# Combining Higher-Order Statistics and Array Techniques to Pick Low-Energy P-Seismic Arrivals
## 2 Data  
We focus on the complex normal fault system of Southern Apennines that was struck by the destructive Ms 6.9 1980 Irpinia earthquake [19]. The Irpinia region in southern Italy exhibits significant seismogenic potential due to its complex fault systems and tectonic activity, as demonstrated by the long history of powerful earthquakes that occurred in this region [20,21] (some of the most important are displayed in Figure 1). Since 2005, the seismicity in the Irpinia area has been monitored in real-time by the Irpinia Near Fault Observatory [22], which also includes the Irpinia Seismic Network (ISNet; [[http://isnet.unina.it](http://isnet.unina.it)]([http://isnet.unina.it](http://isnet.unina.it)) [23]; last accessed on 18 January 2025). ISNet, with its 31 seismic stations equipped with accelerometers and short-period or broad-band seismometers, represents a natural laboratory for studying fault evolution and rupture processes. The seismicity of the last decades (2005-2024) is characterized by low magnitude events (maximum magnitude 3.9), mainly occurring at depths between 8 and 15 km [24,25], within the fault system that hosted the Irpinia earthquake.  
With the aim of monitoring the seismicity in the Irpinia region at a finer scale, in the framework of \"The DEnse muTTi-paramEtriC observations and 4D high-resolution imaging\" (DETECT [26]) experiment, 200 seismic stations were deployed in 20 small-aperture arrays of ten stations from August 2021 to August 2022, integrating the existing network, as illustrated in Figure 1. Each array consisted of one broadband sensor, with a characteristic period of 120s (Trillium-Compact/g = 750), one 1 Hz broadband and eight 4.5 Hz geophones deployed in urban areas within a kilometric-size aperture. Stations belonging to the same array were placed in a confined geographical area. Table 1 shows the maximum distance \(D^{\text{max}}\) between two generic stations of the same array.  
In this work, we analyze the about 35,700 seismic traces registered by DETECT stations, 200 Hz-sampled, corresponding to 226 events reported in the manual catalog provided by ISNet (accessible through the Irpinia Seismic Network website: [[http://isnet-bullettin.fisica.unina.it/cgi-bin/isnet-events/isnet.cgi](http://isnet-bullettin.fisica.unina.it/cgi-bin/isnet-events/isnet.cgi)]([http://isnet-bullettin.fisica.unina.it/cgi-bin/isnet-events/isnet.cgi](http://isnet-bullettin.fisica.unina.it/cgi-bin/isnet-events/isnet.cgi)); last accessed on 18 January 2025). The events have a local magnitude ranging between \(-0.3\) and \(2.3\), as extracted from the released seismic catalog and evaluated through a local magnitude scale tailored for the area [27], and they occurred during the first 6 months of the experiment (September 2021-February 2022). To obtain phase arrival times that will serve as initial references for calibrating our method, we follow the strategy and parameterization proposed by [17], tailored for the detection and phase picking of seismic sequences in Irpinia. This approach integrates the machine learning model EQTransformer [12] for detection and phase picking with a cross-correlation analysis applying the template matching algorithm EQCorrscan [28], with the aim to retrieve picks undetected by the machine learning model [29]. The approach returned 8685 P-wave arrival times. Henceforth, we will refer to these picks as catalog picks.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Array Code** & \(D^{\text{max}}\) **(Km)** & **Array Code** & \(D^{\text{max}}\) **(Km)** \\ \hline
01 & 1.7 & 11 & 2.7 \\
02 & 2.0 & 12 & 4.7 \\
03 & 4.1 & 13 & 4.4 \\
04 & 4.9 & 14 & 2.6 \\
05 & 2.8 & 15 & 1.3 \\
06 & 2.0 & 16 & 3.0 \\
07 & 2.9 & 17 & 2.9 \\
08 & 2.3 & 18 & 3.0 \\
09 & 2.7 & 19 & 5.8 \\
10 & 2.0 &