Summary
We present a modified Richardson-Lucy (RL) algorithm tailored for image reconstruction in MeV gamma-ray observations, focusing on its application to the upcoming Compton Spectrometer and Imager (COSI) mission. Our method addresses key challenges in MeV gamma-ray astronomy by incorporating Bayesian priors for sparseness and smoothness while optimizing background components simultaneously. We introduce a novel sparsity term suitable for Poisson-sampled data in addition to a smoothness prior, allowing for flexible reconstruction of both point sources and extended emission. The performance of the algorithm is evaluated using simulated three-month COSI observations of gamma-ray lines of 44 Ti (1.157 MeV), 26 Al (1.809 MeV), and positron annihilation (0.511 MeV), respectively, representing vario
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.