arXiv subjects

Andrii Tykhonov

Publications and source records attributed to Andrii Tykhonov.

14 recordsLinked to original sources

arXiv2026

Machine-learning correction for the calorimeter saturation of cosmic-ray ions with the Dark Matter Particle Explorer: towards the PeV scale

The Dark MAtter Particle Explorer (DAMPE) instrument is a space-borne cosmic-ray detector, capable of measuring ion fluxes up to $\sim$500 TeV/n. This energy scale is made accessible through its calorimeter, which is the deepest currently operating in orbit. Saturation of the calorimeter readout channels starts occurring above $\sim$100 TeV of incident energy, and can significantly affect the primary energy reconstruction. Different techniques -- analytical and machine-learning based -- were developed to tackle this issue, focusing on the recovery of single-bar deposits, up to several hundreds of TeV. In this work, a new machine-learning technique is presented, which benefits from a unique model to correct the total deposited energy in DAMPE calorimeter. The described method is able to generalise its corrections for different ions and extend the maximum detectable incident energy to the PeV scale. This work is a continuation of the results presented in [1].

astro-ph.HE↗

arXiv2025

The enhanced X-ray Timing and Polarimetry mission -- eXTP for launch in 2030

In this paper we present the current status of the enhanced X-ray Timing and Polarimetry mission, which has been fully approved for launch in 2030. eXTP is a space science mission designed to study fundamental physics under extreme conditions of matter density, gravity, and magnetism. The mission aims at determining the equation of state of matter at supra-nuclear density, measuring the effects of quantum electro-dynamics, and understanding the dynamics of matter in strong-field gravity. In addition to investigating fundamental physics, the eXTP mission is poised to become a leading observatory for time-domain and multi-messenger astronomy in the 2030's, as well as providing observations of unprecedented quality on a variety of galactic and extragalactic objects. After briefly introducing the history and a summary of the scientific objectives of the eXTP mission, this paper presents a comprehensive overview of: 1) the cutting-edge technology, technical specifications, and anticipated performance of the mission's scientific instruments; 2) the full mission profile, encompassing spacecraft design, operational capabilities, and ground segment infrastructure.

astro-ph.HE↗

arXiv2025

Crystal Eye: all sky MeV monitor with high precision real-time localization

Crystal Eye is a space-based all-sky monitor optimized for the autonomous detection and localization of transients in the 10 keV to 30 MeV energy range, a region where extensive observations and monitoring of various astrophysical phenomena are required. By focusing on the operating environment and its impact on the observation process, we optimized the detector design and assessed its scientific potential. We explored the use of novel techniques to achieve the science goals of the experiment. We assumed the orbit of a potential future mission at approximately 550 km altitude near the equatorial region with a 20° inclination. In such an orbit, the main background contributions for this kind of detector are from different particles and radiation of cosmic origin and secondaries produced by their interaction in the Earth's atmospheric and geomagnetic environment. We studied the response of the detector in this background environment, using the Geant4 Monte Carlo simulation toolkit. We also calculated other detector performance parameters to estimate its scientific capabilities. The detector effective area and efficiency are calculated for low energy gamma-ray sources and used to estimate its sensitivity to short-duration transient sources. The calculation shows a better effective area and sensitivity by several factors compared to existing instruments of similar type. A method is also developed and discussed to estimate the online transient-localization performance of the detector, suggesting a better localization precision by about an order of magnitude than those typically reported by existing gamma-ray monitors. We present here the simulation study and results of an innovative detector design concept that can make a significant contribution in the multi-messenger era. Moreover, this study can be useful as a technical reference for similar future experiments.

astro-ph.IM↗

arXiv2025

Energy Reconstruction of Non-fiducial Electron-Positron Events in the DAMPE Experiment Using Convolutional Neural Networks

The Dark Matter Particle Explorer (DAMPE) is a space-based Cosmic-Ray (CR) observatory with the aim, among others, to study Cosmic-Ray Electrons (CREs) up to 10 TeV. Due to the low CRE rate at multi-TeV energies, we aim to increasing the acceptance by selecting events outside the fiducial volume. The complex topology of non-fiducial events requires the development of a novel energy reconstruction method. We propose the usage of Convolutional Neural Networks for a regression task to recover an accurate estimation of the initial energy.

