Cosmic Ray Background Research Articles

A comparison of deep learning models for proton background rejection with the AMS electromagnetic calorimeter

Abstract The alpha magnetic spectrometer (AMS) is a high-precision particle detector onboard the International Space Station containing six different subdetectors. The transition radiation detector and electromagnetic calorimeter (ECAL) are used to separate electrons/positrons from the abundant cosmic-ray proton background. The positron flux measured in space by AMS falls with a power law which unexpectedly softens above 25 GeV and then hardens above 280 GeV. Several theoretical models try to explain these phenomena, and a more accurate measurement of positrons at higher energies is needed to help test them. The currently used methods to reject the proton background at high energies involve extrapolating shower features from the ECAL to use as inputs for boosted decision tree and likelihood classifiers. We present a new approach for particle identification with the AMS ECAL using deep learning (DL). By taking the energy deposition within all the ECAL cells as an input and treating them as pixels in an image-like format, we train an MLP, a CNN, and multiple ResNets and convolutional vision transformers (CvTs) as shower classifiers. Proton rejection performance is evaluated using Monte Carlo (MC) events and ISS data separately. For MC, using events with a reconstructed energy between 0.2–2 TeV, at 90% electron accuracy, the proton rejection power of our CvT model is more than five times that of the other DL models. Similarly, for ISS data with a reconstructed energy between 50–70 GeV, the proton rejection power of our CvT model is more than 2.5 times that of the other DL models.

Prospects for joint reconstruction of imaging air Cherenkov telescope array and extensive air shower array

In this paper, we proposed a joint reconstruction of γ-ray events using both extensive air array (EAS) and Imaging air Cherenkov Telescope array (IACT). We considered eight Cherenkov telescopes to be built on the LHAASO (Large High Altitude Air Shower Observatory) site and investigate the improvement in differential sensitivity when combining the information from both IACT and Moun detectors of LHAASO-KM2A. We found that due to the higher cosmic ray background rejection power and higher gamma ray retention ratio provided by muon detectors of LHAASO, such a joint reconstruction can significantly improve the sensitivity of IACTs, especially for extended sources and long exposure time. The sensitivity of the eight-telescopes array can be improved by 25%−60% in different energy ranges using joint reconstructions with muon detectors.

Zenith angle dependence on cosmic-ray background in HPGe gamma spectrometers by using GEANT4 simulation

In this study, we investigate the impact of zenith angle variations on cosmic-ray induced background in High-Purity Germanium (HPGe) gamma spectrometers using a coincidence technique based on plastic scintillator-Germanium detectors. We utilize an HPGe detector (Model GC2018 Mirion Ge Detector) enclosed within a low-activity cylindrical lead shield (Model 747E Mirion Lead Shield). For cosmic ray detection, a coincidence detection system with plastic scintillator detectors was positioned on top of the lead shielding. The zenith angle at the Germanium detector is computed using the dimensions of the square plastic scintillator and its distance from the Germanium detector center. We carried out measurements of cosmic-ray induced background in an HPGe gamma spectrometer with a square plastic configuration (80cm x 80cm), equivalent to a 45° zenith angle. The experimental measurements were compared with GEANT4 simulation data. The results demonstrate a good agreement between the measured energy spectrum and the simulated data across the energy range of 0.05 to 47 MeV. Further investigations into the effects of varying zenith angles provide valuable insights for optimizing HPGe spectrometer setups with minimized background interference.

The Influence of the Sun and Moon on the Observation of Very High Energy Gamma-ray Sources Using EAS Arrays

With great advance of ground-based extensive air shower arrays, such as LHAASO and HAWC, many very high energy (VHE) gamma-ray sources have been discovered and are being monitored regardless of the day and the night. Hence, the Sun and Moon would have some impacts on the observation of gamma-ray sources, which have not been taken into account in previous analysis. In this paper, the influence of the Sun and Moon on the observation of very high energy gamma-ray sources when they are near the line of sight of the Sun or Moon is estimated. The tracks of all the known VHE sources are scanned and several VHE sources are found to be very close to the line of sight of the Sun or Moon during some period. The absorption of very high energy gamma rays by sunlight is estimated with detailed method and some useful conclusions are achieved. The main influence is the block of the Sun and Moon on gamma rays and the shadow on the cosmic ray background. The influence is investigated considering the detector angular resolution and some strategies on data analysis are proposed to avoid the underestimation of the gamma-ray emission.

