TransFit-CSM: A Fast, Physically Consistent Framework for Interaction-powered Transients

Overview

TransFit-CSM is a computational framework for modeling interaction-powered transients that self-consistently couples ejecta-circumstellar medium shock dynamics with radiative diffusion. The framework solves coupled mass-momentum equations for forward and reverse shocks alongside the diffusion equation in unshocked CSM, enabling both photon escape paths and diffusion timescales to evolve dynamically. The method reproduces characteristic observational sequences in optically thick environments and clarifies physical mechanisms underlying peak luminosity predictions.

Methods and approach

The framework numerically solves coupled hydrodynamic and radiative transfer equations with a moving heating boundary tied to shock fronts. Mass and momentum equations govern forward and reverse shock propagation while diffusion equations describe photon transport in the unshocked CSM. The approach integrates these systems self-consistently such that shock dynamics and radiative cooling are fully coupled. The method is formulated for Bayesian parameter inference, enabling extraction of ejecta and CSM physical parameters from bolometric or multiband photometric observations. Computational efficiency is prioritized to facilitate population-level analysis of large transient samples.

Key Findings

Applications to SN 2006gy and SN 2010jl produce accurate fits to observed light curves with physically interpretable posterior distributions. The models successfully reproduce the canonical sequence of early dark phases, diffusion-mediated rises and peaks, and post-interaction cooling tails. Fits demonstrate that pre-supernova mass loss history dominates the shaping of observable properties. The framework reveals why conventional Arnett-like peak rules fail in optically thick CSM regimes, providing mechanistic insight into parameter dependencies in dense circumstellar environments.

Implications

TransFit-CSM establishes a computational bridge between simple analytic prescriptions and full radiation-hydrodynamic simulations, combining computational efficiency with physical consistency. This capability enables systematic Bayesian inference across populations of interaction-powered transients, facilitating comparative analysis of ejecta-CSM properties across heterogeneous samples. The framework is positioned to leverage current and forthcoming time-domain survey data for constraining progenitor mass-loss histories and explosion properties at population scales.