Solar Flare Size-Waiting-Time Correlations in Individual Active Regions

We investigate solar flare size and waiting-time correlations within individual active regions (ARs) — where by size we mean soft X-ray peak flux — using a recent convolutional neural network (CNN)-based flare catalog. We examine 1,089 events during 18–27 March 2024, when four ARs (13614, 13615, 13617, and 13619) transited the disk. A probabilistic framework is developed to associate the CNN-detected events with their AR of origin, using extreme ultraviolet images. The ARs are observed to flare at different mean rates, ranging from (0.33 ± 0.05) hr−1 in AR 13617 and AR 13619 to (2.83 ± 0.11) hr−1 in AR 13615. The background-subtracted peak-flux distributions in the individual ARs follow power laws above a lower threshold with indices in the range 1.6–1.9. Size-waiting-time correlations are evaluated using time symmetry tests (i.e., tests of the statistical equivalence of waiting times before and after a flare), the Spearman rank correlation, and the Efron-Petrosian test for truncated data. No statistically significant correlations between flare sizes and waiting times are detected in most studied ARs at most times, although we identify specific instances of correlations in AR 13615. We discuss the implications for models of solar flare recurrence.