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Brian O'Shea

Michigan State University

Stellar Astronomy and Astrophysics

2017

Barrow, Kirk S. S., Wise, John H., Norman, Michael L., O'Shea, Brian W., and Xu, Hao (2017): First light: exploring the spectra of high-redshift galaxies in the Renaissance Simulations, Monthly Notices of the Royal Astronomical Society, Oxford University Press, Vol 469, Num 4, pp4863-4878

2016

Hao Xu, Kyungjin Ahn, Michael L. Norman, John H. Wise, and Brian W. O’Shea (2016): X-Ray Background at High Redshifts from Pop III Remnants: Results from Pop III Star Formation Rates in the Renaissance Simulations, The Astrophysical Journal Letters, The American Astronomical Society, Vol 832, Num 1, ppL5
Hao Xu, John H. Wise, Michael L. Norman, Kyungjin Ahn, and Brian W. O'Shea (2016): Galaxy Properties and UV Escape Fractions During Epoch of Reionization: Results from the Renaissance Simulations, The Astrophysical Journal, The American Astronomical Society, Vol 833, Num 1, pp84

2015

Brian W. O'Shea, John H. Wise, Hao Xu, and Michael L. Norman (2015): Probing the Ultraviolet Luminosity Function of the Earliest Galaxies with the Renaissance Simulations, The Astrophysical Journal Letters, The American Astronomical Society, Vol 807, Num 1, ppL12
Britton D. Smith, John H. Wise, Brian W. O'Shea, Michael L. Norman, and Sadegh Khochfar (2015): The First Population II Stars Formed in Externally Enriched Mini-Haloes, Mon. Not. R. Astron. Soc., Oxford University Press (OUP), Vol 452, Num 3, pp2822--2836
Kyungjin Ahn, Hao Xu, Michael L. Norman, Marcelo A. Alvarez, and John H. Wise (2015): Spatially Extended 21 Cm Signal from Strongly Clustered UV and X-Ray Sources in the Early Universe, ApJ, The American Astronomical Society, Vol 802, Num 1, pp8
Michael L. Norman, Daniel R. Reynolds, Geoffrey C. So, Robert P. Harkness, and John H. Wise (2015): Fully Coupled Simulation of Cosmic Reionization. I. Numerical Methods and Tests, The Astrophysical Journal Supplement Series, The American Astronomical Society, Vol 216, Num 1, pp16

2014

Greg L. Bryan and Michael L. Norman and Brian W. O'Shea and Tom Abel and John H. Wise and Matthew J. Turk and Daniel R. Reynolds and David C. Collins and Peng Wang and Samuel W. Skillman and Britton Smith and Robert P. Harkness and James Bordner and Ji-hoon Kim and Michael Kuhlen and Hao Xu and Nathan Goldbaum and Cameron Hummels and Alexei G. Kritsuk and Elizabeth Tasker and Stephen Skory and Christine M. Simpson and Oliver Hahn and Jeffrey S. Oishi and Geoffrey C. So and Fen Zhao and Renyue Cen and Yuan Li and The Enzo Collaboration (2014): Enzo: An Adaptive Mesh Refinement Code for Astrophysics, The Astrophysical Journal Supplement Series, The American Astronomical Society, Vol 211, Num 2, pp19
Hao Xu, Kyungjin Ahn, John H. Wise, Michael L. Norman, and Brian W. O'Shea (2014): Heating the Intergalactic Medium by X-Rays from Population III Binaries in High-Redshift Galaxies, ApJ, The American Astronomical Society, Vol 791, Num 2, pp110
Pengfei Chen, John H. Wise, Michael L. Norman, Hao Xu, and Brian W. O'Shea (2014): Scaling Relations for Galaxies Prior to Reionization, ApJ, The American Astronomical Society, Vol 795, Num 2, pp144

2013

Ji-hoon Kim and Tom Abel and Oscar Agertz and Greg L. Bryan and Daniel Ceverino and Charlotte Christensen and Charlie Conroy and Avishai Dekel and Nickolay Y. Gnedin and Nathan J. Goldbaum and Javiera Guedes and Oliver Hahn and Alexander Hobbs and Philip F. Hopkins and Cameron B. Hummels and Francesca Iannuzzi and Dusan Keres and Anatoly Klypin and Andrey V. Kravtsov and Mark R. Krumholz and Michael Kuhlen and Samuel N. Leitner and Piero Madau and Lucio Mayer and Christopher E. Moody and Kentaro Nagamine and Michael L. Norman and Jose Onorbe and Brian W. O'Shea and Annalisa Pillepich and Joel R. Primack and Thomas Quinn and Justin I. Read and Brant E. Robertson and Miguel Rocha and Douglas H. Rudd and Sijing Shen and Britton D. Smith and Alexander S. Szalay and Romain Teyssier and Robert Thompson and Keita Todoroki and Matthew J. Turk and James W. Wadsley and John H. Wise and and Adi Zolotov (2013): The AGORA High-Resolution Galaxy Simulations Comparison Project, The Astrophysical Journal Supplement Series, The American Astronomical Society, Vol 210, Num 1, pp14
Hao Xu, John H. Wise, and Michael L. Norman (2013): Population III Stars and Remnants in High-Redshift Galaxies, ApJ, The American Astronomical Society, Vol 773, Num 2, pp83

