Deterministic and Stochastic Study of the X-ray Emission from the TeV Blazar Mrk~421

TL;DR

This study combines deterministic and stochastic analysis methods to investigate the complex X-ray variability of the blazar Mrk 421 over 17 years, revealing a multifaceted emission process with scale-dependent behaviors.

Contribution

It introduces a novel combination of recurrence quantification analysis, ARMA, and ARIMA models to analyze blazar variability across multiple temporal scales.

Findings

Deterministic patterns dominate at small scales.

Stochastic processes with memory influence large to small scales.

Noise impacts both short and long timescales.

Abstract

We present a comprehensive timing analysis of X-ray data from the {\it XMM-Newton} satellite, examining 50 light curves covering 17 years of observations of the blazar Mrk~421. This work uses classical deterministic and stochastic methods in a novel way, enabling the distinction of temporal scales and offering essential insights through correlations among parameters. Deterministic behaviors are primarily explored through recurrence quantification analysis (RQA), used innovatively by varying the threshold input parameter to examine variability at multiple temporal scales. To investigate behavior across various scales from a stochastic perspective, we apply both autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models, with results from ARIMA more tightly related to short scales. Our findings reveal that Mrk~421's X-ray emission is a multifaceted process, driven by both deterministic and stochastic patterns, indicating a complex interplay of physical phenomena. Our study demonstrates that deterministic patterns are more pronounced at small temporal scales, which are disconnected from large scales. On the other hand, stochastic processes with memory propagate from large to small time scales, while noise affects both scales, as indicated by the correlation analysis. These results underscore the importance of advanced methodologies for interpreting astrophysical data, contributing to ongoing discussions in blazar physics by exploring connections between our calculated parameters and established models. The same approach can potentially be applied to other sources, enhancing our general understanding of variability and emission mechanisms in blazars.