astro-ph.IM↗

arXiv2023

GEANT4 simulation and spectrum restoration of a pixelated X-ray detector

We perform a detailed simulation of a pixelated CdTe detector using the GEANT4 toolkit completed with a custom code emulating the detector's electronic response. We demonstrate that a measured tungsten X-ray spectrum can be majorly restored back to the original incident spectrum using the developed model, without requiring the dedicated hardware charge sharing correction.

physics.ins-det↗

arXiv2022

Search for gamma-ray spectral lines with the DArk Matter Particle Explorer

The DArk Matter Particle Explorer (DAMPE) is well suitable for searching for monochromatic and sharp $γ$-ray structures in the GeV$-$TeV range thanks to its unprecedented high energy resolution. In this work, we search for $γ$-ray line structures using five years of DAMPE data. To improve the sensitivity, we develop two types of dedicated data sets (including the BgoOnly data which is the first time to be used in the data analysis for the calorimeter-based gamma-ray observatories) and adopt the signal-to-noise ratio optimized regions of interest (ROIs) for different DM density profiles. No line signals or candidates are found between 10 and 300 GeV in the Galaxy. The constraints on the velocity-averaged cross section for $χχ\to γγ$ and the decay lifetime for $χ\to γν$, both at 95% confidence level, have been calculated and the systematic uncertainties have been taken into account. Comparing to the previous Fermi-LAT results, though DAMPE has an acceptance smaller by a factor of $\sim 10$, similar constraints on the DM parameters are achieved and below 100 GeV the lower limits on the decay lifetime are even stronger by a factor of a few. Our results demonstrate the potential of high-energy-resolution observations on dark matter detection.

astro-ph.HE↗

arXiv2022

A deep learning method for the trajectory reconstruction of cosmic rays with the DAMPE mission

A deep learning method for the particle trajectory reconstruction with the DAMPE experiment is presented. The developed algorithms constitute the first fully machine-learned track reconstruction pipeline for space astroparticle missions. Significant performance improvements over the standard hand-engineered algorithms are demonstrated. Thanks to the better accuracy, the developed algorithms facilitate the identification of the particle absolute charge with the tracker in the entire energy range, opening a door to the measurements of cosmic-ray proton and helium spectra at extreme energies, towards the PeV scale, hardly achievable with the standard track reconstruction methods. In addition, the developed approach demonstrates an unprecedented accuracy in the particle direction reconstruction with the calorimeter at high deposited energies, above several hundred GeV for hadronic showers and above a few tens of GeV for electromagnetic showers.

astro-ph.IM↗

arXiv2022

Machine learning-based method of calorimeter saturation correction for helium flux analysis with DAMPE experiment

DAMPE is a space-borne experiment for the measurement of the cosmic-ray fluxes at energies up to around 100 TeV per nucleon. At energies above several tens of TeV, the electronics of DAMPE calorimeter would saturate, leaving certain bars with no energy recorded. In the present work we discuss the application of machine learning techniques for the treatment of DAMPE data, to compensate the calorimeter energy lost by saturation.

astro-ph.HE↗

arXiv2021

Observations of Forbush Decreases of cosmic ray electrons and positrons with the Dark Matter Particle Explorer

The Forbush Decrease (FD) represents the rapid decrease of the intensities of charged particles accompanied with the coronal mass ejections (CMEs) or high-speed streams from coronal holes. It has been mainly explored with ground-based neutron monitors network which indirectly measure the integrated intensities of all species of cosmic rays by counting secondary neutrons produced from interaction between atmosphere atoms and cosmic rays. The space-based experiments can resolve the species of particles but the energy ranges are limited by the relative small acceptances except for the most abundant particles like protons and helium. Therefore, the FD of cosmic ray electrons and positrons have just been investigated by the PAMELA experiment in the low energy range ($<5$ GeV) with limited statistics. In this paper, we study the FD event occurred in September, 2017, with the electron and positron data recorded by the Dark Matter Particle Explorer. The evolution of the FDs from 2 GeV to 20 GeV with a time resolution of 6 hours are given. We observe two solar energetic particle events in the time profile of the intensity of cosmic rays, the earlier and weak one has not been shown in the neutron monitor data. Furthermore, both the amplitude and recovery time of fluxes of electrons and positrons show clear energy-dependence, which is important in probing the disturbances of the interplanetary environment by the coronal mass ejections.

