This page is designed for accessibility. Content is obtainable and functional to any browser or Internet device. This page's full visual experience is available in a graphical browser that supports web standards. Please consider upgrading your web browser.

 Supernova Early Warning System

UMD Physics Professor Presents to Astronomical Society.

Dr. Alec Habig, associate professor of physics at UMD and a scientist at the Soudan Mine Underground Laboratory (Neutrino Study) in Soudan, Minnesota, was a featured speaker at the annual meeting of the American Astronomical Society in Minneapolis, Minnesota on June 1. Habig explained the new Supernova Early Warning System (SNEWS), which is a network created by astro physicists to provide advance warning of a Supernova about to appear in our own galaxy.

Photo: Supernova remnant 1987A.
Image credit: NASA

SNEWS receives input from the neutrino experiments currently being conducted through-out the world, and will use this information to send an alert that light from a nearby supernova will be arriving at Earth in the next few hours, allowing for rapid observations of such a rare and spectacular event. A supernova, caused by the collapse of the core of a massive star, is one of the brightest events in the universe. The light from such an explosion is not seen until the resulting shock wave breaks out of the star's surface. However, the massive blast of neutrinos created by the core collapse escapes from the star immediately, preceding the light by hours.

Neutrinos are fundamental particles related to electrons. Unlike electrons, these "n" are electrically neutral and only interact weakly with matter. While this inherent "slipperiness" is what lets them escape from the exploding star so rapidly, it also makes them very hard to detect, requiring massive detectors located deep underground to shelter the subtle neutrino signal from the constant rain of cosmic rays at the surface of the Earth.

Four of these experiments send possible supernova neutrino alerts to the SNEWS network: Super-Kamiokande in Japan; the Sudbury Neutrino Observatory (SNO) in Ontario, Canada; the Large Volume Detector (LVD) in Italy; and the Antarctic Muon and Neutrino Detector Array (AMANDA). The burst of neutrinos from a supernova somewhere in our galaxy would create many neutrino inter-actions in these experiments. More distant supernovae in other galaxies are too far away to be seen in neutrinos, but one in our galaxy would be both a spectacular event and a great chance to study such an event up close. It is estimated that one such supernova should occur in our galaxy every few decades, although one has not been observed optically since 1604.

Each participating experiment sends potential supernova neutrino bursts to the SNEWS computer (hosted by Brookhaven National Lab). A real supernova will be seen in multiple experiments at the same time, while any instrumental noise or other false alarms in a single detector will not be propagated. This allows the rapid and automated distribution of the early warning to observers, who can use the advance warning to prepare to observe the impending light show from the earliest possible time.

"SNEWS will be helpful because distant supernovae are routinely observed only after they become optically bright enough to be discovered, days after the explosion itself," said Habig. "An early warning will let us watch a close-up supernova as it explodes. Now we just have to be patient and wait for a star to explode in our own galaxy, close enough to see in neutrinos."

For more information on the network, including links to the participating experiments, and a form to sign up to receive a future supernova alarm by email, see: http://snews.bnl.gov/
This work is supported by NSF Collaborative Research grants
PHY-0303196 and PHY-0302166.

For more information on Alec Habig's work at UMD, see: http://neutrino.d.umn.edu/~habig/

 

 

Written by Susan Latto. Posted July 14, 2005

Cheryl Reitan, Publications Director, creitan@d.umn.edu
NEW RELEASES, UMD media contact, Susan Latto, slatto@d.umn.edu, 218-726-8830


 

Did you find what you were looking for? YES NO