenge of calibration without standard star-based astrometry.
Contribution
It introduces a new technique applying Variance images for camera alignment validation in Cherenkov telescopes, achieving sub-arcsecond accuracy.
Findings
Variance images can determine camera alignment to ~1'' precision.
Star positions are estimated with sub-pixel accuracy through PSF convolution analysis.
Field rotation analysis enables high-precision alignment checks during observations.
Abstract
A peculiar aspect of Cherenkov telescopes is that they are designed to detect atmospheric light flashes on the time scale of nanoseconds, being almost blind to stellar sources. As a consequence, the pointing calibration of these instruments cannot be done in general exploiting the standard astrometry of the focal plane. In this paper we validate a procedure to overcome this problem for the case of the innovative ASTRI telescope, developed by INAF, exploiting sky images produced as an ancillary output by its novel Cherenkov camera. In fact, this instrument implements a statistical technique called "Variance method" (VAR) owning the potentiality to image the star field (angular resolution ). We demonstrate here that VAR images can be exploited to assess the alignment of the Cherenkov camera with the optical axis of the telescope down to . To this end, we evaluate the…
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