astro-ph.HE↗

arXiv2021

A neural network classifier for electron identification on the DAMPE experiment

The Dark Matter Particle Explorer (DAMPE) is a space-borne particle detector and cosmic ray observatory in operation since 2015, designed to probe electrons and gamma rays from a few GeV to 10 TeV energy, as well as cosmic protons and nuclei up to 100 TeV. Among the main scientific objectives is the precise measurement of the cosmic electron+positron flux, which due to the very large proton background in orbit requires a powerful particle identification method. In the past decade, the field of machine learning has provided us the needed tools. This paper presents a neural network based approach to cosmic electron identification and proton rejection and showcases its performances based on simulated Monte Carlo data. The neural network reaches significantly lower background than the classical, cut-based method for the same detection efficiency, especially at highest energies. A good matching between simulations and real data completes the picture.

astro-ph.IM↗

arXiv2020

Comparison of proton shower developments in the BGO calorimeter of the Dark Matter Particle Explorer between GEANT4 and FLUKA simulations

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne detector for high-energy cosmic rays and $γ$-rays. To fully understand the detector performance and obtain reliable physical results, extensive simulations of the detector are necessary. The simulations are particularly important for the data analysis of cosmic ray nuclei, which relies closely on the hadronic and nuclear interactions of particles in the detector material. Widely adopted simulation softwares include the GEANT4 and FLUKA, both of which have been implemented for the DAMPE simulation tool. Here we describe the simulation tool of DAMPE and compare the results of proton shower properties in the calorimeter from the two simulation softwares. Such a comparison gives an estimate of the most significant uncertainties of our proton spectral analysis.

physics.ins-det↗

arXiv2017

Offline software for the DAMPE experiment

A software system has been developed for the DArk Matter Particle Explorer (DAMPE) mission, a satellite-based experiment. The DAMPE software is mainly written in C++ and steered using Python script. This article presents an overview of the DAMPE offline software, including the major architecture design and specific implementation for simulation, calibration and reconstruction. The whole system has been successfully applied to DAMPE data analysis, based on which some results from simulation and beam test experiments are obtained and presented.

astro-ph.IM↗

arXiv2017

Charge reconstruction study of the DAMPE Silicon-Tungsten Tracker with ion beams

The DArk Matter Particle Explorer (DAMPE) is one of the four satellites within Strategic Pioneer Research Program in Space Science of the Chinese Academy of Science (CAS). DAMPE can detect electrons, photons in a wide energy range (5 GeV to 10 TeV) and ions up to iron (100GeV to 100 TeV). Silicon-Tungsten Tracker (STK) is one of the four subdetectors in DAMPE, providing photon-electron conversion, track reconstruction and charge identification for ions. Ion beam test was carried out in CERN with 60GeV/u Lead primary beams. Charge reconstruction and charge resolution of STK detectors were investigated.

physics.ins-det↗

arXiv2011

On the role of longitudinal momenta in high energy hadron-hadron scattering

We demonstrate a new method for the calculation of inelastic scattering cross-section, which in contrary to the Regge-based methods takes into account the energy momentum conservation law. By virtue of this method it was shown that the main contribution to integral expressing inelastic scattering cross-sections comes not from the multi-Regge domain. In particular this leads to the fact that accounting of longitudinal momenta contribution to virtualities is sufficient and results in the new mechanism of cross-section growth. The necessity of taking into account the large number of interference contributions is shown and the approximate method for this purpose is developed. By considering the interference contributions from a single fitting constant achieved a qualitative agreement of the total and inelastic cross sections with experimental data.

hep-ph↗