Enhanced material identification via momentum-integrated muon scattering tomography

Background Cosmic ray muons, originating from interactions in the upper atmosphere, possess high energy and unique penetrative capabilities suitable for non-traditional radiographic inspection. This study explores their application in various fields such as nuclear fuel cask monitoring, nuclear reactor imaging, and archaeology, leveraging the principle of multiple Coulomb scattering for imaging dense materials. While muon scattering tomography has shown promise, accurately measuring muon momentum remains challenging. Methods This research introduces the Momentum Integrated Point-of-Closest Approach (mPoCA) algorithm, integrating muon momentum data into the traditional Point-of-Closest Approach (PoCA) framework. Utilizing the Cherenkov muon spectrometer, renowned for precise muon momentum estimation, the mPoCA algorithm offers a novel imaging approach. Results Simulations conducted with GEANT4 evaluate the mPoCA algorithm’s performance against the standard PoCA method, demonstrating superior image resolution and enhanced material identification capabilities, particularly in distinguishing materials like uranium and lead. Conclusions These findings underscore the potential of the mPoCA algorithm for advancing muon scattering tomography applications.

Neural networks for separation of cosmic gamma rays and hadronic cosmic rays in air shower observation with a large area surface detector array

The Tibet ASγ experiment has been observing cosmic gamma rays and cosmic rays in the energy range from teraelectron volts to several tens of petaelectron volts with a surface detector array since 1990. The derivation of cosmic gamma-ray flux is made by finding the excess distribution of the arrival direction of air showers above background cosmic rays. In 2014, the underground water Cherenkov muon detector (MD) was added to separate cosmic gamma rays from the background on the basis of the muon-less feature of the air showers of gamma-ray origin; hybrid observations using these two detectors were started at this time. In the present study, we developed methods to separate gamma-ray-induced air showers and hadronic cosmic-ray-induced ones using the measured particle number density distribution to improve the sensitivity of cosmic gamma-ray measurements using the Tibet air shower array data alone before the installation of the MD. We tested two approaches based on neural networks. The first method used feature values representing the lateral spread of the secondary particles, and the second method used the shower image data. To compare the separation performance of each method, we analyzed Monte Carlo air shower events in the vertically incident direction with mono-initial-energy gamma rays and protons. When discriminated by a single feature, the feature with the highest separation performance has an area under the curve (AUC) value of 0.701 for a gamma-ray energy of 10 TeV and 0.808 for 100 TeV. A separation method with a multilayer perceptron (MLP) based on multiple features has AUC values of 0.761 for a gamma-ray energy of 10 TeV and 0.854 for 100 TeV, which represents an improvement of approximately 5% in the AUC value compared with the single-feature case. We also found that the feature values that effectively contribute to the separation vary depending on the energy. A separation method with a convolutional neural network (CNN) using the shower image data has AUC values of 0.781 for a gamma-ray energy of 10 TeV and 0.901 for 100 TeV, which are approximately 5% higher than those of the MLP method. We applied the CNN separation method to Monte Carlo gamma-ray and cosmic-ray events from the Crab Nebula in the energy range 10–100 TeV. The AUC values range from 0.753 to 0.879, and the significance of the observed gamma-ray excess is improved by 1.3 to 1.8 times compared with the case without the separation procedure.

