相关论文: Fast simulation of muons produced at the SHiP expe…

This paper concerns with the production of synthetic phasor measurement unit (PMU) data for research and education purposes. Due to the confidentiality of real PMU data and no public access to the real power systems infrastructure…

The underground muon detector of the Pierre Auger Observatory is aimed at attaining direct measurements of the muonic component of extensive air showers produced by cosmic rays with energy from $10^{16.5}$ eV up to the region of the ankle…

In this study, we exhibit a number elementary strategies that might be at disposal in diverse computational applications in the GEANT4 simulations with the purpose of hemispherical particle sources. To further detail, we initially generate…

In this paper, we propose a multi-generator extension to the adversarial training framework, in which the objective of each generator is to represent a unique component of a target mixture distribution. In the training phase, the generators…

Photon detection is important for liquid argon detectors for direct dark matter searches or neutrino property measurements. Precise simulation of photon transport is widely used to understand the probability of photon detection in liquid…

Generative adversarial networks (GANs) are capable of generating strikingly realistic samples but state-of-the-art GANs can be extremely computationally expensive to train. In this paper, we propose the fused propagation (FusedProp)…

In this work we demonstrate that generative adversarial networks (GANs) can be used to generate realistic pervasive changes in remote sensing imagery, even in an unpaired training setting. We investigate some transformation quality metrics…

We present results from a detailed GEANT4 simulation of a proposed Muon Tomography System that employs compact Micro Pattern Gas Detectors with high spatial resolution. A basic Point-Of-Closest-Approach algorithm is applied to reconstructed…

We use PYTHIA event generator to simulate the process of muon pair production in antiproton scattering upon the proton target at the energy of the antiproton equal to $14GeV$, which may be one of the energies for the future PANDA (GSI,…

One of the most challenges in medical imaging is the lack of data. It is proven that classical data augmentation methods are useful but still limited due to the huge variation in images. Using generative adversarial networks (GAN) is a…

In this paper, a novel strategy of Secure Steganograpy based on Generative Adversarial Networks is proposed to generate suitable and secure covers for steganography. The proposed architecture has one generative network, and two…

Proton beam dump experiments are among the most promising strategies to search for light and feebly interacting states such as axion-like particles (ALPs). The interpretation of these experiments is however complicated by the wide range of…

The identification and reconstruction of charged particles, such as muons, is a main challenge for the physics program of the ATLAS experiment at the Large Hadron Collider. This task will become increasingly difficult with the start of the…

Different types of neural networks have been used to solve the flow sensing problem in turbulent flows, namely to estimate velocity in wall-parallel planes from wall measurements. Generative adversarial networks (GANs) are among the most…

A new muon and pion capture system is proposed for the China Spallation Neutron Source (CSNS), currently under construction. Using about 4\% of the pulsed proton beam (1.6 GeV, 4 kW and 1 Hz) of CSNS to bombard a cylindrical graphite target…

In Fermilab's neutrino facilities such as the Neutrinos at the Main Injector (NuMI) and the upcoming Long Baseline Neutrino Facility (LBNF), a proton beam strikes high-power target, producing positively and negatively charged pions and…

To address the possible lack or total absence of pulses from particle detectors during the development of its associate electronics, we propose a model that can generate them without losing the features of the real ones. This model is based…

A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated using MadGraph5 + Pythia8, and Delphes3 fast detector…

Simulating detector responses is a crucial part of understanding the inner-workings of particle collisions in the Large Hadron Collider at CERN. The current reliance on statistical Monte-Carlo simulations strains CERN's computational grid,…

Muon beams are customarily obtained via $K/\pi$ decays produced in proton interaction on target. In this paper we investigate the possibility to produce low emittance muon beams from electron-positron collisions at centre-of-mass energy…