2012

B. O'Shea and M. Norman and B. Smith and M. Turk and M. Kuhlen and J. Wise and D. Reynolds and R. Harkness and M. Gajbe and D. Semeraro (2012): Cosmology on the Blue Waters Early Science System, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, IEEE, pp1578-1578, Salt Lake City, Utah, U.S.A.
James Bordner, Michael L. Norman, and Brian W. O'Shea (2012): Enzo-P/Cello: Extreme Adaptive Mesh Refinement for Astrophysics and Cosmology, University of Illinois at Urbana-Champaign, Proceedings of the Extreme Scaling Workshop (XSEDE '12), pp4:1--4:11, Chicago, Illinois, U.S.A.

2010

Matthew J. Turk, Britton D. Smith, Jeffrey S. Oishi, Stephen Skory, Samuel W. Skillman, Tom Abel, and Michael L. Norman (2010): Yt: A Multi-Code Analysis Toolkit for Astrophysical Simulation Data, The Astrophysical Journal Supplement Series, The American Astronomical Society, Vol 192, Num 1, pp9

2017

Brian O'Shea (2017): Simulating Galaxy Formation across Cosmic Time, 2017 Blue Waters Annual Report, pp42-43

2016

Brian O'Shea (2016): Connecting Galaxies in The Early Universe to The Milky Way, 2016 Blue Waters Annual Report, pp30-31

2015

Brian O'Shea (2015): Exploring The First Generations of Galaxies, 2015 Blue Waters Annual Report, pp26-27
Brian O'Shea: Studying the cosmic Dark Ages with petascale supercomputing
Blue Waters Symposium 2014, May 13, 2014

Claire Kopenhafer: Exploring Galactic Scaling Relations With Numerical Simulations


Conference for Undergraduate Women in Physics (CUWiP); Wayne State University, Detroit, Michigan, U.S.A., Jan 14, 2017

2015 Blue Waters Symposium highlights successes, looks to the future of supercomputing


May 29, 2015

The 2015 Blue Waters Symposium, held May 10-13 at Oregon's beautiful Sunriver Resort, brought together leaders in petascale computational science and engineering to share successes and methods. Around 130 attendees, many of whom were Blue Waters users and the NCSA staff who support their work, enjoyed presentations on computational advances in a range of research areas—including sub-atomic physics, weather, biology, astronomy, and many others—as well as keynotes from innovative thinkers and leaders in high-performance computing. Over the three days of the symposium, 58 science teams from across the country presented on their work on Blue Waters.


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Great Lakes Consortium awards Blue Waters resources to 9 research teams


Mar 13, 2015

Nine research teams from a wide range of disciplines have been awarded computational and data resources on the Blue Waters supercomputer at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. Blue Waters is one of the world’s most powerful supercomputers, capable of performing quadrillions of calculations every second and working with quadrillions of bytes of data. Its massive scale and balanced architecture enable scientists and engineers to tackle research challenges that could not be addressed with other computing systems.


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Getting viral


Sep 1, 2009

"In the planning world, we work with policymakers to design studies of particular outcomes," says Virginia Tech's Keith Bisset. Months of planning, collaboration, and modeling might go into strategies for what a city, county, or entire country might do when facing a disease outbreak. "But now we also have tools that allow for a quick turnaround. We can do a situational assessment that shows them what a particular [outbreak] might look like tomorrow or next week as it unfolds. They describe the situation, and we can tell them the outcomes of various interventions," he says. This spring Bisset and a group from Virginia Tech joined forces with the Pittsburgh Supercomputing Center's Shawn Brown and Douglas Roberts and Diglio Simoni of North Carolina's Research Triangle Institute to win one of the first Petascale Computing Resource Allocations awards. With that support and with computing time on Blue Waters, they expect to model global epidemics, as well as smaller-scale outbreaks. Instead of looking at a few hundred million people, as the team members do with their current codes, they'll look at more than 6 billion people.


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6 science teams begin using Blue Waters Early Science System


Mar 20, 2012

Six research teams have begun using the first phase of the Blue Waters sustained-petascale supercomputer to study some of the most challenging problems in science and engineering, from supernovae to climate change to the molecular mechanism of HIV infection. The Blue Waters Early Science System, which is made up of 48 Cray XE6 cabinets, represents about 15 percent of the total Blue Waters computational system and is currently the most powerful computing resource available through the National Science Foundation.


