The Young Supernova Experiment: Survey Goals, Overview, and Operations
Research output: Contribution to journal › Journal article › peer-review
Time-domain science has undergone a revolution over the past decade, with tens of thousands of new supernovae (SNe) discovered each year. However, several observational domains, including SNe within days or hours of explosion and faint, red transients, are just beginning to be explored. Here we present the Young Supernova Experiment (YSE), a novel optical time-domain survey on the Pan-STARRS telescopes. Our survey is designed to obtain well-sampled griz light curves for thousands of transient events up to z 0.2. This large sample of transients with four-band light curves will lay the foundation for the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope, providing a critical training set in similar filters and a well-calibrated low-redshift anchor of cosmologically useful SNe Ia to benefit dark energy science. As the name suggests, YSE complements and extends other ongoing time-domain surveys by discovering fast-rising SNe within a few hours to days of explosion. YSE is the only current four-band time-domain survey and is able to discover transients as faint as similar to 21.5 mag in gri and similar to 20.5 mag in z, depths that allow us to probe the earliest epochs of stellar explosions. YSE is currently observing approximately 750 deg(2) of sky every 3 days, and we plan to increase the area to 1500 deg(2) in the near future. When operating at full capacity, survey simulations show that YSE will find similar to 5000 new SNe per year and at least two SNe within 3 days of explosion per month. To date, YSE has discovered or observed 8.3% of the transient candidates reported to the International Astronomical Union in 2020. We present an overview of YSE, including science goals, survey characteristics, and a summary of our transient discoveries to date.
|Number of pages||24|
|Publication status||Published - Feb 2021|
- Supernovae, Cosmology, Sky surveys, Transient detection