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The Pan-STARRS telescopes on Haleakalā in Hawaii

Thousands of new cosmic explosions discovered by Young Supernova Experiment

15 March 2023

Thousands of new cosmic explosions and other astrophysical events, dozens of them discovered just days or hours after their explosion, have been revealed in the first data release from the Young Supernova Experiment (YSE), which began in 2019. The Young Supernova Experiment, which includes Penn State astrophysicist V. Ashley Villar, aims to find young and rare transient cosmic events, better understand black hole variability, and constrain the fundamental cosmological parameters of the universe by surveying more than 1,500 square degrees of sky—slightly less than 4% of the entire sky—every three days.

For the experiment, data taken with the Pan-STARRS1 telescope atop Haleakalā, Hawaii, is transferred to the University of Hawaii Information Technology Center for initial processing and calibration. Higher-level processing, detailed analysis and storage is done by computing systems at the National Center for Supercomputing Applications’ Center for AstroPhysical Surveys (CAPS) at the University of Illinois; the University of California, Santa Cruz (UCSC); and the Dark Cosmology Centre (DARK) at the Niels Bohr Institute at the University of Copenhagen. Researchers from Penn State developed algorithms to help classify the data.

“The first data release of the Young Supernova Experiment is really a testament to the power of collaboration,” said Villar, assistant professor of astronomy and astrophysics and a co-hire of the Penn State Institute for Computational and Data Science. “Our group at Penn State created one of the classification algorithms used to classify the full sample of nearly 2,000 new supernovae. This would have been impossible without spectra taken from many members of our team and a large grid of simulations from the University of Illinois.”

A paper describing the data release is accepted for publication in The Astrophysical Journal and is available online as a downloadable PDF.

Images of deep space have intrigued many a sky-gazer over the course of modern history. The first images from NASA’s Hubble Space Telescope marked a remarkable moment in space exploration and, more recently, the newly captured snapshots of deep space from the James Webb Space Telescope became a news highlight that reached well beyond typical astronomy audiences.

Astrophysicists acquire these images as part of large surveys – systematic studies of large areas of the sky over time and through different parts of the electromagnetic spectrum. These surveys can be designed for different scientific goals such as studying distant galaxies and how they have changed over the history of the universe, looking at specific regions that are especially important like the Andromeda Galaxy or looking for energetic astrophysical “transient” sources such as supernovae, tidal disruption events, and kilonovae. These transients evolve quickly, rising to a maximum and then fading away over days to months, so the Young Supernova Experiment’s regular surveys every three days are vital for capturing these events.

Map showing the fields and 1975 supernovae surveyed by the Young Supernova Experiment
The fields (polygons) and 1975 supernovae (points) surveyed by the Young Supernova Experiment (YSE) and included in Data Release 1. YSE combines its observations of over 1500 sq degrees of sky taken every 3 nights with the Pan-STARRS telescopes on Haleakalā in Hawaii with publicly available observations from other surveys to discover supernovae in the hours to days after they explode. Credit: University of Illinois, Urbana-Champaign.

"The data release is an important milestone for supernova science and a testament to the hard work of astronomers scattered across the world at all career stages – from undergraduate students to professors, pipeline scientists, observers, and more,” said Patrick Aleo, graduate fellow at the University of Illinois Urbana-Champaign (UIUC) and lead author of the study. “With further study, it will provide insights into the origin of the supernovae, the properties of their progenitor star, and the structure of their host galaxies. I am excited to see it used as a reference point for future surveys and the research that the community produces with this dataset."

It is the largest multi-band data release of nearby supernovae ever—slightly fewer than 2,000 objects—and is the first to use photometric classification and photometric redshifts—the increase in wavelength that astronomers observe when objects in space are moving away from us—extensively.  This is critical for the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time, a planned 10-year survey of the southern sky, for where there are too many objects to get spectra.

“Much of the time-domain universe is uncharted,” said Gautham Narayan, deputy director of CAPS and assistant professor at UIUC. “We still do not know the progenitor systems of many of the most common classes of transients, such as type Ia supernovae, while still using these sources to try and understand the expansion history of our universe. We’ve also seen one electromagnetic counterpart to a binary neutron star merger. There are many kinds of transients that are theoretically predicted, but have never been seen at all.”

Narayan stated that “With high-redshift experiments such as the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope about to begin operations, we saw an opportunity to establish our Young Supernova Experiment to be a low-redshift anchor. We can probe time-scales that these newer experiments cannot and find lots of transients in the nearby universe to compare to their samples in the distant universe. In particular, with this data release, we made extensive use of AI and machine learning techniques to classify the data release sample – techniques that will be crucial for Rubin and Roman.”

This groundbreaking effort could not have succeeded without the collective partnership between the University of Hawaii, UCSC, DARK, NCSA, UIUC, and Penn State. Using Hawaii’s Pan-STARRS1 telescope to collect the images, DARK’s enhanced processing of the data on its computing cluster, UCSC’s organization of the survey and data hosting, and NCSA and UIUC’s analysis – it is an outstanding achievement for multi-institution research.

“This survey is a discovery portal,” said Ryan Foley, assistant professor of astronomy and astrophysics at UCSC, who led the organization of the YSE survey project. “We are finding thousands of interesting objects, which we can then follow and study with additional observations to understand what we’re seeing.”

Mark Huber, a senior researcher at University of Hawaii’s Institute for Astronomy, and deeply involved in the YSE project said, "Pan-STARRS produces a steady stream of transient discoveries, observing large areas of the sky every clear night with two telescopes. With over a decade of observations, Pan-STARRS operates one of the best calibrated systems in astronomy with a detailed reference image of the static sky visible from Haleakalā. This enables rapid discovery and follow up of supernovae and other transient events well suited for programs like YSE to build up the sample required for analysis and this significant data release."

Director of Pan-STARRS Observatories Ken Chambers added “this collaboration with the Young Supernova Experiment makes exceptional use of Pan-STARRS’ ability to routinely survey the sky for transient phenomena and moving objects. We have provided an unprecedented sample of young supernovae discovered before their peak luminosity that will be an important resource for supernova researchers and cosmologists for many years. Looking ahead, Pan-STARRS will remain a crucial resource in the Northern Hemisphere to complement the Rubin Observatory in the Southern Hemisphere.”

In addition to Villar, the research team at Penn State includes postdoctoral scholar Conor Ransome and graduate students Kaylee De Soto and S. Karthik Yadavalli.

Media Contacts
Ashley Villar
Assistant Professor of Astronomy and Astrophysics
Sam Sholtis
Science Writer