Related papers: Using a neural network approach for muon reconstru…
The implementation of convolutional neural networks in programmable logic, for applications in fast online event selection at hadron colliders is studied. In particular, an approach based on full event images for classification is studied,…
Due to the huge interaction rates and the tough experimental environment of pp collisions at a centre-of-mass energy sqrt(s)=14TeV and luminosities of up to 10^34 cm^-2 s^-1, one of the experimental challenges at the LHC is the triggering…
The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton…
The ATLAS detector at CERN's Large Hadron Collider will be exposed to proton-proton collisions from beams crossing at 40 MHz. A three-level trigger system was designed to select potentially interesting events and reduce the incoming rate to…
In this work we explore the application of deep neural networks to the optimization of atomic layer deposition processes based on thickness values obtained at different points of an ALD reactor. We introduce a dataset designed to train…
An FPGA-based online trigger system has been developed for the COMET Phase-I experiment. This experiment searches for muon-to-electron conversion, which has never been observed yet. A drift chamber and trigger counters detect a…
An artificial neural network algorithm is implemented using a field programmable gate array hardware. One hidden layer is used in the feed-forward neural network structure in order to discriminate one class of patterns from the other class…
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)…
The performance of the ATLAS muon trigger system is evaluated with proton-proton collision data collected in 2012 at the Large Hadron Collider at a centre-of-mass energy of 8 TeV. It is primarily evaluated using events containing a pair of…
The Level-1 Muon Barrel Trigger of the ATLAS Experiment at LHC makes use of Resistive Plate Chamber (RPC) detectors. The on-detector trigger electronics modules are able to identify muons with predefined transverse momentum values (pT) by…
We demonstrate the use of neural networks to accelerate the reaction steps in the MAESTROeX stellar hydrodynamics code. A traditional MAESTROeX simulation uses a stiff ODE integrator for the reactions; here we employ a ResNet architecture…
The Muon Spectrometer (MS) of the ALICE experiment at LHC is equipped with a HLT (High Level Trigger), whose aim is to improve the accuracy of the trigger cuts delivered at the L0 stage. A computational challenge of real-time event…
Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models…
The Muon Collider, recently highlighted as Recommendation 1 in the U.S. National Academies report on Elementary Particle Physics, offers a unique opportunity for fixed-target experiments with high energy and luminosity. This paper outlines…
This paper presents an implementation of multilayer feed forward neural networks (NN) to optimize CMOS analog circuits. For modeling and design recently neural network computational modules have got acceptance as an unorthodox and useful…
The trigger systems of the LHC detectors play a crucial role in determining the physics capabilities of the experiments. A reduction of several orders of magnitude of the event rate is needed to reach values compatible with the detector…
The choice of architecture of artificial neuron network (ANN) is still a challenging task that users face every time. It greatly affects the accuracy of the built network. In fact there is no optimal method that is applicable to various…
With the high bunch-crossing and interaction rates and potentially large event sizes the experiments at the LHC challenge data acquisition and trigger systems. Within the ATLAS experiment, a multi-level trigger system based on hardware and…
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…
The topology of artificial neural networks has a significant effect on their performance. Characterizing efficient topology is a field of promising research in Artificial Intelligence. However, it is not a trivial task and it is mainly…