Analysis of extremely low signal-to-noise ratio data from INTEGRAL/PICsIT
Piotr Lubinski (CAMK, Isdc)

TL;DR
This paper introduces a new Bayesian-based spectral extraction method for PICsIT data, significantly improving reliability and sensitivity, enabling detection of more sources in the high-energy gamma-ray band.
Contribution
The paper presents a novel spectral extraction technique that models background and source probability within a Bayesian framework, enhancing PICsIT's data analysis capabilities.
Findings
More stable count rates for Crab with the new method
Detection of at least 8 additional sources
High-precision, unbiased spectral results in simulations
Abstract
The PICsIT detector onboard the INTEGRAL satellite was designed to provide information about emission in the soft gamma-ray band for many bright sources. Due to strong and variable instrumental background, only 4 objects have been detected so far using standard software. The moderate sensitivity of PICsIT can be compensated for in the case of many objects by adopting a long exposure time, thanks to INTEGRAL's large field of view. With angular resolution far higher than that of all other instruments operating in a similar energy band, PICsIT is suitable for fields too crowded or too significantly affected by Galactic diffuse emission. Therefore, it is desirable to improve the spectral extraction software to both obtain more reliable results and enlarge the number of objects that can be studied. The new PICsIT spectral extraction method is based on three elements: careful modelling of the…
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