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首页> 外文期刊>Nuclear Instruments & Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment >A feature-extraction and pile-up reconstruction algorithm for the forward-spectrometer EMC of the PANDA experiment
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A feature-extraction and pile-up reconstruction algorithm for the forward-spectrometer EMC of the PANDA experiment

机译:熊猫实验前锋光谱仪EMC的特征提取与堆积重构算法

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摘要

A digital algorithm for real-time feature extraction, i.e. determination of pulse amplitude and timing, has been developed for the forward-spectrometer electromagnetic calorimeter in the PANDA experiment. The algorithm, which is based on the well known optimal-filter algorithm, has been designed to allow reconstruction of pile-up signals in real time and to work in a free-running DAQ system such as PANDA. To benchmark the algorithm, a Geant4-based Monte Carlo model of photon interactions in the calorimeter has been developed to generate realistic detector signals which were used as inputs to a VHDL simulation of the algorithm. The results of this simulation study show that the developed algorithm improves the time resolution by almost 50% compared to a conventional linear constant fraction discriminator algorithm. For the PANDA calorimeter, this results in a time resolution close to 100 ps/√GeV per detector element at high energies. The algorithm allows reconstruction of the amplitude and timing of pile-up pulses separated by as little as 30 ns with good efficiency, fulfilling the PANDA requirements.
机译:用于实时特征提取的数字算法,即脉冲幅度和定时的测定,用于熊猫实验中的前进光谱仪电磁量热计。该算法基于众所周知的最佳滤波算法,旨在允许实时重建堆积信号,并在自由运行DAQ系统中工作,如熊猫。为了基准算法,已经开发出热量计中的光子相互作用的基于Geant4的蒙特卡罗模型以产生现实的检测器信号,该信号被用作算法的VHDL模拟的输入。该仿真研究结果表明,与传统的线性恒定分数鉴别器算法相比,开发算法通过近50%提高了时间分辨率。对于Panda Calorimeter,这导致在高能量下接近100 PS /√EdV的时间分辨率。该算法允许重建堆叠脉冲的幅度和定时,以良好的效率分离为30 ns,效率良好,满足熊猫要求。

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