Related papers: The Fermilab Test Beam Facility Data Acquisition S…
By exploiting a causality property of the nonlinear Fourier transform, a novel decision-feedback detection strategy for nonlinear frequency-division multiplexing (NFDM) systems is introduced. The performance of the proposed strategy is…
At MAX IV pixelated area detectors are operated at high frame rates to take advantage of the X-ray beam properties available from the fourth generation synchrotron in scattering, diffraction and imaging applications. A variety of photon…
As a promising approach to deal with distributed data, Federated Learning (FL) achieves major advancements in recent years. FL enables collaborative model training by exploiting the raw data dispersed in multiple edge devices. However, the…
Federated Learning (FL) has emerged as a compelling methodology for the management of distributed data, marked by significant advancements in recent years. In this paper, we propose an efficient FL approach that capitalizes on additional…
A VME-based data acquisition system for beam-loss monitors has been developed and is in use in the Tevatron and Main Injector accelerators at the Fermilab complex. The need for enhanced beam-loss protection when the Tevatron is operating in…
We present the optimization and performance characterization of the second-generation Fermilab Constant Fraction Discriminator ASIC (FCFD), designed for the readout of AC-coupled low-gain avalanche detector (LGAD) strip-sensors. The FCFD is…
The Intensity Frontier (IF) experiments at Fermilab require computing, software, data handling, and infrastructure development for detector and beamline design and to extract maximum scientific output from the data. The emphasis of…
A remote data acquisition chassis, called a HOTLink Rack Monitor, HRM, has been developed for use in the Fermilab control system. This chassis provides for 64 analog input channels, 8 analog output channels, and 8 bytes of digital I/O. The…
The Time-of-Flight system is a proposed addition to the STAR detector currently installed at RHIC. The proposal is based on a new technology called the Multi-gap Resistive Plate Chamber (MRPC), and consists of approximately 23,000 channels…
The real-time data processing of the next generation of experiments conducted at FAIR requires a reliable reconstruction of event topologies and, therefore, will depend heavily on in-situ calibration procedures. A neural network-based…
Due to the distributed characteristics of Federated Learning (FL), the vulnerability of global model and coordination of devices are the main obstacle. As a promising solution of decentralization, scalability and security, leveraging…
The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To operate high current beam, accelerators must…
Although CMS will not start operation for several years, many subdetector groups have active testbeam programs involving final or near-final electronics. The high-bandwidth electronics require the development of new DAQ systems including…
The XENONnT detector uses the latest and largest liquid xenon-based time projection chamber (TPC) operated by the XENON Collaboration, aimed at detecting Weakly Interacting Massive Particles and conducting other rare event searches. The…
This paper presents the design and implementation of the front-end electronics and the data acquisition (DAQ) system for readout of multi-wire drift chambers (MWDC). Apart of the conventional drift time measurement the system delivers the…
A collaboration between Fermilab and the Institute for High Energy Physics (IHEP), Beijing, has developed a beam position monitor for the IHEP test beam facility. This telescope is based on 5 stations of silicon strip detectors having a…
FAST is a facility at Fermilab that consists of a photoinjector, two superconducting capture cavities, one superconducting ILC-style cryomodule, and a small ring for studying non-linear, integrable beam optics called IOTA. This paper…
Federated Learning (FL) as a promising distributed machine learning paradigm has been widely adopted in Artificial Intelligence of Things (AIoT) applications. However, the efficiency and inference capability of FL is seriously limited due…
Early detection of atrial fibrillation (AFib) is challenging due to its asymptomatic and paroxysmal nature. However, advances in deep learning algorithms and the vast collection of electrocardiogram (ECG) data from devices such as the…
Ensuring reliable data collection in large-scale particle physics experiments demands Data Quality Monitoring (DQM) procedures to detect possible detector malfunctions and preserve data integrity. Traditionally, this resource-intensive task…