13 citations · 59 across the 10 of their papers we have counts for
10 papers
Structured generalized sliced Wasserstein distance for keV X-ray polarization analysis with Gas Pixel Detector
Pengcheng Ai, Hongtao Qin, Xiangming Sun +3
Because of the special angular distribution of excited electrons by the photoelectric effect, the Gas Pixel Detector (GPD) is effective in measuring keV X-ray polarization of astro…
Towards energy-insensitive and robust neutron/gamma classification: A learning-based frequency-domain parametric approach
Pengcheng Ai, Hongtao Qin, Xiangming Sun +1
Neutron/gamma discrimination has been intensively researched in recent years, due to its unique scientific value and widespread applications. With the advancement of detection mate…
Scintillation pulse characterization with spectrum-inspired temporal neural networks: case studies on particle detector signals
Pengcheng Ai, Xiangming Sun, Zhi Deng +1
Particle detectors based on scintillators are widely used in high-energy physics and astroparticle physics experiments, nuclear medicine imaging, industrial and environmental detec…
Label-free timing analysis of SiPM-based modularized detectors with physics-constrained deep learning
Pengcheng Ai, Le Xiao, Zhi Deng +6
Pulse timing is an important topic in nuclear instrumentation, with far-reaching applications from high energy physics to radiation imaging. While high-speed analog-to-digital conv…
PulseDL-II: A System-on-Chip Neural Network Accelerator for Timing and Energy Extraction of Nuclear Detector Signals
Pengcheng Ai, Zhi Deng, Yi Wang +3
Front-end electronics equipped with high-speed digitizers are being used and proposed for future nuclear detectors. Recent literature reveals that deep learning models, especially…
Universal uncertainty estimation for nuclear detector signals with neural networks and ensemble learning
Pengcheng Ai, Zhi Deng, Yi Wang +1
Characterizing uncertainty is a common issue in nuclear measurement and has important implications for reliable physical discovery. Traditional methods are either insufficient to c…
Neural network--featured timing systems for radiation detectors: performance evaluation based on bound analysis
Pengcheng Ai, Zhi Deng, Yi Wang +1
Waveform sampling systems are used pervasively in the design of front end electronics for radiation detection. The introduction of new feature extraction algorithms (eg. neural net…
A deep learning approach to multi-track location and orientation in gaseous drift chambers
Pengcheng Ai, Dong Wang, Xiangming Sun +2
Accurate measuring the location and orientation of individual particles in a beam monitoring system is of particular interest to researchers in multiple disciplines. Among feasible…
Timing and characterization of shaped pulses with MHz ADCs in a detector system: a comparative study and deep learning approach
Pengcheng Ai, Dong Wang, Guangming Huang +3
Timing systems based on Analog-to-Digital Converters are widely used in the design of previous high energy physics detectors. In this paper, we propose a new method based on deep l…
Three-dimensional convolutional neural networks for neutrinoless double-beta decay signal/background discrimination in high-pressure gaseous Time Projection Chamber
Pengcheng Ai, Dong Wang, Guangming Huang +1
In the search for neutrinoless double-beta decay, the high-pressure gaseous Time Projection Chamber has a distinct advantage, because the ionization charge tracks produced by parti…