Related papers: Development of a resource-efficient FPGA-based neu…

This study presents advanced neural network architectures including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTMs), and Deep Belief Networks (DBNs) for enhanced ECG signal…

The performance of the three-level ATLAS muon trigger as evaluated by using LHC data is presented. Events have been selected by using only the hardware-based Level-1 trigger in order to commission and to subsequently enable the…

The innermost station of the present ATLAS forward muon detector needs to be upgraded for the super-LHC. We present a proposal to replace it with a sandwiched detector composed of several layers of small-radius Monitored Drift Tube chambers…

After successfully completing Phase I upgrades during LHC Long Shutdown 2, the ATLAS detector is back in operation with several upgrades implemented. The most important and challenging upgrade is in the Muon Spectrometer, where the two…

The ATLAS Trigger system is a key component of the ATLAS experiment at the CERN Large Hadron Collider (LHC), designed to reduce the event rate from the 40 MHz proton-proton bunch crossing frequency to an output suitable for offline storage…

An extensive system test of the ATLAS muon spectrometer has been performed in the H8 beam line at the CERN SPS during the last four years. This spectrometer will use pressurized Monitored Drift Tube (MDT) chambers and Cathode Strip Chambers…

In view of the large amount of calculation and long calculation time of convolutional neural network (CNN), this paper proposes a convolutional neural network hardware accelerator based on field programmable logic gate array (FPGA). First,…

The ATLAS detector at LHC will require a Trigger system to efficiently select events down to a manageable event storage rate of about 400 Hz. By 2015 the LHC instantaneous luminosity will be increased up to 3 x 10^34 cm-2s-1, this…

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…

Recent advancements in large language models (LLMs) boasting billions of parameters have generated a significant demand for efficient deployment in inference workloads. The majority of existing approaches rely on temporal architectures that…

Keyword Spotting nowadays is an integral part of speech-oriented user interaction targeted for smart devices. To this extent, neural networks are extensively used for their flexibility and high accuracy. However, coming up with a suitable…

We present a programmable time alignment scheme used in an ASIC for the ATLAS forward muon trigger development. The scheme utilizes regenerated clocks with programmable phases to compensate for the timing offsets introduced by different…

The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient…

The planned high-luminosity upgrade of the Large Hadron Collider (LHC) at CERN will bring much higher data rates that are far above the capabilities of currently installed software-based data processing systems. Therefore, new methods must…

The increase in open-source availability of Large Language Models (LLMs) has enabled users to deploy them on more and more resource-constrained edge devices to reduce reliance on network connections and provide more privacy. However, the…

The ATLAS trigger has been used very successfully for the online event selection during the first part of the second LHC run (Run-2) in 2015/16 at a center-of-mass energy of 13 TeV. The trigger system is composed of a hardware Level-1…

Highly selective first-level triggers are essential to exploit the full physics potential of the ATLAS experiment at High-Luminosity LHC (HL-LHC). The concept for a new muon trigger stage using the precision monitored drift tube (MDT)…

We present a systematic study of Tensor Network (TN) models $\unicode{x2013}$ Matrix Product States (MPS) and Tree Tensor Networks (TTN) $\unicode{x2013}$ for real-time jet tagging in high-energy physics, with a focus on low-latency…

In hadron collider experiments, triggering the detector to store interesting events for offline analysis is a challenge due to the high rates and multiplicities of particles produced. Maintaining high trigger efficiency for the physics we…

The SeaQuest experiment (Fermilab E906) detects pairs of energetic {\mu}+ and {\mu}- produced in 120 GeV/c proton-nucleon interactions in a high rate environment. The trigger system consists of several arrays of scintillator hodoscopes and…