Forecast of strongly lensed supernovae rates in the China Space Station Telescope surveys

TL;DR

This paper predicts that the China Space Station Telescope will detect over a thousand strongly lensed supernovae in ten years, significantly advancing the sample size for cosmology and stellar physics research.

Contribution

It provides the first detailed forecast of strongly lensed supernovae detection rates for the upcoming CSST survey using Monte Carlo simulations.

Findings

CSST can detect approximately 1008 strongly lensed SNe in the Wide Field Survey.

About 35% of detected events involve Type Ia supernovae.

Both surveys can contribute significantly despite not being optimized for transient detection.

Abstract

Strong gravitationally lensed supernovae (SNe) are a powerful probe for cosmology and stellar physics. The relative time delays between lensed SN images provide an independent way of measuring a fundamental cosmological parameter -- the Hubble constant -- , the value of which is currently under debate. The time delays also serve as a ``time machine'', offering a unique opportunity to capture the extremely early phase of the SN explosion, which can be used to constrain the SN progenitor and explosion mechanism. Although there are only a handful of strongly lensed SN discoveries so far, which greatly hinders scientific applications, the sample size is expected to grow substantially with next-generation surveys. In this work, we investigate the capability of detecting strongly lensed SNe with the China Space Station Telescope (CSST), a two-meter space telescope to be launched around 2026. Through Monte Carlo simulations, we predict that CSST can detect 1008.53 and 51.78 strongly lensed SNe from its Wide Field Survey (WFS, covering 17,500 deg$^2$) and Deep Field Survey (DFS, covering 400 deg$^2$) over the course of ten years. In both surveys, about 35\% of the events involve Type Ia SNe as the background sources. Our results suggest that the WFS and DFS of CSST, although not designed or optimized for discovering transients, can still make a great contribution to the strongly lensed SNe studies.