Related papers: Deep Learning-Based Classification of Gamma Photon…
To detect and track structural changes in atomic nuclei, the systematic study of nuclear levels with firm spin-parity assignments is important. While linear polarization measurements have been applied to determine the electromagnetic…
Photon counting detectors (PCDs) bring valuable advantages to diagnostic computed tomography (CT), including lower noise and higher resolution than energy integrating detectors. However, there are still several nonideal factors preventing…
Methods of gamma-gamma, gamma-electron luminosities measurement at photon colliders based on Compton scattering of laser photons on high energy electrons at linear colliders are considered.
Diverse searches for direct dark matter (DM) in effective electromagnetic and leptophilic interactions resulting from new physics, as well as Weakly Interacting Massive Particles (WIMPs) with unconventional electronic recoils, are…
We have developed a neural network model to perform event reconstruction of Compton telescopes. This model reconstructs events that consist of three or more interactions in a detector. It is essential for Compton telescopes to determine the…
Two-photon events at the LHC are characterized by the protons scattered at very small angles and the particles centrally produced via the photon-photon fusion. To select these events from the huge samples of generic pp interactions a…
The purpose of this project is to investigate the use of charge couple devices (CCDs) to detect electrons directly. This can be done in transmission electron microscopy (TEM) for electrons over 100 KeV, but for space plasma instruments,…
Excitons in atomically-thin semiconductors interact very strongly with electromagnetic radiation and are necessarily close to a surface. Here, we exploit the deep-subwavelength confinement of surface plasmon polaritons (SPPs) at the edge of…
We present a deep learning, computer vision algorithm constructed for the purposes of identifying and classifying charged particles in camera image sensors. We apply our algorithm to data collected by the Distributed Electronic Cosmic-ray…
Diagnostics are critical on the path to commercial fusion reactors, since measurements and characterisation of the plasma is important for sustaining fusion reactions. Gamma spectroscopy is commonly used to provide information about the…
We provide a fast approach incorporating the usage of deep learning for evaluating the effects of photon sensors in an antineutrino detector on the event reconstruction performance therein. This work is an attempt to harness the power of…
We present a Machine Learning based approach to the cross section and asymmetries for deeply virtual Compton scattering from an unpolarized proton target using both an unpolarized and polarized electron beam. Machine learning methods are…
We propose new concepts for experiments in which intense high energy photon or muon beams are employed parasitically to detect scattering by cosmic heavy weakly interacting dark matter (DM) particles. We show that the scattering…
Simulation studies and spectroscopic measurements are presented regarding the development of a pixel multilayer CdTe detector under development in the context of the COCAE project. The instrument will be used for the localization and…
Liquid scintillator detectors are widely used in neutrino experiments due to their low energy threshold and high energy resolution. Despite the tiny abundance of $^{14}$C in LS, the photons induced by the $\beta$ decay of the $^{14}$C…
We have modeled, tested, and installed a large, cerium-activated Gd2SiO5 crystal scintillator for use as a detector of gamma rays. We present the measured detector response to two types of incident photons: nearly monochromatic photons up…
The interaction of radiation with liquid xenon, inducing both scintillation and ionization signals, is of particular interest for Compton-sequences reconstruction. We report on the development and recent results of a liquid-xenon…
Metamaterials have recently established a new paradigm for enhanced light absorption in state-of-the-art photodetectors. Here, we demonstrate broadband, highly efficient, polarization-insensitive, and gate-tunable photodetection at room…
Microtubule networks (MTs) are a component of a cell that may indicate the presence of various chemical compounds and can be used to recognize properties such as treatment resistance. Therefore, the classification of MT images is of great…
By implementing the bremsstrahlung with Monte Carlo algorithm into the particle-in-cell code, the bremsstrahlung and nonlinear Compton scattering can be studied simultaneously in comparison way in the laser plasma interactions. The…