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Register a new userTime-of-Propagation Cherenkov counter for particle identification
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M. Akatsu
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We describe here a new concept of a Cherenkov detector for particle identification by means of measuring the Time-of-Propagation (TOP) of Cherenkov photons.
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The Time-Of-Propagation (TOP) counter is a novel device for particle identification for the barrel region of the Belle II experiment, where, information of Cherenkov light propagation time is used to reconstruct its ring image. We successfully finished the detector production and installation to the Belle II structure in 2016. Commissioning of the installed detector has been on going, where the detector operation in the 1.5-T magnetic field was studied. Although we found a problem where photomultipliers were mechanically moved due to the magnetic force, it was immediately fixed. Performance was evaluated with cosmic ray data, the number of photon hits were confirmed to be consistent with simulation within 15-30%.
TORCH is a time-of-flight detector that is being developed for the Upgrade II of the LHCb experiment, with the aim of providing charged particle identification over the momentum range 2-10 GeV/c. A small-scale TORCH demonstrator with customised readout electronics has been operated successfully in beam tests at the CERN PS. Preliminary results indicate that a single-photon resolution better than 100 ps can be achieved.
Equipping an experiment at FCC-ee with particle identification (PID) capabilities, in particular the ability to distinguish between hadron species, would bring great benefits to the physics programme. Good PID is essential for precise studies in quark flavour physics, and is also a great asset for many measurements in tau, top and Higgs physics. The requirements placed by flavour physics and these other applications are surveyed, with an emphasis on the momentum range over which PID is necessary. Possible solutions are discussed, including classical RICH counters, time-of-flight systems, and d$E$/d$x$ and cluster counting. Attention is paid to the impact on the global detector design that including PID capabilities would imply.
We have developed a new laser-based time calibration system for the MEG II timing counter dedicated to timing measurement of positrons. The detector requires precise timing alignment between $sim,$500 scintillation counters. In this study, we present the calibration system which can directly measure the time offset of each counter relative to the laser-synchronized pulse. We thoroughly tested all the optical components and the uncertainty of this method is estimated to be 24 ps. In 2017, we installed the full system into the MEG II environment and performed a commissioning run. This method shows excellent stability and consistency with another method. The proposed system provides a precise timing alignment for SiPM-based timing detectors. It also has potential in areas such as TOF-PET.
JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primary aiming to determine the neutrino mass ordering. Moreover, its 20,kt target mass makes it an ideal detector to study neutrinos from various sources, including nuclear reactors, the Earth and its atmosphere, the Sun, and even supernovae. Due to the small cross section of neutrino interactions, the event rate of neutrino experiments is limited. In order to maximize the signal-to-noise ratio, it is extremely important to control the background levels. In this paper we discuss the potential of particle identification in JUNO, its underlying principles and possible areas of application in the experiment. While the presented concepts can be transferred to any large liquid scintillator detector, our methods are evaluated specifically for JUNO and the results are mainly driven by its high optical photon yield of 1,200 photo electrons per MeV of deposited energy. In order to investigate the potential of event discrimination, several event pairings are analysed, i.e. $alpha/beta$, $p/beta$, $e^+/e^-$, and $e^-/gamma$. We compare the discrimination performance of advanced analytical techniques based on neural networks and on the topological event reconstruction keeping the standard Gatti filter as a reference. We use the Monte Carlo samples generated in the physically motivated energy intervals. We study the dependence of our cuts on energy, radial position, PMT time resolution, and dark noise. The results show an excellent performance for $alpha/beta$ and $p/beta$ with the Gatti method and the neural network. Furthermore, $e^+/e^-$ and $e^-/gamma$ can partly be distinguished by means of neural network and topological reconstruction on a statistical basis. Especially in the latter case, the topological method proved very successful.
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