| Name: | Rohan Ganesh Amanaganti |
| Affiliation: | Indian Institute of Technology Bombay |
| Conference ID : | ASI2024_772 |
| Title : | Needle in a haystack: Searching for GRB-s in unbinned Time Tagged Event Data |
| Authors : | Rohan Ganesh Amanaganti 1, Varun Bhalerao 1, Surhud More 2 |
| Authors Affiliation: | 1. Department of Physics, IIT Bombay, Powai, Mumbai - 400076, India
2. Inter-University Center for Astronomy and Astrophysics, Pune, Maharashtra - 411007, India |
| Mode of Presentation: | Oral |
| Abstract Category : | Facilities, Technologies and Data science |
| Abstract : | High energy satellites like AstroSat, Daksha, etc produce Time-Tagged Event (TTE) data containing the time and energy information for each individual photon. Transients such as GRBs appear as excess photons in this event list and are typically detected by binning the data to create lightcurves. However, this approach often completely ignores the available information about energies of the photons. We present a Bayesian framework to identify the arrival time, duration and strength of potential GRBs in the unbinned data and assign them a credible detection significance. The likelihood function incorporates both the arrival times of photons and their energies through Poisson processes whose rates vary with energy according to the parametrized spectra of the GRB and background. We combine the likelihood with physically motivated and data-driven priors in order to assign a detection statistic. We quantify the purity and completeness of our detections obtained by applying the framework to an extensive set of lightcurve simulations and present comparison with existing state-of-the-art methods which neglect the differing energy spectra of the sources and the backgrounds. In this talk, I will detail the methods used and present the results obtained for the data from the CZTI instrument on AstroSat.
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