Related papers: Real-Time Data Processing in the Muon System of th…
The Super Proton Synchrotron (SPS) is the last stage in the injector chain for CERN's Large Hadron Collider, and it also provides proton and ion beams for several fixed-target experiments. The SPS has been in operation since 1976, and it…
The Compact Muon Solenoid (CMS) detector at the CERN Large Hadron Collider (LHC) is undergoing an extensive Phase II upgrade program to prepare for the challenging conditions of the High-Luminosity LHC (HL-LHC). A new timing layer is…
This paper presents a novel data detector ASIC for massive multiuser multiple-input multiple-output (MU-MIMO) wireless systems. The ASIC implements a modified version of the large-MIMO approximate message passing algorithm (LAMA), which…
Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition system architectures, in which the live acquisition of data and their processing are decoupled through a storage…
For image-related deep learning tasks, the first step often involves reading data from external storage and performing preprocessing on the CPU. As accelerator speed increases and the number of single compute node accelerators increases,…
The ATLAS experiment at the Large Hadron Collider (LHC) at CERN is currently waiting to record the first collision data in spring 2009. Its muon spectrometer is designed to achieve a momentum resolution of 10% pT(mu) = 1 TeV/c. The…
Muon Spin Rotation, Relaxation and Resonance ({\mu}SR) technology has an irreplaceable role in studying the microstructure and properties of materials, especially micro-magnetic properties. An experimental muon source is being built in…
Gradient orthogonalization is a simple strategy that shows great utility in speeding up gradient descent. The Muon optimizer (Jordan, Jin, et al., 2024) combines gradient orthogonalization with first-order momentum and achieves significant…
In particle detectors at the Large Hadron Collider, tens of terabytes of data are produced every second from proton-proton collisions occurring at a rate of 40 megahertz. This data rate is reduced to a sustainable level by a real-time event…
A single calorimeter station for the Muon $g-2$ experiment at Fermilab includes the following subsystems: a 54-element array of PbF$_{2}$ Cherenkov crystals read out by large-area SiPMs, bias and slow-control electronics, a suite of 800…
With the advent of the 5G wireless networks, achieving tens of gigabits per second throughputs and low, milliseconds, latency has become a reality. This level of performance will fuel numerous real-time applications, such as autonomy and…
In recent times, the trend in very large scale integration (VLSI) industry is multi-dimensional, for example, reduction of energy consumption, occupancy of less space, precise result, less power dissipation, faster response. To meet these…
Autonomous robots require efficient on-device learning to adapt to new environments without cloud dependency. For this edge training, Microscaling (MX) data types offer a promising solution by combining integer and floating-point…
The planned luminosity increase at the Large Hadron Collider in the coming years has triggered interest in the use of the particles' time of arrival as additional information in specialized detectors to mitigate the impact of pile-up. The…
Optical packet header recognition is an important signal processing task of optical communication networks. In this work, we propose an all-optical reservoir, consisting of integrated double-ring resonators (DRRs) as nodes, for fast and…
The fast-rising demand for wireless bandwidth requires rapid evolution of high-performance baseband processing infrastructure. Programmable many-core processors for software-defined radio (SDR) have emerged as high-performance baseband…
We report on the development, implementation, and performance of a fast neural network used to measure the transverse momentum in the CMS Level-1 Endcap Muon Track Finder. The network aims to improve the triggering efficiency of muons…
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads…
In modern computer architectures, the performance of many memory-bound workloads (e.g., machine learning, graph processing, databases) is limited by the data movement bottleneck that emerges when transferring large amounts of data between…
In this work, we provide a comprehensive study of fermion-portal dark matter models in the freeze-in regime at a future muon collider. For different possible non-singlet fermion portals, we calculate the upper bound on the mediator's mass…