ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Keywords

A list of keywords associated with codes in the ASCL.

NASA (173), Kepler (31), Spitzer (13), TESS (13), Fermi (6), HITS (6), HST (5), ROSAT (4), Swift (4), CGRO (3), LISA (3), RXTE (3), ASCA (2), Chandra (2), COBE (2), Geotail (2), Heliophysics (2), Herschel (2), LRO (2), Magellan (2), MRO (2), NICER (2), Polar (2), Rosetta (2), Wind (2), WISE (2), WMAP (2), Apollo (1), Cassini (1), Dawn (1), GOES (1), Hinode (1), Hitomi (1), InSight (1), INTEGRAL (1), ISO (1), Juno (1), JWST (1), K2 (1), Lucy (1), Lunar Quest (1), MAVEN (1), MESSENGER (1), MGS (1), NEAR (1), New Horizons (1), NISAR (1), NuSTAR (1), OSIRIS-REx (1), Parker Solar Probe (1), Psyche (1), RHESSI (1), SDO (1), SOFIA (1), SOHO (1), STEREO (1), Suzaku (1), THEMIS (1), TRMM (1)

Codes associated with 'Chandra'

[ascl:1203.001] AE: ACIS Extract

ACIS Extract (AE), written in the IDL language, provides innovative and automated solutions to the varied challenges found in the analysis of X-ray data taken by the ACIS instrument on NASA's Chandra observatory. AE addresses complications found in many Chandra projects: large numbers of point sources (hundreds to several thousand), faint point sources, misaligned multiple observations of an astronomical field, point source crowding, and scientifically relevant diffuse emission. AE can perform virtually all the data processing and analysis tasks that lie between Level 2 ACIS data and publishable LaTeX tables of point-like and diffuse source properties and spectral models.

[ascl:1905.022] ClusterPyXT: Galaxy cluster pipeline for X-ray temperature maps

ClusterPyXT (Cluster Pypeline for X-ray Temperature maps) creates X-ray temperature maps, pressure maps, surface brightness maps, and density maps from X-ray observations of galaxy clusters to show turbulence, shock fronts, nonthermal phenomena, and the overall dynamics of cluster mergers. It requires CIAO (ascl:1311.006) and CALDB. The code analyzes archival data and provides capability for integrating additional observations into the analysis. The ClusterPyXT code is general enough to analyze data from other sources, such as galaxies, active galactic nuclei, and supernovae, though minor modifications may be necessary.