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Blue Waters simulations suggest there are fewer faint galaxies than expected


Jul 1, 2015

There may be far fewer galaxies further out in the Universe than might be expected, suggests a new study based on simulations conducted using the Blue Waters supercomputer at the National Center for Supercomputing Applications, with resulting data transferred to SDSC Cloud at the San Diego Supercomputer Center at the University of California, San Diego, for future analysis. The study, published this week in the Astrophysical Journal Letters, shows the first results from the Renaissance Simulations, a suite of extremely high-resolution adaptive mesh refinement (AMR) calculations of high redshift galaxy formation. "Our work suggests that there are far fewer faint galaxies than one could previously infer," said principal investigator and lead author Brian W. O'Shea, an associate professor at Michigan State University with a joint appointment in the Department of Computational Mathematics, Science and Engineering; the Department of Physics and Astronomy; and the National Superconducting Cyclotron Laboratory.


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Building blocks


Oct 20, 2015

Why do we care what happened 13 billion years ago? A bold lead question for an interview with an astrophysicist looking at the early universe, but one that doesn’t seem to faze Brian O’Shea. The Michigan State University professor just smiles across the Skype connection and then chuckles. ... O’Shea is no stranger to supercomputing or NCSA, dating back to his days as a student at the University of Illinois at Urbana-Champaign. As leader of a Petascale Computing Resource Allocations (PRAC) team that includes co-principal investigator Michael Norman and Hao Xu at the University of California, San Diego, John Wise of Georgia Tech, and Britton Smith of the University of Edinburgh, O’Shea’s been able to explore early galaxy formation and evolution. The team has published more than 16 papers, primarily in the Astrophysical Journal.


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There May Be Nowhere Near the Number of Galaxies We Thought There Were


Jul 2, 2015

It looks like we might have overestimated how many neighbors we have. New predictions show that the universe might be an emptier place than we imagined. Since the Hubble launched, we’ve been seeing stunning image of the crowded universe. Most of the images come accompanied by assurances that what we see in the images is just the start. Astronomers have been excitedly guessing at the amount of faint, distant galaxies that they can’t see. Lurkers surely outnumbered visible galaxies. New simulations done on Blue Waters, a supercomputer at the National Center for Supercomputing Applications indicate that that isn’t the case.


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Simulating the Earliest Generations of Galaxies with Enzo and Blue Waters


Aug 29, 2016

In this video from the 2016 Blue Waters Symposium, Brian O’Shea from Michigan State University presents: Simulating the Earliest Generations of Galaxies with Enzo and Blue Waters.


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What will scientists do with Blue Waters?


Dec 9, 2009

Many scientists are working now with the Blue Waters team so they are ready to use the massive sustained-petaflop supercomputer when it comes online in 2011. These teams will use Blue Waters to improve our understanding of tornadoes, earthquakes, the spread of contagious diseases, the formation of galaxies, the behavior of molecules and more.


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Blue Waters visualization team provides first science images


Apr 3, 2012

With the first portion of the Blue Waters petascale supercomputer now being used by six science teams, the Blue Waters visualization team is using scalable visualization software to produce some of the first science images from the Blue Waters project. NCSA staff members are performing application tests to ascertain Blue Waters' system and application performance. These tests, done in collaboration with the early science users, have produced datasets that are in turn being used by the Blue Waters visualization staff to test scalable visualization tools. Such tools enable science teams to explore the very large volumes of data they will produce on the full Blue Waters system. While the early visualization work is mostly concerned with software functionality, it is providing tantalizing glimpses of the early science.


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Tantalizing glimpses


Aug 27, 2012

Visualization has been an integral part of NCSA since its beginning. That tradition continues with the Blue Waters project. While the early visualization work is mostly concerned with testing software functionality and performance, says Dave Semeraro, Blue Waters visualization team leader, it is providing tantalizing glimpses of the science. As Petascale Computing Resource Allocations (PRAC) teams exercise the Blue Waters Early Science System (BW-ESS), NCSA staff members are performing application tests to ascertain system and application performance. These tests, done in collaboration with BW-ESS users, have produced datasets that are, in turn, being used by the Blue Waters visualization staff to test scalable visualization tools.


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Advances in Computational Research Transform Scientific Process and Discovery


Mar 25, 2013

Not every scientific discovery originates in the lab, or from the field. Scientists increasingly are turning to powerful new computers to perform calculations they couldn't do with earlier generation machines, and at breathtaking speed, resulting in groundbreaking computational insights across a range of research fields. .... Last October, NSF inaugurated Yellowstone, one of the world's most powerful computers, based at NCAR in Cheyenne, Wyo., and later this month will dedicate two additional supercomputers, Blue Waters, located at the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, and Stampede, headquartered at the Texas Advanced Computing Center 9TACC) at The University of Texas at Austin. ... "The computer is excellent in permitting us to test a hypothesis," says Klaus Schulten, a professor of physics at the University of Illinois at Urbana-Champaign, who uses large-scale computing to study the molecular assembly of biological cells, most recently HIV, the virus that causes AIDS. "But if you want to test a hypothesis, you need to have a hypothesis."


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