# Type IIn Supernova Light Curves Powered by Forward and Reverse Shocks

## TL;DR

This paper develops a detailed model of Type IIn supernova light curves powered by ejecta interactions with circumstellar material, emphasizing the roles of forward and reverse shocks in energy conversion and light curve evolution.

## Contribution

It introduces a semi-analytical and radiation transfer simulation model that incorporates shock physics to better interpret supernova observations and estimate progenitor mass-loss rates.

## Key findings

- Reverse shock emission remains efficient at late phases.
- The progenitor's mass-loss rate was estimated to be higher than previous models suggested.
- The model's early-phase light curves are testable by current surveys.

## Abstract

We present a bolometric light curve model of Type IIn supernovae powered by supernova ejecta colliding with a circumstellar medium. We estimate the conversion efficiency of the ejecta's kinetic energy to radiation at the reverse and forward shocks and find that a large density contrast makes a difference in the efficiency. The emission from the reverse shock can maintain high efficiency for a long time, and becomes important at the late phase of the light curve. We first construct a semi-analytical model that is applicable to the late phase of the light curve when the diffusion time of photons in the shocked region becomes negligible. We further develop radiation transfer simulations that incorporate these physical processes into the light curve. The numerical calculations predict light curves at early phases, which are testable by present and future short-cadence surveys. We compare our model with the bolometric light curve constructed from observations for a type IIn supernova 2005ip. Due to the reduced efficiency at the forward shock, we find from our model that the mass-loss rate of the progenitor star was $\approx 1\times 10^{-2}\ {\rm M_\odot \ yr^{-1}}$ for a wind velocity of $100\ {\rm km \ s^{-1}}$, an order of magnitude higher compared to previous work that used simple assumptions of the efficiency. This highlights the importance of taking these two components into account when extracting the physical parameters from observations.