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LombScargle

Introduction:

This is a toolbox written in Mathematica, providing basic tools to analyse light curve data from surveys. Currently supported surveys: Catalina, ASAS-SN, ZTF, and NEOWISE. Please feel free to use, modify, and distribute this toolbox. Any suggestions to improve the code or bug reports are most welcomed! If your research work benefits from this toolbox, please cite the web page of this repository: https://github.com/TuanYi/LombScargle. Many thanks!

Installation:

In order to run the toolbox, you should have Wolfram's Mathematica (version 10 or higher) installed on your computer. You can then download the repository and put it anywhere on your computer, open the notebook, and run it.

Descriptions:

[data]: folder to contain the light curve files. You should put the raw light curve data file in this folder.

[kernel]:modules for data import, LombScargle, and other useful tools.

[look.nb]: notebook that demonstrates how to use the tools to find the periodicity of a given light curve.

[results]: you can export any results you want in this folder

Example:

Step1: A lightcurve was downloaded from the Catalina Real-Time Transient Surveys:

lightcurve

Step2: Use the toolbox to import the data, find the period of this source by using the generalised Lomb-Scargle algorithm. Please refer to the following paper for details of the Lomb-Scargle algorithm:

VanderPlas 2018: https://ui.adsabs.harvard.edu/abs/1982ApJ...263..835S/abstract

Zechmeister & Kürster 2009: https://ui.adsabs.harvard.edu/abs/2009A%26A...496..577Z/abstract

Scargle 1982: https://ui.adsabs.harvard.edu/abs/1982ApJ...263..835S/abstract

Lomb 1976: https://ui.adsabs.harvard.edu/abs/1976Ap%26SS..39..447L/abstract:

(a) the lombscargle power: lombscargle_power

(b) the phasefolded light curve: phased_lightcurve

Maintenance:

[email protected]

The code is used in my recent paper: [A dynamically discovered and characterized non-accreting neutron star - M dwarf binary candidate] (https://www.nature.com/articles/s41550-022-01766-0)

If your research work benefits from this toolbox, please cite the web page of this repository: https://github.com/TuanYi/LombScargle. Many thanks!