In this work we present the latest developments in the SAMPA-SRS integration. A software was developed to improve the acquisition configuration, acquisition, and decoding of the data. The complete framework was tested using a triple GEM-based position sensitive detector for X-rays. The detector was operated in Ar/CO2 (70/30) in continuous flow, at atmospheric pressure and made use of a 1 dimension strip readout (200 μm wide strips at a pitch of 400 μm) for charge collection. With this detector a position resolution of better than 833 μm was obtained, with an energy resolution of 14.2 % (σ/E) for 5.9 keV.

Gas Electron Multiplier (GEM) based detectors contain microstructures that provide amplification, via avalanche multiplication, for the charges generated due to ionizing radiation. The readout of the detector is responsible for collecting electrons multiplied by the GEM structure and it may be position sensitive. In this preliminary study, we created algorithms to compare the error of three different methods for position reconstruction. All these methods are based on weighted averages. In the algorithm we modeled an electron cloud as a normalized Gaussian function that is collected by a 1D readout of strips affected by white noise, then we made a clustering algorithm to identify the strips that collected the electron cloud. The method that uses the weight equal to squared charges shows the highest errors for narrow clouds, when the σ value (standard deviation of a Gaussian function) is closer to the strip width. Nonetheless, the errors of the three methods get similar results for a σ approximately equal to the width of one and a half strips.