Related papers: Development of Convolutional Neural Networks for a…
The hybrid pixel detector Timepix3 allows the measurement of the time and energy deposition of an event simultaneously in each 55 $\mu$m pixel, which makes Timepix3 a promising approach for a compact Compton camera. However, the angular…
We present our study on the reconstruction of photoelectron tracks in gas pixel detectors used for astrophysical X-ray polarimetry. Our work aims to maximize the performance of convolutional neural networks (CNNs) to predict the impact…
The detection of photons with energies greater than a few tenths of an MeV, interacting via Compton scattering and/or pair production, faces a number of difficulties. The reconstruction of single-scatter Compton events can only determine…
A neutron time projection chamber can locate the approximate direction of a neutron hot spot with high efficiency and a 4{\pi} field of view. The angular resolution can be significantly improved by adding several plastic scintillation…
The Liquid Xenon Gamma-Ray Imaging Telescope (LXeGRIT) is the first realization of a liquid xenon time projection chamber for Compton imaging of MeV gamma-ray sources in astrophysics. By measuring the energy deposit and the three spatial…
This paper presents a data processing algorithm with machine learning for polarization extraction and event selection applied to photoelectron track images taken with X-ray polarimeters. The method uses a convolutional neural network (CNN)…
MeV gamma-rays provide a unique window for the direct measurement of line emissions from radioisotopes, but observations have made little significant progress after COMPTEL/{\it CGRO}. To observe celestial objects in this band, we are…
We have developed an Electron Tracking Compton Camera (ETCC), which provides a well-defined Point Spread Function (PSF) by reconstructing a direction of each gamma as a point and realizes simultaneous measurement of brightness and spectrum…
In the context of modeling spectral energy distributions (SEDs) for blazars, we extend the method that uses a convolutional neural network (CNN) to include external inverse Compton processes. The model assumes that relativistic electrons…
Accurate real-time pose estimation of spacecraft or object in space is a key capability necessary for on-orbit spacecraft servicing and assembly tasks. Pose estimation of objects in space is more challenging than for objects on Earth due to…
The cross section of atomic electron Compton scattering $\gamma + e \rightarrow \gamma^\prime + e^\prime $ was measured in the 4.40--5.475 GeV photon beam energy region by the {\em PrimEx} collaboration at Jefferson Lab with an accuracy of…
The Compton camera is a promising alternative to the Anger camera for imaging gamma radiation, with the potential to significantly increase the sensitivity of SPECT. Two-dimensional Compton camera image reconstruction can be implemented by…
The coherent elastic scattering of neutrinos on nuclei, also known as CEvNS, has been studied for several years by the COHERENT program of experiments using neutrinos from stopped-pion decays produced at the Spallation Neutron Source (SNS).…
We have developed a compact Compton gamma-ray imager with a large field of view and a low channel-count that is capable of quickly localizing gamma-ray sources in the few hundred keV - several MeV range. The two detector planes (scatter and…
The adaptability of the convolutional neural network (CNN) technique for aerodynamic meta-modeling tasks is probed in this work. The primary objective is to develop suitable CNN architecture for variable flow conditions and object geometry,…
The Mega electron volt (MeV) gamma-ray observation is a promising diagnostic tool for observing the universe. However, the sensitivity of MeV gamma-ray telescopes is limited due to peculiar backgrounds, restricting the application of MeV…
In this work, we report on the advantageous aspects of the i-TED Compton imager for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that…
We propose a machine learning method to investigate the propagation of cosmic rays based on the precisely measured spectra of the primary and secondary cosmic ray nuclei of Li, Be, B, C, and O from AMS-02, ACE, and Voyager-1. We train two…
Point cloud analysis is an area of increasing interest due to the development of 3D sensors that are able to rapidly measure the depth of scenes accurately. Unfortunately, applying deep learning techniques to perform point cloud analysis is…
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…