TURBUSTAT: Turbulence Statistics in Python']Python

被引:25
作者
Koch, Eric W. [1 ]
Rosolowsky, Erik W. [1 ]
Boyden, Ryan D. [2 ,3 ]
Burkhart, Blakesley [4 ,5 ]
Ginsburg, Adam [6 ]
Loeppky, Jason L. [7 ]
Offner, Stella S. R. [8 ]
机构
[1] Univ Alberta, Dept Phys, 4-183 CCIS, Edmonton, AB T6G 2E1, Canada
[2] Univ Arizona, Dept Astron, 933 North Cherry Ave, Tucson, AZ 85721 USA
[3] Univ Arizona, Steward Observ, 933 North Cherry Ave, Tucson, AZ 85721 USA
[4] Flatiron Inst, Ctr Computat Astrophys, 162 Fifth Ave, New York, NY 10010 USA
[5] Rutgers State Univ, Dept Phys & Astron, 136 Frelinghuysen Rd, Piscataway, NJ 08854 USA
[6] Natl Radio Astron Observ, 1003 Lopezville Rd, Socorro, NM 87801 USA
[7] Univ British Columbia, Dept Phys, Okanagan Campus,3333 Univ Way, Kelowna, BC V1V 1V7, Canada
[8] Univ Texas Austin, Dept Astron, 2515 Speedway,Stop C1400, Austin, TX 78712 USA
基金
加拿大自然科学与工程研究理事会;
关键词
methods: data analysis; methods: statistical; turbulence; SPECTRAL-LINE DATA; HIERARCHICAL INTERSTELLAR STRUCTURE; DENSITY-VELOCITY CORRELATIONS; PRINCIPAL COMPONENT ANALYSIS; MAGNETIC-FIELD; POWER SPECTRUM; SUPERSONIC TURBULENCE; DELTA-VARIANCE; STAR-FORMATION; MAGNETOHYDRODYNAMIC TURBULENCE;
D O I
10.3847/1538-3881/ab1cc0
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We present TURBUSTAT (v1.0): a PYTHON package for computing turbulence statistics in spectral-line data cubes. TURBUSTAT includes implementations of 14 methods for recovering turbulent properties from observational data. Additional features of the software include: distance metrics for comparing two data sets; a segmented linear model for fitting lines with a break point; a two-dimensional elliptical power-law model; multicore fast-Fourier-transform support; a suite for producing simulated observations of fractional Brownian Motion fields, including two-dimensional images and optically thin H I data cubes; and functions for creating realistic world coordinate system information for synthetic observations. This paper summarizes the TURBUSTAT package and provides representative examples using several different methods. TURBUSTAT is an open-source package and we welcome community feedback and contributions.
引用
收藏
页数:11
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