New imaging method shows improved accuracy in detecting MeV gamma-ray sources in cosmic nucleosynthesis, suggesting enhanced observational capabilities.
The Compton Spectrometer and Imager (COSI), scheduled for launch in 2027, will improve sensitivity for MeV gamma-ray line observations by an order of magnitude, opening new windows to study cosmic nucleosynthesis. Primary targets include the 511 keV emission from positron annihilation, ²⁶Al from stellar nucleosynthesis, and ⁴⁴Ti from supernova remnants. However, image reconstruction in this energy band presents unique challenges: Compton telescopes constrain gamma-ray directions to circles rather than points, necessitating statistical approaches for source recovery. Additionally, complex background environments require careful treatment for reliable source detection. We present an advanced image reconstruction framework implemented within the COSIpy data analysis library. Our approach extends COSIpy's capabilities by introducing a modified Richardson-Lucy algorithm with Bayesian priors optimized for MeV gamma-ray observations. The framework flexibly incorporates prior distributions for sparseness and smoothness while simultaneously optimizing background components. The modular design enables multi-dataset handling, multi-energy reconstruction, and unbinned likelihood analysis, providing a comprehensive tool for Compton telescope data analysis. We evaluate the method using simulated three-month COSI observations of key nuclear lines (⁴⁴Ti at 1.157 MeV, ²⁶Al at 1.809 MeV, and positron annihilation at 0.511 MeV). Our results demonstrate successful suppression of artifacts in point source reconstructions while preserving extended emission features. For the complex 511 keV morphology, our method achieves total flux accuracy within 10% of the true value, while conventional approaches overestimate by ~60% due to artifact amplification. This work establishes a robust foundation for MeV gamma-ray image analysis with COSI and represents an important step toward advancing our understanding of nucleosynthesis, positron annihilation, and other high-energy phenomena in future missions.
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