Atangana-Baleanu Regularized Wavelet Compression For Astronomical Time-Series

TL;DR

This paper introduces a novel fractional wavelet compression technique using Atangana Baleanu derivatives to effectively compress astronomical light curves, reducing noise while preserving faint signals.

Contribution

It presents a new regularized wavelet compression method with long memory smoothing, outperforming classical methods in preserving weak astronomical signals.

Findings

Competitive compression ratios achieved.

Enhanced preservation of low-amplitude events.

Effective noise suppression while maintaining signal integrity.

Abstract

Astronomical light curves are noisy and irregular, so compression must reduce size without erasing weak transients. We propose a fractional wavelet compression method where wavelet coefficients are regularized via an Atangana Baleanu Caputo derivative with a nonsingular Mittag Leffler kernel. The induced long memory smoothing suppresses noise while preserving coherent transits, flares and oscillations. We give the coefficient level formulation, an efficient implementation, and comparisons with classical discrete wavelet thresholding, showing competitive compression with improved retention of low-amplitude events.