Stellar wind bubbles of OB stars as Galactic cosmic-ray re-accelerators

Abstract Cosmic rays are highly energetic messengers propagating in magnetized plasma, which are, possibly but not exclusively, accelerated at astrophysical shocks. Amongst the variety of astrophysical objects presenting shocks, the huge circumstellar stellar wind bubbles forming around very massive stars, are potential non-thermal emitters. We present the 1D magneto-hydrodynamical simulation of the evolving magnetized surroundings of a single, OB-type main-sequence $60\, \rm M_{\odot }$ star, which is post-processed to calculate the re-acceleration of pre-existing non-thermal particles of the Galactic cosmic ray background. It is found that the forward shock of such circumstellar bubble can, during the early phase ($1\, \rm Myr$) of its expansion, act as a substantial re-accelerator of pre-existing interstellar cosmic rays. This results in an increasing excess emission flux by a factor of 5, the hadronic component producing γ-rays by π0 decay being more important than those by synchrotron and inverse Compton radiation mechanisms. We propose that this effect is at work in the circumstellar environments of massive stars in general and we conjecture that other nebulae such as the stellar wind bow shocks of runaway massive stars also act as Galactic cosmic-ray re-accelerators. Particularly, this study supports the interpretation of the enhanced hadronic emission flux measured from the surroundings of κ Ori as originating from the acceleration of pre-existing particles at the forward shock of its wind bubble.

Sub-GeV dark matter search at ILC beam dumps

Light dark matter particles may be produced in electron and positron beam dumps of the International Linear Collider (ILC). We propose an experimental setup to search for such events, the Beam-Dump eXperiment at the ILC (ILC-BDX). The setup consists of a muon shield placed behind the beam dump, followed by a multi-layer tracker and an electromagnetic calorimeter. The calorimeter can detect electron recoils due to elastic scattering of dark matter particles produced in the dump, while the tracker is sensitive to decays of excited dark-sector states into the dark matter particle. We study the production, decay and scattering of sub-GeV dark matter particles in this setup in several models with a dark photon mediator. Taking into account beam-related backgrounds due to neutrinos produced in the beam dump as well as the cosmic-ray background, we evaluate the sensitivity reach of the ILC-BDX experiment. We find that the ILC-BDX will be able to probe interesting regions of the model parameter space and, in many cases, reach well below the relic target.

Callio lab: an underground and above ground,laboratory—overview and prospects for high energy and applied physics

This overview provides a comprehensive insight into Callio Lab, a versatile multidisciplinary research platform, by describing the events and actions that have led to the development of the project-based, pay-by-service approach to organizing and economically running the research activities, a mandatory approach for a platform operating without governmental funding. The research platform has a maximum depth of 1.4 km underground, equivalent to approximately 4,100 m of water equivalent (m.w.e.). The flat-overburden mine configuration of Callio Lab minimizes cosmic-ray background interference, making it an ideal setting for low-background experiments, particularly in neutrino and dark matter research. The main-level galleries, with dimensions up to 12 m wide, 30–40 m long, and 8 m tall, provide ample space for research activities, with the potential for even more extensive galleries based on Laguna design studies. Callio Lab has a history with several small and medium-scale cosmic ray and low-background experiments. This overview highlights the site’s inherent characteristics, revealing promising opportunities for high-energy and applied physics research and applications across various scientific domains.

Fast muon simulation in the JUNO experiment with neural networks

Fast muon simulation in the JUNO experiment with neural networks

MicroBooNE Public Data Sets: A Collaborative Tool for LArTPC Software Development

Among liquid argon time projection chamber (LArTPC) experiments MicroBooNE is the one that continually took physics data for the longest time (2015-2021), and represents the state of the art for reconstruction and analysis with this detector. Recently published analyses include oscillation physics results, searches for anomalies and other BSM signatures, and cross section measurements. LArTPC detectors are being used in current experiments such as ICARUS and SBND, and being planned for future experiments such as DUNE. MicroBooNE has recently released to the public two of its data sets, with the goal of enabling collaborative software developments with other LArTPC experiments and with AI or computing experts. These data sets simulate neutrino interactions on top of off-beam data, which include cosmic ray background and noise. The data sets are released in two formats: the native art/ROOT format used internally by the collaboration and familiar to other LArTPC experts, and the HDF5 format which contains reduced and simplified content and is suitable for usage by the broader community. This contribution presents the open data sets, discusses their motivation, the technical implementation, and the extensive documentation – all inspired by FAIR principles. Finally, opportunities for collaborations are discussed.

