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Register a new userMuon ID- Taking Care of Lower Momenta Muons
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In the Muon package under study, the tracks are extrapolated using an algorithm which accounts for the magnetic field and the ionization (dE/dx). We improved the calculation of the field dependent term to increase the muon detection efficiency at lower momenta using a Runge-Kutta method. The muon identification and hadron separation in b-bbar jets is reported with the improved software. In the same framework, the utilization of the Kalman filter is introduced. The principle of the Kalman filter is described in some detail with the propagation matrix, with the Runge-Kutta term included, and the effect on low momenta single muons particles is described.
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This paper describes a new way to reconstruct and identify muons with high efficiency and high pion rejection. Since muons at the ILC are often produced with or in jets, for many of the physics channels of interest[1], an efficient algorithm to deal with the identification and separation of particles within jets is important. The algorithm at the core of the method accounts for the effects of the magnetic field and for the loss of energy by charged particles due to ionization in the detector. We have chosen to develop the analysis within the setup of one of the Linear Collider Concept Detectors adopted by the US. Within b-pair production jets, particles cover a wide range in momenta; however ~ 80% of the particles have a momentum below 30 GeV[2]. Our study, focused on bbar-b jets, is preceded by a careful analysis of single energy particles between 2 and 50 GeV. As medium energy particles are a substantial component of the jets, many of the particles lose part of their energy in the calorimeters and the solenoid coil before reaching the muon detector where they may have energy below 2 GeV. To deal with this problem we have implemented a Runge-Kutta correction of the calculated trajectory to better handle these lower energy particles. The multiple scattering and other stochastic processes, more important at lower energy, is addressed by a Kalman-filter integrated into the reconstruction algorithm. The algorithm provides a unique and powerful separation of muons from pions. The 5 Tesla magnetic field from a solenoid surrounds the hadron calorimeter and allows the reconstruction and precision momentum measurement down to a few GeV.
We have measured the muon flux and production rate of muon-induced neutrons at a depth of 611 m water equivalent. Our apparatus comprises three layers of crossed plastic scintillator hodoscopes for tracking the incident cosmic-ray muons and 760 L of gadolinium-doped liquid scintillator for producing and detecting neutrons. The vertical muon intensity was measured to be $I_{mu} = (5.7 pm 0.6) times 10^{-6}$ cm$^{-2}$s$^{-1}$sr$^{-1}$. The yield of muon-induced neutrons in the liquid scintillator was determined to be $Y_{n} = (1.19 pm 0.08 (stat) pm 0.21 (syst)) times 10^{-4}$ neutrons/($mucdot$g$cdot$cm$^{-2}$). A fit to the recently measured neutron yields at different depths gave a mean muon energy dependence of $leftlangle E_{mu} rightrangle^{0.76 pm 0.03}$ for liquid-scintillator targets.
Shashlyk-type electromagnetic calorimeter (ECal) of the Multi-Purpose Detector at heavy-ion NICA collider is optimized to provide precise spatial and energy measurements for photons and electrons in the energy range from about 40 MeV to 2-3 GeV. To deal with high multiplicity of secondary particles from Au-Au reactions, ECal has a fine segmentation and consists of 38,400 cells (towers). Given the big number of towers and the time constraint, it is not possible to calibrate every ECal tower with beam. In this paper, we describe the strategy of the first-order calibration of ECal with cosmic muons.
An experiment to search for mu-e conversion named COMET is being constructed at J-PARC. The experiment will be carried out using a two-stage approach of Phase-I and Phase-II. The data taking system of Phase-I is developed based on common network technology. The data taking system consists of two kinds of networks. One is a front-end network. Its network bundles around twenty front-end devices that have a 1-Gb optical network port. And a front-end computer accepts data from the devices via its network. The other is a back-end network that collects all event fragments from the front-end computers using a 10-Gb network. We used a low price 1Gb/10Gb optical network switch for the front-end network. And direct connection between the front-end PC and an event building PC using 10-Gb optical network devices was used for the back-end network. The event building PC has ten 10-Gb network ports. And each network port of the event building PC is connected to the front-end PCs port without using a network switch. We evaluated data taking performance with an event building on these two kinds of networks. The event building throughput of the front-end network achieved 337 MiB/s. And the event building throughput of the back-end networks achieved 1.2 GiB/s. It means that we could reduce the construction cost of the data taking network using this structure without deteriorating performance. Moreover, we evaluated the writing speed of the local storage RAID disk system connected to a back-end PC by a SAS interface, and a long-distance network copy from the experiment location to the lasting storage.
The calibration procedure of a finely granulated digital hadron calorimeter with Resistive Plate Chambers as active elements is described. Results obtained with a stack of nine layers exposed to muons from the Fermilab test beam are presented.
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