Abstract Details
| Name: Mani Khurana Affiliation: Bhabha Atomic Research Centre Conference ID: ASI2025_228 Title : DIOS: An Image Cleaning Method to improve MACE sensitivity Authors and Co-Authors : Mani Khurana1,2, Pradeep Chandra 2, Kuldeep Kumar Yadav 1,2 , Chinmay Borwankar 1, Krishna Kumar Singh 1,2 Abstract Type : Poster Abstract Category : Facilities, Technologies and Data science Abstract : Ground-based atmospheric Cherenkov telescopes play a crucial role in detecting very high energy (VHE) gamma rays, providing key insights into non-thermal energetic phenomena and the acceleration processes occurring under extreme astrophysical conditions. Detection of VHE $\gamma$ ray photons is inherently challenging due to the presence of huge cosmic ray background. Cosmic ray background events can mimic gamma-ray signatures, making it difficult to distinguish true VHE gamma-ray signals. Therefore, it is critical to implement a robust image cleaning that can effectively remove the cosmic ray background. Here, we present a new image cleaning method DIOS (Denoising Image of Shower) for the Major Cherenkov Atmospheric Experiment(MACE), which enhances the cleaning of the event data, improves the signal-to-noise ratio and allows for more precise measurements of the gamma rays properties. Proper image cleaning not only enhance the detection of faint gamma-ray signals but also ensures that the reconstructed images are reliable, leading to a more accurate understanding of the underlying astrophysical phenomena. This advancement due to DIOS method compared to the standard cleaning method directly leads to an increase in the sensitivity of the MACE telescope. The workings of the DIOS method and its importance will be discussed in detail. |