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 one-dimensional convolutional neural networks, are promising when dealing with digital signals from nuclear detectors. Simulations and experiments demonstrate the satisfactory accuracy and additional benefits of...
The LHCb (Large Hadron Collider beauty) experiment is designed to study differences between particles and anti-particles as well as very rare decays in the charm and beauty sector at the LHC. With the major upgrade done in view of Run 3, the detector will read-out all events at the full LHC frequency of 40 MHz, the online system will be subjected to a considerably increased data rate, reaching...
The LHCb experiment has gone through a major upgrade for LHC's Run-3, scheduled to start in the middle of 2022. The entire readout system has been replaced by Front-End and Back-End electronics that are able to record LHC events at the full LHC bunch rate of 40MHz.
In order to maintain synchronicity across the full system, clock and control commands are originated from a single Readout...
The MTCA.4 standard is widely used in developing advanced data acquisition and processing solutions in the big physics community. The number of applications implemented using commercial MTCA AMC cards using XILINX and IntelFPGA systems on chips is growing due to the flexibility and scalability of these reconfigurable hardware devices and their suitability to implement intelligent applications...
This paper presents an reactive, actor-model and FBP paradigm based framework that we develop to design data-stream processing applications for HEP and NP. This framework encourages a functional decomposition of the overall data processing application into small mono-functional artifacts. Artifacts that are easy to understand, develop, deploy and debug. The fact that these artifacts (actors)...
