Real-time particle identification in liquid xenon

We present an FPGA-based technique for the online identification of highly ionizing particles in a Liquid Xenon detector. The method was developed and successfully exploited to select α particles emitted by 241Am sources submerged in the liquid xenon in an overwhelming, mostly beam-related, γ-ray background. After revising the main features of xenon and other liquid noble gases as UV scintillating media, we describe the algorithm idea and its firmware implementation. We then present the results in terms of efficiency and background suppression for the real time α-particle tagging and the limits of the MEG trigger configuration. Finally we show that in MEG II we are going to overcome the main issues and further improve the performances.