Nearby Supernova Factory Churns Out Discoveries
When the Supernova Cosmology Project got up to speed in the mid-1990s, its team of astrophysicists, led by Saul Perlmutter of Lawrence Berkeley National Laboratory, were looking forward to finally getting decent measurements of how much the expansion of the Universe was slowing down.
The team had figured out how to accelerate the discovery of Type Ia supernovae by systematically searching the same patches of sky at intervals, then subtracting the images from one another, following up with more detailed measurements of the remaining bright spots. By comparing the distance of these exploding stars (which all have the same intrinsic brightness) with the redshifts of their home galaxies, researchers could calculate how fast the Universe was expanding at different times in its history.
As so often happens in science and in life, things did not turn out as expected. The researchers got their high-quality measurements all right, but the data showed that the expansion of the Universe was speeding up, not slowing down as everyone had assumed. The data were analyzed on NERSC computers using different sets of cosmological assumptions, but the results were inescapable. And Australia’s High-z Supernova Search Team, working independently, had reached the same conclusion.
So in 1998, the two teams of researchers made the startling announcement that the expansion of the Universe is accelerating. Before long a new term entered the vocabulary of astrophysics: dark energy, the unknown force driving the expansion, which accounts for about two-thirds of the total energy density in the Universe. To find out what dark energy is, scientists need more detailed measurements of the Universe’s expansion history. Thus they need even more observations of Type Ia supernovae, and they need to reduce some remaining uncertainty about the uniform brightness of these exploding stars.
Reducing the uncertainty and improving the calibration of Type Ia supernovae are among the chief goals of the Nearby Supernova Factory (SNfactory), a spinoff of the Supernova Cosmology Project, led by Berkeley Lab physicist Greg Aldering. At present, astronomers can determine the distance to a well-studied Type Ia supernova with an accuracy of 5 percent, an accuracy the SNfactory expects to improve. “Our motive is to establish a much better sample of nearby Type Ia supernovae, against which the brightness of distant supernovae can be compared to obtain relative distances,” says Aldering.
What researchers want to measure, says Aldering, also includes “the intrinsic colors of a Type Ia at every stage, so we’ll know the effects of intervening dust. And we want to know what difference the ‘metallicity’ of the home galaxy makes—that is, the presence of elements heavier than helium.”
To accomplish these goals, the SNfactory needs to discover and make detailed observations of 300 to 600 low-redshift supernovae, many more than have been studied so far. Automation and tight coordination of the search and follow-up stages are absolutely essential to achieving these numbers. During its first year of operation, the SNfactory found 34 supernovae. “This is the best performance ever for a ‘rookie’ supernova search,” Aldering says. “In our second year, we have shown we can discover supernovae at the rate of nine a month, a rate other searches have reached only after years of trying.”
This remarkable discovery rate is made possible by a high-speed data link, custom data pipeline software, and NERSC’s data handling and storage capacity. So far the SNfactory has processed a quarter-million images and archived 6 terabytes (trillion bytes) of compressed data at NERSC—one of the few centers with an archive large enough to store this much data. “The SNfactory owes much of its success to NERSC’s ability to store and process the vast amounts of data that flow in virtually every night,” says Aldering.
The SNfactory’s custom-developed data pipeline software, developed by UC Berkeley graduate student Michael Wood-Vasey, manages up to 50 gigabytes (billion bytes) of data each night from wide-field cameras built and operated by the Jet Propulsion Laboratory’s Near Earth Asteroid Tracking program (NEAT). NEAT uses remote telescopes at Mount Palomar Observatory in Southern California and at the U.S. Air Force’s Maui Space Surveillance System on Mount Haleakala.
With the help of the High Performance Wireless Research and Education Network (HPWREN) program at the San Diego Supercomputer Center (SDSC), the SNfactory was able to establish a custom-built, high-speed link with Mount Palomar (Figure 6). Existing links to Maui and to SDSC through the DOE’s Energy Sciences Network (ESnet) complete the connection to NERSC.
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| Figure 6 |
NEAT sends images of about 500 square degrees of the sky to NERSC each night. The data pipeline software automatically archives these in NERSC’s High Performance Storage System (HPSS). NEAT’s telescopes revisit the same regions of the sky roughly every six days during a typical 18-day observing period. When a supernova appears in one of those galaxies, the SNfactory can find it using image subtraction software that can sift through billions of objects. This analysis is done using NERSC’s PDSF Linux cluster.
Eventually the pipeline will automate the entire discovery and confirmation process. Once a supernova is discovered from the Palomar or Maui images, follow-up observations will be obtained via remote control of a custom-built dual-beam optical spectrograph (being completed by SNfactory collaborators in France) mounted on the University of Hawaii’s 88-inch telescope on Mauna Kea. The Hawaii observations will be shipped by Internet for image processing at a supercomputing center in France and then sent to NERSC for analysis.
A recent major discovery made possible by the SNfactory was the first detection of hydrogen in the form of circumstellar material around a supernova—in this case, SN 2002ic, discovered near maximum light3. Researchers have been looking for hydrogen to discriminate between different types of possible progenitor systems to Type Ia supernovae. Large amounts of hydrogen around SN 2002ic suggest that the progenitor system contained a massive asymptotic giant branch star that lost several solar masses of gas in a “stellar wind” in the millennia leading up to the Type Ia explosion. Discoveries like this, which provide a more detailed understanding of the physics of supernovae, will improve the usefulness of supernovae as distance markers on the journey back through the history of the cosmos.
Research funding: HEP, LBNL, FBF, CNRS, IN2P3, INSU, PNC
3 M. Hamuy, M. M. Phillips, N. B. Suntzeff, J. Maza, L. E. González, M. Roth, K. Krisciunas, N. Morrell, E. M. Green, S. E. Persson, and P. J. McCarthy, "An asymptotic-giant-branch star in the progenitor system of a type 1a supernova," Nature 424, 651 (2003).
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