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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.
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The Technical Design for the COMET Phase-I experiment is presented in this paper. COMET is an experiment at J-PARC, Japan, which will search for neutrinoless conversion of muons into electrons in the field of an aluminium nucleus ($mu-e$ conversion, $mu^- N to e^- N$); a lepton flavor violating process. The experimental sensitivity goal for this process in the Phase-I experiment is $3.1times10^{-15}$, or 90 % upper limit of branching ratio of $7times 10^{-15}$, which is a factor of 100 improvement over the existing limit. The expected number of background events is 0.032. To achieve the target sensitivity and background level, the 3.2 kW 8 GeV proton beam from J-PARC will be used. Two types of detectors, CyDet and StrECAL, will be used for detecting the mue conversion events, and for measuring the beam-related background events in view of the Phase-II experiment, respectively. Results from simulation on signal and background estimations are also described.
Radiation damage on front-end readout and trigger electronics is an important issue in the COMET Phase-I experiment at J-PARC, which plans to search for the neutrinoless transition of a muon to an electron. To produce an intense muon beam, a high-power proton beam impinges on a graphite target, resulting in a high-radiation environment. We require radiation tolerance to a total dose of $1.0,mathrm{kGy}$ and $1,mathrm{MeV}$ equivalent neutron fluence of $1.0times10^{12},mathrm{n_{eq},cm^{-2}}$ including a safety factor of 5 over the duration of the physics measurement. The use of commercially-available electronics components which have high radiation tolerance, if such components can be secured, is desirable in such an environment. The radiation hardness of commercial electronic components has been evaluated in gamma-ray and neutron irradiation tests. As results of these tests, voltage regulators, ADCs, DACs, and several other components were found to have enough tolerance to both gamma-ray and neutron irradiation at the level we require.
The GERDA experiment located at the LNGS searches for neutrinoless double beta (0 ubetabeta) decay of ^{76}Ge using germanium diodes as source and detector. In Phase I of the experiment eight semi-coaxial and five BEGe type detectors have been deployed. The latter type is used in this field of research for the first time. All detectors are made from material with enriched ^{76}Ge fraction. The experimental sensitivity can be improved by analyzing the pulse shape of the detector signals with the aim to reject background events. This paper documents the algorithms developed before the data of Phase I were unblinded. The double escape peak (DEP) and Compton edge events of 2.615 MeV gamma rays from ^{208}Tl decays as well as 2 ubetabeta decays of ^{76}Ge are used as proxies for 0 ubetabeta decay. For BEGe detectors the chosen selection is based on a single pulse shape parameter. It accepts 0.92$pm$0.02 of signal-like events while about 80% of the background events at Q_{betabeta}=2039 keV are rejected. For semi-coaxial detectors three analyses are developed. The one based on an artificial neural network is used for the search of 0 ubetabeta decay. It retains 90% of DEP events and rejects about half of the events around Q_{betabeta}. The 2 ubetabeta events have an efficiency of 0.85pm0.02 and the one for 0 ubetabeta decays is estimated to be 0.90^{+0.05}_{-0.09}. A second analysis uses a likelihood approach trained on Compton edge events. The third approach uses two pulse shape parameters. The latter two methods confirm the classification of the neural network since about 90% of the data events rejected by the neural network are also removed by both of them. In general, the selection efficiency extracted from DEP events agrees well with those determined from Compton edge events or from 2 ubetabeta decays.
This paper discusses a parallelized event reconstruction of the COMET Phase-I experiment. The experiment aims to discover charged lepton flavor violation by observing 104.97 MeV electrons from neutrinoless muon-to-electron conversion in muonic atoms. The event reconstruction of electrons with multiple helix turns is a challenging problem because hit-to-turn classification requires a high computation cost. The introduced algorithm finds an optimal seed of position and momentum for each turn partition by investigating the residual sum of squares based on distance-of-closest-approach (DCA) between hits and a track extrapolated from the seed. Hits with DCA less than a cutoff value are classified for the turn represented by the seed. The classification performance was optimized by tuning the cutoff value and refining the set of classified hits. The workload was parallelized over the seeds and the hits by defining two GPU kernels, which record track parameters extrapolated from the seeds and finds the DCAs of hits, respectively. A reasonable efficiency and momentum resolution was obtained for a wide momentum region which covers both signal and background electrons. The event reconstruction results from the CPU and GPU were identical to each other. The benchmarked GPUs had an order of magnitude of speedup over a CPU with 16 cores while the exact speed gains varied depending on their architectures.
This article documents the characteristics of the high voltage (HV) system of the hadronic calorimeter TileCal of the ATLAS experiment. Such a system is suitable to supply reliable power distribution into particles physics detectors using a large number of PhotoMultiplier Tubes (PMTs). Measurements performed during the 2015 and 2016 data taking periods of the ATLAS detector show that its performance, in terms of stability and noise, fits the specifications. In particular, almost all the PMTs show a voltage instability smaller than 0.5 V corresponding to a gain stability better than 0.5%. A small amount of channels was found not working correctly. To diagnose the origin of such defects, the results of the HV measurements were compared to those obtained using a Laser system. The analysis shows that less than 0.2% of the about 10 thousand HV channels were malfunctioning.
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