Using Mutual Information to measure Time-lags from non-linear processes in Astronomy
Nachiketa Chakraborty, Peter Jan van Leeuwen

TL;DR
This paper introduces a mutual information-based method to accurately measure time-lags in non-linear astronomical lightcurves, outperforming traditional linear correlation techniques like DCF, and demonstrates its effectiveness on both toy models and real AGN data.
Contribution
The paper presents the mutual information correlation function (MICF) as a novel tool for detecting non-linear time-lags in astronomical data, improving upon standard methods.
Findings
MICF accurately identifies non-linear lag components.
Application to AGN NGC 4593 shows X-ray leads UV by ~0.2 days.
Detection of inward propagating fluctuations at ~-1 day.
Abstract
Measuring time lags between time-series or lighcurves at different wavelengths from a variable or transient source in astronomy is an essential probe of physical mechanisms causing multiwavelength variability. Time-lags are typically quantified using discrete correlation functions (DCF) which are appropriate for linear relationships. However, in variable sources like X-ray binaries, active galactic nuclei (AGN) and other accreting systems, the radiative processes and the resulting multiwavelength lightcurves often have non-linear relationships. For such systems it is more appropriate to use non-linear information-theoretic measures of causation like mutual information, routinely used in other disciplines. We demonstrate with toy models loopholes of using the standard DCF & show improvements when using the mutual information correlation function (MICF). For non-linear correlations, the…
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Taxonomy
TopicsStatistical and numerical algorithms · Advanced Statistical Methods and Models · Scientific Measurement and Uncertainty Evaluation
