相关论文: The Neural Network First-Level Hardware Track Trig…
We present the concept of a track trigger for the Belle II experiment, based on a neural network approach, that is able to reconstruct the z (longitudinal) position of the event vertex within the latency of the first level trigger. The…
The Belle II experiment at the SuperKEKB accelerator is designed to explore physics beyond the Standard Model with unprecedented luminosity. As the beam intensity increased, the experiment faced significant challenges due to higher…
One of the major components of the Belle II trigger system is the neural network trigger. Its task is to estimate the z-Vertex particle tracks observed in the experiments drift chamber. The trigger is implemented on FPGAs to ensure…
The Belle II experiment will go into operation at the upgraded SuperKEKB collider in 2016. SuperKEKB is designed to deliver an instantaneous luminosity $\mathcal{L}=8\times10^{35}\,\mathrm{cm}^{-2}\,\mathrm{s}^{-1}$. The experiment will…
The future Belle II experiment will employ a computer-farm based data reduction system for the readout of its innermost detector, a DEPFET-technology based silicon detector with pixel readout. A large fraction of the background hits can be…
The Belle~II experiment operates at high luminosity, where an increasing beam-induced background imposes stringent demands on the hardware Level-1 trigger system, which must operate under tight latency and bandwidth constraints. To achieve…
The Belle~II experiment is designed to search for physics beyond the Standard Model by investigating rare decays at the SuperKEKB \(e^{+}e^{-}\) collider. Owing to the significant beam background at high luminosity, the data acquisition…
We describe a neural network for predicting the background hit rate in the Belle II detector produced by the SuperKEKB electron-positron collider. The neural network, BGNet, learns to predict the individual contributions of different…
The Belle II detector at the SuperKEKB accelerator has a level 1 trigger implemented in field-programmable gate arrays. Due to the high luminosity of the beam, a trigger that effectively rejects beam induced background is required. A three…
High backgrounds and detector ageing impact the track finding in the Belle II central drift chamber, reducing both track purity and track efficiency in events. This necessitates the development of new track finding algorithms to mitigate…
Neurons in the nervous system exhibit an outstanding variety of morphological and physiological properties. However, close to threshold, this remarkable richness may be grouped succinctly into two basic types of excitability, often referred…
The Belle II experiment at the SuperKEKB $e^{+}e^{-}$ collider in KEK, Japan, started physics data-taking with a complete detector from early 2019 with the primary physics goal of probing new physics in heavy quark and lepton decays. An…
The Belle II experiment at the SuperKEKB collider at KEK, Tsukuba, Japan has successfully started taking data with the full detector in March 2019. Belle II is a luminosity frontier experiment of the new generation to search for physics…
An unconventional solution for finding the location of event creation is presented. It is based on two feed-forward neural networks with fixed architecture, whose parameters are chosen so as to reach a high accuracy. The interaction point…
The Pixel Detector is the innermost detector of the tracking system of the Compact Muon Solenoid (CMS) experiment at CERN Large Hadron Collider (LHC). It precisely determines the interaction point (primary vertex) of the events and the…
The extended physics program of the SuperCDMS SNOLAB dark matter search experiment aims to maximize the sensitivity to low-mass dark matter. To realize this, an upgrade of the existing level-1 trigger of the data acquisition system is…
We present the study of an end-to-end multi-track reconstruction algorithm for the central drift chamber of the Belle II experiment at the SuperKEKB collider using Graph Neural Networks for an unknown number of particles. The algorithm uses…
The extremely high rate of events that will be produced in the future Large Hadron Collider requires the triggering mechanism to take precise decisions in a few nano-seconds. We present a study which used an artificial neural network…
The Silicon Vertex Detector of Belle II is a state-of-the-art tracking and vertexing system based on double-sided silicon strip sensors, designed and fabricated by a large international collaboration in the period 2012--2018. Since 2019 it…
Using simulated collider data for $p+p\rightarrow 2{\rm Jets}\ $ interactions in a 2-barrel pixel detector, a neural network is trained to construct the coordinate of the primary vertex to a high degree of accuracy. Three other estimates of…