Related papers: Using TMine for the Fermi-LAT Event Analysis

The ALICE experiment at CERN LHC is specifically designed for investigating heavy ion collisions. The upgraded ALICE accommodates a tenfold increase in PbPb luminosity and a two-order of magnitude surge in minimum bias events. To address…

The Data Handling Pipeline ("Pipeline") has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data…

The Large Area Telescope (LAT) on-board the Fermi Gamma-ray Space Telescope started nominal operations on August 13, 2008, after about 60 days of instrument checkout and commissioning and is currently performing an all-sky gamma-ray survey…

Latte (for LATent Tensor Evaluation) is a Python library for evaluation of latent-based generative models in the fields of disentanglement learning and controllable generation. Latte is compatible with both PyTorch and TensorFlow/Keras, and…

The Large Area Telescope (LAT) instrument on board the Fermi satellite consists of a multi-layer silicon-strip tracker interleaved with tungsten converters (TKR), followed by a CsI crystal hodoscopic calorimeter (CAL). Sixteen TKR and CAL…

Four years into the mission, the understanding of the performance of the Fermi Large Area Telescope (LAT) and data analysis have increased enormously since launch. Thanks to a careful analysis of flight data, we were able to trace back some…

Event extraction has gained extensive research attention due to its broad range of applications. However, the current mainstream evaluation method for event extraction relies on token-level exact match, which misjudges numerous…

The Large Area Telescope (LAT) onboard the Fermi satellite is observing the gamma-ray sky in the high energy region, above 20 MeV. We have developed a method to reconstruct the energy spectra of the gamma-rays detected by the Fermi LAT…

This paper is a sequel to an evolving research project on a diagrammatic methodology called thinging machine (TM). Initially, it was proposed as a base for conceptual modelling (e.g., conceptual UML) in areas such as requirement…

State-of-the-art automatic event detection struggles with interpretability and adaptability to evolving large-scale key events -- unlike episodic structures, which excel in these areas. Often overlooked, episodes represent cohesive clusters…

A novel application of machine-learning (ML) based image processing algorithms is proposed to analyze an all-sky map (ASM) obtained using the Fermi Gamma-ray Space Telescope. An attempt was made to simulate a one-year ASM from a…

This contribution describes the experience with the application of different Machine Learning (ML) techniques to a physics analysis case. The use case chosen is the classification of top-antitop events coming from BSM or from SM using data…

The planned Cherenkov Telescope Array (CTA) is a future observatory for very-high-energy (VHE) gamma-ray astronomy composed of one site per hemisphere. It aims at 10 times better sensitivity, a better angular resolution and wider energy…

In this contribution we present the FAST, which is a comprehensive software suite that aims to streamline and automatically manage the forecast of atmospheric and astroclimatic parameters (provided respectively by Meso-Nh and Astro-Meso-Nh…

Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learning techniques have been extremely successful in…

Machine learning-based interatomic potentials and force fields depend critically on accurate atomic structures, yet such data are scarce due to the limited availability of experimentally resolved crystals. Although atomic-resolution…

Arrays of imaging atmospheric Cherenkov telescopes (IACT) are superb instruments to probe the very-high-energy gamma-ray sky. This type of telescope focuses the Cherenkov light emitted from air showers, initiated by very-high-energy gamma…

The Gamma-ray Large Area Space Telescope (GLAST) is an observatory designed to perform gamma-ray astronomy in the energy range 20 MeV to 300 GeV, with supporting measurements for gamma-ray bursts from 10 keV to 25 MeV. GLAST will be…

We describe a statistical reconstruction methodology for the GLAST LAT. The methodology incorporates in detail the statistics of the interactions of photons and charged particles with the tungsten layers in the LAT, and uses the scattering…

The Fermi Large Area Telescope has enabled detailed studies of high-energy astrophysical sources. To support analysis, we present FermiPhased, a flexible, open-source tool for phase-resolved studies of pulsars, binaries, and other…