Conveners
SHARED SESSION II: RDC 4&5 ASICS & TDAQ
- Mitchell Franck Newcomer (University of Pennsylvania (US))
- Zeynep Demiragli (Boston University (US))
- Jinlong Zhang (Argonne National Laboratory (US))
- Lorenzo Rota (SLAC National Laboratory)
Of the many items that need to be considered in a push towards one -picosecond timing for particle detectors, we have focused on one essential component: the distribution of references clock with an inter-channel precision of 100 femtoseconds (fs) or less. Our program has been to develop the tools to measure a reference clock to this level of precision using a digital dual mixer time...
In the High Energy Physics (HEP) and Nuclear Physics (NP) experiments, there is always a wish to readout all the detector data to improve efficiency and avoid losing potential useful information. This requirement motivates the development of technologies such as the on-detector processing, high speed data links and powerful back-end electronics. The Front-End Link eXchange (FELIX) system is an...
Inference of standard convolutional neural networks (CNNs) on FPGAs often incurs high latency and long initiation intervals due to the nested loops required to slide filters across the full input, especially when the input dimensions are large. However, in some datasets, meaningful signals may occupy only a small fraction of the input, say sometimes just a few percent of the total pixels or...
Next-generation pixel sensors will be sufficiently fine-grained, both in space and time, to determine kinematic properties of a traversing particle by analyzing the resulting charge cluster in a single layer of silicon. Customized machine learning (ML) models based on mixture density networks are capable of extracting track angles and hit positions, as well as uncertainties on these...
Real-time machine learning is emerging as a key tool for next-generation detector systems, where strict latency and hardware constraints require highly efficient models. We present PQuant, a backend-agnostic Python library designed to unify and streamline pruning and quantization techniques for hardware deployment, supporting both PyTorch and TensorFlow. PQuant provides a comprehensive suite...
We present a high-speed, modular Data Acquisition (DAQ) solution developed for Pitt-CoRTEx (Pitt-Cosmic Ray Tracker Experiment), a compact and scalable muon tracking detector designed for educational and small-scale particle physics applications. The detector consists of 128 extruded plastic scintillator bars, each embedded with a wavelength-shifting (WLS) optical fiber that guides light to...
