36,386 research outputs found

    New readout and data-acquisition system in an electron-tracking Compton camera for MeV gamma-ray astronomy (SMILE-II)

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    For MeV gamma-ray astronomy, we have developed an electron-tracking Compton camera (ETCC) as a MeV gamma-ray telescope capable of rejecting the radiation background and attaining the high sensitivity of near 1 mCrab in space. Our ETCC comprises a gaseous time-projection chamber (TPC) with a micro pattern gas detector for tracking recoil electrons and a position-sensitive scintillation camera for detecting scattered gamma rays. After the success of a first balloon experiment in 2006 with a small ETCC (using a 10×\times10×\times15 cm3^3 TPC) for measuring diffuse cosmic and atmospheric sub-MeV gamma rays (Sub-MeV gamma-ray Imaging Loaded-on-balloon Experiment I; SMILE-I), a (30 cm)3^{3} medium-sized ETCC was developed to measure MeV gamma-ray spectra from celestial sources, such as the Crab Nebula, with single-day balloon flights (SMILE-II). To achieve this goal, a 100-times-larger detection area compared with that of SMILE-I is required without changing the weight or power consumption of the detector system. In addition, the event rate is also expected to dramatically increase during observation. Here, we describe both the concept and the performance of the new data-acquisition system with this (30 cm)3^{3} ETCC to manage 100 times more data while satisfying the severe restrictions regarding the weight and power consumption imposed by a balloon-borne observation. In particular, to improve the detection efficiency of the fine tracks in the TPC from \sim10\% to \sim100\%, we introduce a new data-handling algorithm in the TPC. Therefore, for efficient management of such large amounts of data, we developed a data-acquisition system with parallel data flow.Comment: 11 pages, 24 figure

    Cache Equalizer: A Cache Pressure Aware Block Placement Scheme for Large-Scale Chip Multiprocessors

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    This paper describes Cache Equalizer (CE), a novel distributed cache management scheme for large scale chip multiprocessors (CMPs). Our work is motivated by large asymmetry in cache sets usages. CE decouples the physical locations of cache blocks from their addresses for the sake of reducing misses caused by destructive interferences. Temporal pressure at the on-chip last-level cache, is continuously collected at a group (comprised of cache sets) granularity, and periodically recorded at the memory controller to guide the placement process. An incoming block is consequently placed at a cache group that exhibits the minimum pressure. CE provides Quality of Service (QoS) by robustly offering better performance than the baseline shared NUCA cache. Simulation results using a full-system simulator demonstrate that CE outperforms shared NUCA caches by an average of 15.5% and by as much as 28.5% for the benchmark programs we examined. Furthermore, evaluations manifested the outperformance of CE versus related CMP cache designs

    Infrastructure for Detector Research and Development towards the International Linear Collider

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    The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

    Technical Design Report for the PANDA Micro Vertex Detector

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    This document illustrates the technical layout and the expected performance of the Micro Vertex Detector (MVD) of the PANDA experiment. The MVD will detect charged particles as close as possible to the interaction zone. Design criteria and the optimisation process as well as the technical solutions chosen are discussed and the results of this process are subjected to extensive Monte Carlo physics studies. The route towards realisation of the detector is outlined

    Proton tracking in a high-granularity Digital Tracking Calorimeter for proton CT purposes

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    Radiation therapy with protons as of today utilizes information from x-ray CT in order to estimate the proton stopping power of the traversed tissue in a patient. The conversion from x-ray attenuation to proton stopping power in tissue introduces range uncertainties of the order of 2-3% of the range, uncertainties that are contributing to an increase of the necessary planning margins added to the target volume in a patient. Imaging methods and modalities, such as Dual Energy CT and proton CT, have come into consideration in the pursuit of obtaining an as good as possible estimate of the proton stopping power. In this study, a Digital Tracking Calorimeter is benchmarked for proof-of-concept for proton CT purposes. The Digital Tracking Calorimeteris applied for reconstruction of the tracks and energies of individual high energy protons. The presented prototype forms the basis for a proton CT system using a single technology for tracking and calorimetry. This advantage simplifies the setup and reduces the cost of a proton CT system assembly, and it is a unique feature of the Digital Tracking Calorimeter. Data from the AGORFIRM beamline at KVI-CART in Groningen in the Netherlands and Monte Carlo simulation results are used to in order to develop a tracking algorithm for the estimation of the residual ranges of a high number of concurrent proton tracks. The range of the individual protons can at present be estimated with a resolution of 4%. The readout system for this prototype is able to handle an effective proton frequency of 1 MHz by using 500 concurrent proton tracks in each readout frame, which is at the high end range of present similar prototypes. A future further optimized prototype will enable a high-speed and more accurate determination of the ranges of individual protons in a therapeutic beam.Comment: 21 pages, 8 figure

    The COMPASS Experiment at CERN

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    The COMPASS experiment makes use of the CERN SPS high-intensitymuon and hadron beams for the investigation of the nucleon spin structure and the spectroscopy of hadrons. One or more outgoing particles are detected in coincidence with the incoming muon or hadron. A large polarized target inside a superconducting solenoid is used for the measurements with the muon beam. Outgoing particles are detected by a two-stage, large angle and large momentum range spectrometer. The setup is built using several types of tracking detectors, according to the expected incident rate, required space resolution and the solid angle to be covered. Particle identification is achieved using a RICH counter and both hadron and electromagnetic calorimeters. The setup has been successfully operated from 2002 onwards using a muon beam. Data with a hadron beam were also collected in 2004. This article describes the main features and performances of the spectrometer in 2004; a short summary of the 2006 upgrade is also given.Comment: 84 papes, 74 figure

    A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

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    This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast 128x64128\mathrm{x}64 binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode (10μW10\mu W at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between 193μW193\mu W and 277μW277\mu W, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa
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