Cosmic Ray Background Detection and Removal from CCD Images using Neural Networks

Cosmic Ray Background Detection and Removal from CCD Images using Neural Networks

Method to measure muon content of extensive air showers with LHAASO KM2A-WCDA synergy

The measurement of shower muons on an event-by-event basis offers a potent tool for conducting ground-based experiments on gamma rays and cosmic rays due to its sensitivity to primary mass and interaction models. In recent years, underground water Cherenkov detectors as large-area muon counters provide the most powerful way of rejecting cosmic ray background when searching for TeV–PeV gamma rays and cosmic ray electrons, an unprecedented rejection power of 104–105 is achieved. Unburied water Cherenkov detectors are widely used in ground-based gamma astronomy experiments, e.g, Milagro, HAWC, LHAASO-WCDA, etc. However, due to the presence of electromagnetic components, their deployment as event-by-event muon counters has encountered considerable challenges. All the experiments mentioned above reconstruct lateral-distribution-function related parameters to tell a gamma from hadrons. In this work, we first developed a method to utilize the WCDA, to specify muon content in each shower with LHAASO KM2A-WCDA synergy and help LHAASO to gain approximately a 37,650-meter-square effective area as a muon counter.

The deep underground Bellotti Ion Beam Facility—status and perspectives

For more than three decades, accelerators are in use in the underground laboratories of the Laboratori Nazionali del Gran Sasso (LNGS), located in central Italy. The LUNA Collaboration has exploited the potential of the site’s low cosmic ray background to achieve important and often groundbreaking results in the field of nuclear astrophysics. This long success story stimulated the installation of accelerators in deep underground laboratories also in other countries, including the USA and China. Recently, LNGS took a major step forward with the activation of the Bellotti Ion Beam Facility, which will provide ion beams to the scientific community for research not only in nuclear astrophysics, but in all fields that can benefit from the low cosmic ray background conditions of the underground site.

The ALPACA experiment: The project of the first sub-PeV gamma-ray observation in the southern sky

The ALPACA experiment is a project aiming to observe sub-PeV gamma rays for the first time in the southern hemisphere. The main goal of ALPACA is to identify PeVatrons, the accelerators of Galactic PeV cosmic rays, by observing sub-PeV pion-decay gamma rays generated in interactions between PeV cosmic rays and the interstellar medium. This new air shower experiment is located at an altitude of 4,740 m above sea level in the middle of Mt. Chacaltaya in Bolivia. The air shower array consists of 401 scintillation counters covering an 83,000 m^22 surface area. In addition, a water-Cherenkov-type muon detector array with an area of 3,700 m^22 is installed to discriminate gamma rays from background cosmic rays. The prototype array ALPAQUITA will start data taking in 2022 and will extend to ALPACA in 2024. We report on a general introduction to ALPACA, the progress of the project, and the sensitivity to sub-PeV gamma rays.

Dimensionality reduction and sensitivity improvement for TACTIC Cherenkov data using t-SNE machine learning algorithm

Very high energy (VHE) gamma and cosmic rays scatter with the atmospheric nuclei and create an extensive air shower (EAS) of electrons and positrons, which travel with relativistic speeds and induce the medium to emit a flash of Cherenkov light, which is detected by the camera. This indirect method to detect EAS is known as the imaging atmospheric Cherenkov technique (IACT). However, the main challenge in IACT is to segregate the EAS events induced by gamma primaries from huge cosmic ray background events. Since cosmic background events are ∼103 times more abundant than gamma rays, the gamma-cosmic ray discrimination plays a crucial role in evaluating the sensitivity of an IACT telescope, like the TACTIC. There are several methods to reduce the dimensionality of Cherenkov event images, such as principal component analysis (PCA), gamma domain dynamic supercuts and machine learning-based cuts which classify the gamma or hadronic events.In this study, we report applying a novel dimensionality reduction technique t-SNE (t-distributed stochastic neighbour embedding), on the image parameters of EASs. This technique enables us to visualize complex multi-dimensional features of EAS images into a compressed two-dimensional projection while preserving local neighbourhood features of the higher dimension. The efficacy of dimensionality reduction, which in this case is measured in terms of the statistical significance of detecting gamma-ray signal over cosmic ray background, is compared with the significance obtained using the conventional dynamic supercuts method. The application of the t-SNE technique to estimate signals from TACTIC observation data is also presented.

