A new representation of the light curve and its power density spectrum

TL;DR

This paper introduces a novel light curve representation using photon intervals, enabling high-resolution power spectrum analysis without binning, especially useful for sparse photon data, and demonstrates its effectiveness on artificial and real celestial data.

Contribution

The paper presents a new photon interval-based light curve representation that improves frequency analysis and period detection over traditional binning methods.

Findings

Successfully detects periods in artificial and celestial data

Offers higher time resolution and wider frequency range

Effective for sparse photon data with minimal information loss

Abstract

We present a new representation of light curves, which is quite different from the binning method. Instead of choosing uniform bins, the reciprocal of interval between two successive photons is adopted to represent the counting rate. A primary application of this light curve is to compute the power density spectrum by means of Lomb Periodogram and to find possible periods. To verify this new representation, we apply this method to artificial periodic data and some known periodic celestial objects, and the periods are all correctly found. Compared with the traditional fast Fourier transform method, our method does not rely on the bin size and has a spontaneously high time resolution, guaranteeing a wide frequency range in power density spectrum, and is especially useful when the photons are rare for its little information losses. Some other applications of the new light curve, like pulse identification, variability and spectral time lag, are also discussed.