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The physical scenario responsible for gamma-ray flaring activity and itslocation for Flat Spectrum Radio Quasars is still debated. The study of thestatistical distribution of waiting-times between flares (the time intervalsbetween consecutive activity peaks) can give information on the distribution offlaring times, and constrain the physical mechanism responsible for gamma-rayemission. We adopt here a Scan-Statistic driven clustering method (iSRS) torecognize flaring states within the FERMI-LAT data, and identify the time ofactivity-peaks. Results: Flares waiting times can be described with apoissonian process, consisting of a set of overlapping bursts of flares, withan average burst duration of about 0.6 year, and average rate of 1.3/y . Forwaiting times below 1d host-frame we found a statistically-relevant secondpopulation, the fast-component, mainly from CTA 102 data. The period ofconspicuous detection of the fast component for CTA 102 coincides with thecrossing-time of the superluminal K1 feature with the C1 stationary feature inradio reported in Jorstad et al. (2017); Casadio et al. (2019). Conclusions: Toreconcile the mechanism proposed in Jorstad et al. (2017); Casadio et al.(2019) with the bursting-activity, we have to assume that plasma streams with atypical length of about 2pc (in the stream reference-frame) reach therecollimation-shock. Otherwise, the distribution of waiting-times can beinterpreted as originating from relativistic-plasma moving along the jet for adeprojected length of about 30-50pc (assuming a Lorentz-factor=10), thatsporadically produces gamma-ray flares. In magnetic-reconnection scenario,reconnection events or plasma injection to the reconnection-sites should beintermittent. Individual plasmoids can be resolved in a few favourable casesonly (Christie et al., 2019); they could be responsible for the fast component.

Waiting times between gamma-ray flares of Flat Spectrum Radio Quasars, and constraints on emission processes