The WaveDAQ integrated Trigger and Data Acquisition System for the MEG II experiment

The WaveDAQ is a newly-designed digitization Trigger and Data AcQuisition system (TDAQ) allowing Multi-gigasample waveform recording on a large amount of channels (up to 16384) by using the DRS4 analog switched capacitor array as downconverting ASIC. A high bandwidth, programmable input stage has been coupled with a bias generator to allow SiPM operation without need of any other external apparatus. The trigger generation is tightly coupled within the system to limit the required depth of the analog memory, allowing faster digitization speeds. This system has been designed for the MEG experiment upgrade but also proved to be highly scalable and already found other applications.Comment: This manuscript is for conference record of the 21st IEEE Real Time conference onl

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

The WaveDAQ integrated Trigger and Data Acquisition System for the MEG II experiment

The WaveDAQ is a newly-designed digitization Trigger and Data AcQuisition system (TDAQ) allowing Multi-gigasample waveform recording on a large amount of channels (up to 16384) by using the DRS4 analog switched capacitor array as downconverting ASIC. A high bandwidth, programmable input stage has been coupled with a bias generator to allow SiPM operation without need of any other external apparatus. The trigger generation is tightly coupled within the system to limit the required depth of the analog memory, allowing faster digitization speeds. This system has been designed for the MEG experiment upgrade but also proved to be highly scalable and already found other applications

The Mu3e Data Acquisition

International audienceThe Mu3e experiment aims to find or exclude the lepton flavour violating decay $\mu^+\to e^+e^-e^+$ with a sensitivity of one in 10$^{16}$ muon decays. The first phase of the experiment is currently under construction at the Paul Scherrer Institute (PSI, Switzerland), where beams with up to 10$^8$ muons per second are available. The detector will consist of an ultra-thin pixel tracker made from High-Voltage Monolithic Active Pixel Sensors (HV-MAPS), complemented by scintillating tiles and fibres for precise timing measurements. The experiment produces about 100 Gbit/s of zero-suppressed data which are transported to a filter farm using a network of FPGAs and fast optical links. On the filter farm, tracks and three-particle vertices are reconstructed using highly parallel algorithms running on graphics processing units, leading to a reduction of the data to 100 Mbyte/s for mass storage and offline analysis. The paper introduces the system design and hardware implementation of the Mu3e data acquisition and filter farm

The trigger system for the MEG II experiment

Intending to improve the current sensitivity on decay by one order of magnitude, the MEG II experiment at Paul Scherrer Institute completed the integration phase in 2021 with all detectors successfully operated throughout the subsequent beamtime. Earlier in 2021, the WaveDAQ integrated Trigger and Data Acquisition (TDAQ) system, developed for the readout of the experiment, was completely commissioned. Receiving almost 9000 channels from the detectors, the MEG II TDAQ system is the largest WaveDAQ deployment so far, proving the scalability of the overall design, from bench-top setup through various smaller-size experiments. We will describe how MEG II trigger system reduces the muon decays at the experiment target down to a 10 Hz event rate by exploiting the signal event characteristics at the online level. The trigger system performs the calorimetric reconstruction of the photon shower and then compares the timing and direction with positron candidates within a 600 ns hard latency time. The first release of the online reconstruction, deployed in 2021, achieved a photon energy resolution at the signal energy of and a coincidence time resolution among the child particles