chandralc: A Python Package for CXO Lightcurve Analysis

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The chandralc Python package was developed to analyze Chandra X-ray Observatory lightcurves in a matter of seconds. With algorithms and programs to automatically extract, download, plot, and analyze data, it is the perfect tool to study CXO lightcurves efficiently and accurately.

chandralc is the perfect tool for citizen science. If you're interested in detecting extragalactic planets, feel free to shoot me an email at sam@qprogramming.net!

To see chandralc in action, check out the demo (currently in development).

Features:

Lightcurve Extraction

Extract lightcurves from one or more ObsIDs automatically. This feautre is not yet available publicly.

Downloads:

• Large database of over 150,000 lightcurves from 10,000+ X-ray Sources
• Downloading extracted lightcurves from 19+ galaxies.
• Search for lightcurves with J2000 coordinates
• Retrieve galaxy from lightcurve file names

Convert:

• Convert FITS lightcurves to ASCII txt files

Analysis:

Observation Details

• Total counts
• Observation time (in kiloseconds)
• Count rate (kiloseconds (rate_ks), seconds (rate_s))
• Source coordinates (J2000 format)
• ObsID (Observation ID of the lightcurve)
• Galaxy (Messier or NGC)

Plots

• Cumulative Count plots over time to view net counts over time
• Lightcurves with custom binning to view data in the form of count rate per bin or net counts per bin over time.
• Power Spectral Density (PSD) to identify periodicity and their time periods/frequencies.
• Running Average Plot

State Detection

Note: the flare detection algorithm is currently under development and has not been extensively tested. The eclipse detection algorithm has been tested on a sample of 150,000+ X-ray lightcurves and it was able to rediscover known transits and eclipses (including that of the first extragalactic planet candidate). It has also been used by the author of this package to make new discoveries.

• Flares
• Eclipses

Astrophysics Database Connection

• NASA ADS
  • Search for listings which include the source
  • Simple usage: only one method required (.search_ads())

Upcoming features:

• Integration with galaXy
• VizeR connection

Installation

1. Install dependencies via the requirements.txt file: pip install requirements.txt
2. Install the chandralc package via PIP: pip install chandralc
3. File Databases will automatically be downloaded on import of package

[more details coming soon]

Cite chandralc

If you use chandralc, code from chandralc or data products (images, data) in your research, please cite it as follows:

@MISC{chandralc,
	author = {{Kumar}, Sammarth},
	title = "{chandralc: Python Package for CXO Lightcurve Analysis}",
	keywords = {Software, Chandra, CXO, lightcurves },
	url = {https://github.com/sammarth-k/chandralc},
	howpublished = {https://github.com/sammarth-k/chandralc},
	year = {2021},
	month = {May},
}