Last modified: 24 October 2023

URL: https://cxc.cfa.harvard.edu/ciao/why/lightcurve.html

Timing Analysis with Lightcurves


This document discusses caveats that one should be aware of when doing timing analysis on Chandra data. The CIAO Timing Threads - primarily the Basic Lightcurves thread - show how to create and use lightcurves in your analysis.


Tool: dmextract

The CIAO tool dmextract is used to create lightcurves. Refer to the dmextract help file for information on the tool.

A general command for making a lightcurve with dmextract looks like:

unix% dmextract \
      infile="acis_evt2.fits[ccd_id=3,sky=region(src.reg)][bin time=::259.28]" \
      outfile="lightcurve.fits" opt="ltc1"

As shown, the minimum and maximum range values may be omitted from the binning specification. dmextract will use the TSTART and TSTOP keywords from the input event file to determine the beginning and end points. Given how those keywords are defined this often results in bins which have 0 counts and 0 exposure time at the beginning and end of the lightcurve.

Barycenter Correction

In general, a barycenter correction should be applied to any data before it is used for timing analysis. Barycentering adjusts the times associated with the observation (both the times associated with the events and the times in the header keywords) for the difference in photon arrival times as the Earth and Chandra move around the Sun. For more information on barycenter-correcting times, see the Apply Barycenter Correction thread.

ACIS Lightcurves

The simplest lightcurve we can create is from a point source in ACIS data. This is generally done to get an idea of the variability of the source, or to look for background flares that should be filtered out.

Caveats:

HRC Lightcurves

The proper method of creating an HRC lightcurve requires accounting for the Dead Time Factor (DTF), as illustrated in the Basic Lightcurves thread.

Caveats:

Timing with ACIS CC-Mode Data

The ACIS continuous clocking mode may also be used for timing analysis. Observing in this mode produces a 1-D "image" of the sky by continually reading out the detector at a rate of 2.85 msec/row.

Caveats:

Timing with an ACIS Readout Streak

Bright sources observed by ACIS are typically problematic in data reduction, but the "readout streak" may be considered an exception. As it does not have a shutter, ACIS continues to detect photons while reading out a frame (which takes ~41 msec/frame). During this short time, it is probable that photons from bright sources (e.g. a 1 count/s point source) will strike the detector. These events will be read with CHIPY values offset from the nominal position of the source, forming a streak along the direction of readout.

The acisreadcorr tool was designed to find these "out-of-time" events. Once flagged, the events may be filtered or corrected; see the Remove the ACIS Readout Streak thread for more information. Since the CHIPY value of an out-of-time event is related to its arrival time, a high-resolution lightcurve may be generated with the corrected photons.

The temporal resolution of this lightcurve is limited by the frame transfer rate of ~41 msec/frame. However, since the corrected time is based on the assumption that all photons originate from the center of the source, the error will be proportional to the size of the source. As mentioned in the ahelp file, the accuracy of these times has not been rigorously tested, so use caution when performing timing analysis with these events.

Precise, Flux-Calibrated Lightcurve

The most dependable method of calculating fluxes is to model the response-folded source spectrum. This will give an intrinsic flux [ergs/cm2/s], instead of a simple count rate [count/s]. Moreover, one may plot source spectral parameters (the slope of a power law, line FWHM, etc.) versus time for a more detailed study of the nature of the source variation. The Phase-binning a Spectrum thread shows how to extract the data.

In general, creating a flux-calibrated lightcurve is uncomplicated, but time-consuming. First, extract spectra for the times of interest; one spectrum is needed for every datapoint in the final lightcurve. Each spectrum is then fit with a source model and the integrated flux is calculated for a given energy range. Each flux value will be calibrated and based on the appropriate GTIs. Finally, the flux value for each of the fits can be manually written to a file for plotting; the file should have two columns - time and flux (the best-fit parameter value).