A New Versatile Code for Gamma-Ray Monte-Carlo Radiative Transfer

TL;DR

This paper introduces a new Python-based Monte-Carlo radiative transfer code designed to simulate gamma-ray spectra and light curves from various supernovae and novae, aiding the interpretation of observational data from current and future gamma-ray telescopes.

Contribution

The paper presents a versatile, efficient Monte-Carlo radiative transfer code capable of modeling gamma-ray emissions from diverse astrophysical sources, with extensive testing and comparison to existing models.

Findings

Code reproduces analytic model results

Consistent with literature models

Dependence on input physics analyzed

Abstract

Ongoing MeV telescopes such as INTEGRAL/SPI and Fermi/GBM, and proposed telescopes including the recently accepted COSI and the e-ASTROGAM and AMEGO missions, provide another window in understanding transients. Their signals contain information about the stellar explosion mechanisms and their corresponding nucleosynthesis of short-lived radioactive isotopes. This raises the need of a radiative transfer code which may efficiently explore different types of astrophysical $\gamma$-ray sources and their dependence on model parameters and input physics. In view of this, we present our new Monte-Carlo Radiative Transfer code in Python. The code synthesizes the $\gamma$-ray spectra and light curves suitable for modeling supernova ejecta, including C+O novae, O+Ne novae, Type Ia and core-collapse supernovae. We test the code extensively for reproducing results consistent with analytic models. We also compare our results with similar models in the literature and discuss how our code depends on selected input physics and setting.