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Matthew Turk

University of Illinois at Urbana-Champaign

Stellar Astronomy and Astrophysics

Chemistry in the Early Universe

(bahf)
Oct 2016 - Sep 2018

2016

Kamdar, Harshil M. and Turk, Matthew J. and Brunner, Robert J. (2016): Machine learning and cosmological simulations – II. Hydrodynamical simulations, Monthly Notices of the Royal Astronomical Society, The Royal Astronomical Society, Vol 457, Num 2, pp1162-1179
Kamdar, Harshil M. and Turk, Matthew J. and Brunner, Robert J. (2016): Machine learning and cosmological simulations – I. Semi-analytical models, Monthly Notices of the Royal Astronomical Society, The Royal Astronomical Society, Vol 455, Num 1, pp642-658

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

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

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.

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

NCSA Grants $2.6M in Blue Waters Awards to Illinois Researchers


Jul 6, 2017

The National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign has awarded 3,697,000 node hours (NH) of time on the Blue Waters supercomputer to Illinois researchers from Spring 2017 proposal submissions. The combined value of these awards is over $2.6 million dollars, and through the life of the Blue Waters program, NCSA has awarded over 43 million node hours to UI researchers—a value of nearly $27 million. Some of the time allocated for Blue Waters will go to projects that focus on HIV research, Laser Interferometer Gravitational-Wave Observatory (LIGO) simulations, genomics and global warming research.


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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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YT Project Awarded NSF Grant to Expand to Multiple New Science Domain


Aug 11, 2017

The yt Project, an open science environment created to address astrophysical questions through analysis and visualization, has been awarded a $1.6 million dollar grant from the National Science Foundation(NSF) to continue developing their software project. This grant will enable yt to expand and begin to support other domains beyond astrophysics, including weather, geophysics and seismology, molecular dynamics and observational astronomy. It will also support the development of curricula for Data Carpentry, to ease the onramp for scientists new to data from these domains.


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