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Register a new userApplication of Geiger-mode photo sensors in Cherenkov detectors
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Silicon-based photosensors (SiPMs) working in the Geiger-mode represent an elegant solution for the readout of particle detectors working at low-light levels like Cherenkov detectors. Especially the insensitivity to magnetic fields makes this kind of sensors suitable for modern detector systems in subatomic physics which are usually employing magnets for momentum resolution. In our institute we are characterizing SiPMs of different manufacturers for selecting sensors and finding optimum operating conditions for given applications. Recently we designed and built a light concentrator prototype with 8x8 cells to increase the active photon detection area of an 8x8 SiPM (Hamamatsu MPPC S10931-100P) array. Monte Carlo studies, measurements of the collection efficiency, and tests with the MPPC were carried out. The status of these developments are presented.
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This paper presents the physical concept and test results of sample data of the high-speed hardware true random number generator design based on typically used for High Energy Physics hardware. Main features of this concept are the high speed of the true random numbers generation (tens of Mbt/s), miniature size and estimated lower production cost. This allows the use of such a device not only in large companies and government offices but for the end-user data cryptography, in classrooms, in scientific Monte-Carlo simulations, computer games and any other place where large number of true random numbers is required. The physics of the operations principle of using a Geiger-mode avalanche photo detector is discussed and the high quality of the data collected is demonstrated.
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The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.
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The Ring Imaging Cherenkov detectors of the LHCb experiment at the Large Hadron Collider at CERN are equipped with Hybrid Photo-Detectors. These vacuum photo-detectors are affected by the stray magnetic field of the LHCb magnet, which degrades their imaging properties. This effect increases the error on the Cherenkov angle measurement and would reduce the particle identification capabilities of LHCb. A system has been developed for the RICH2 Ring Imaging Cherenkov detector to perform a detailed characterisation of the magnetic distortion effects. It is described, along with the methods implemented to correct for these effects, restoring the optimal resolution.
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