A 24-channel three-stage SiGe preamplifier achieves 0.35 nV/sqrt(Hz) voltage noise density, 21.11 mV/fC charge gain, 542 MHz bandwidth, 0.14 fC ENC, and SNR of 73 in He:iC4H10 gas for dN/dx measurements in drift tubes.
rep., CERN, Geneva (2017)
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Machine learning classifiers using fifteen cluster-level descriptors from time and ADC distributions effectively separate signal from background hits in prototype RPC detectors.
ATLAS reports on its Run 3 software infrastructure for data management, workflows, databases, validation, and physics analysis tools at the LHC.
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A 24-Channel Ultra-Low-Noise Preamplifier for dN/dx Measurements with Drift Tube Detectors
A 24-channel three-stage SiGe preamplifier achieves 0.35 nV/sqrt(Hz) voltage noise density, 21.11 mV/fC charge gain, 542 MHz bandwidth, 0.14 fC ENC, and SNR of 73 in He:iC4H10 gas for dN/dx measurements in drift tubes.
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Machine Learning-Based Cluster Classification to Suppress Background in a Prototype RPC Detector
Machine learning classifiers using fifteen cluster-level descriptors from time and ADC distributions effectively separate signal from background hits in prototype RPC detectors.
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Software and computing for Run 3 of the ATLAS experiment at the LHC
ATLAS reports on its Run 3 software infrastructure for data management, workflows, databases, validation, and physics analysis tools at the LHC.