Towards a direct measurement of the E cm = 65 keV resonance strength in 17O(p, γ)18F at LUNA

The 17O(p, γ)18F reaction plays a crucial role in several stellar scenarios where the hydrogen burning phases takes place. In particular, in the temperature energy range of interest for AGB nucleosynthesis (20 MK< T <80 MK) the main contribution to the astrophysical reaction rate comes from the elusive 65 keV resonance. Indeed, this resonance strength is at the moment determined only through indirect measurements, with a reported value of ωγ = (1.6 ± 0.3) × 10−11 eV. With typical experimental quantities for beam current, isotopic enrichment and detection efficiency, this strength yields an expected count rate of less than one count per Coulomb, making the direct measurement of this resonance extremely challenging. The Laboratory for Underground Nuclear Astrophysics (LUNA) 400kV accelerator installed in Laboratori Nazionali del Gran Sasso (Italy) provides a unique possibility to directly measure this low resonance thanks to the reduction of cosmic ray background by six orders of magnitude with respect surface laboratories and thanks to an intense, narrow proton beam. To improve the experimental sensitivity, the environmental background was further reduced designing a lead and borated (5%) polyethylene shielding and the absorption of γ − rays emitted by the reaction was minimised by the installation of target chamber and holder made of aluminum.With about 400 Coulomb accumulated on Ta2O5 targets, with nominal 17O enrichment of 90%, the LUNA collaboration has performed the first direct measurement of the 65 keV resonance strength.

γ-Ray and ultra-high energy neutrino background suppression due to solar radiation

The Sun emits copious amounts of photons and neutrinos in an approximately spatially isotropic distribution. Diffuse γ-rays and ultra-high energy (UHE) neutrinos from extragalactic sources may subsequently interact and annihilate with the emitted solar photons and neutrinos respectively. This will in turn induce an anisotropy in the cosmic ray (CR) background due to attenuation of the γ-ray and UHE neutrino flux by the solar radiation. Measuring this reduction, therefore, presents a simple and powerful astrophysical probe of electroweak interactions. In this letter we compute such anisotropies, which at the Earth (Sun) can be at least ≃5×10−3(1)% and ≃1×10−16(2×10−14)% for TeV scale γ-rays and PeV scale UHE neutrinos respectively. We briefly discuss observational prospects for experiments such as the Fermi Gamma-Ray Space Telescope Large Area Telescope (Fermi LAT), High-Altitude Water Cherenkov (HAWC) detector, The Large High Altitude Air Shower Observatory (LHAASO), Cherenkov Telescope Array (CTA) and IceCube. The potential for measuring γ-ray attenuation at orbital locations of other active satellites such as the Parker Solar Probe and James Webb Space Telescope (JWST) is also explored.

The Upcoming GAMMA-400 Experiment

The upcoming GAMMA-400 experiment will be implemented aboard the Russian astrophysical space observatory, which will be operating in a highly elliptical orbit over a period of 7 years to provide new data on gamma-ray emissions and cosmic-ray electron + positron fluxes, mainly from the galactic plane, the Galactic Center, and the Sun. The main observation mode will be a continuous point-source mode, with a duration of up to ~100 days. The GAMMA-400 gamma-ray telescope will study high-energy gamma-ray emissions of up to several TeV and cosmic-ray electrons + positrons up to 20 TeV. The GAMMA-400 telescope will have a high angular resolution, high energy and time resolutions, and a very good separation efficiency for separating gamma rays from the cosmic-ray background and the electrons + positrons from protons. A distinctive feature of the GAMMA-400 gamma-ray telescope is its wonderful angular resolution for energies of &gt;30 GeV (0.01° for Eγ = 100 GeV), which exceeds the resolutions of space-based and ground-based gamma-ray telescopes by a factor of 5–10. GAMMA-400 studies can reveal gamma-ray emissions from dark matter particles’ annihilation or decay, identify many unassociated, discrete sources, explore the extended sources’ structures, and improve the cosmic-ray electron + positron spectra data for energies of &gt;30 GeV.

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1pm 0.6% and 84.1pm 0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.