Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy

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The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate ... continued below

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5 pages

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Turk, M. & /KIPAC, Menlo Park September 30, 2008.

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The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate how the origins of cosmic structure--from the scale of clusters of galaxies down to the formation of individual stars--can be analyzed and visualized using a NumPy-based toolkit. Additionally, I discuss efforts to port this analysis code to other adaptive mesh refinement data formats, enabling direct comparison of data between research groups using different methods to simulate the same objects.

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5 pages

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  • Presented at7th Annual Python in Science Conference, , 8/19/2008-8/24/2008

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  • Report No.: SLAC-PUB-13416
  • Grant Number: AC02-76SF00515
  • Office of Scientific & Technical Information Report Number: 939104
  • Archival Resource Key: ark:/67531/metadc902352

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  • September 30, 2008

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  • Sept. 27, 2016, 1:39 a.m.

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  • Dec. 2, 2016, 7:18 p.m.

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Turk, M. & /KIPAC, Menlo Park. Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy, article, September 30, 2008; [Menlo Park, California]. (digital.library.unt.edu/ark:/67531/metadc902352/: accessed September 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.