SEARCH · Search NASA

Results for “cosmic ray sources”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Constraints on neutrino emission from nearby galaxies using the 2MASS redshift survey and IceCube

The distribution of galaxies within the local universe is characterized by anisotropic features. Observatories searching for the production sites of astrophysical neutrinos can take advantage of these features to establish directional correlations between a neutrino dataset and overdensities in the galaxy distribution in the sky. The results of two correlation searches between a seven-year time-integrated neutrino dataset from the IceCube Neutrino Observatory, and the 2MASS Redshift Survey (2MRS) catalog are presented here. The first analysis searches for neutrinos produced via interactions between diffuse intergalactic Ultra-High Energy Cosmic Rays (UHECRs) and the matter contained within galaxies. The second analysis searches for low-luminosity sources within the local universe, which would produce subthreshold multiplets in the IceCube dataset that directionally correlate with galaxy distribution. No significant correlations were observed in either analyses. Herein, constraints are presented on the flux of neutrinos originating within the local universe through diffuse intergalactic UHECR interactions, as well as on the density of standard candle sources of neutrinos at low luminosities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Dark matter and galaxy cross-correlations with the Cherenkov Telescope Array Observatory

The Cherenkov Telescope Array Observatory (CTAO) will be a ground-based Cherenkov telescope performing wide-sky surveys, ideal for anisotropy studies such as cross-correlations with tracers of the cosmic large-scale structure. Cross-correlations can shed light on high-energy γ -ray sources and potentially reveal exotic signals from particle dark matter. In this work, we investigate CTAO sensitivity to cross-correlation signals between γ -ray emission and galaxy distributions. We find that by using dense, low-redshift catalogs like 2 MASS, and for integration times around 50 hours, this technique achieves sensitivities to both annihilating and decaying dark matter signals that are competitive with those from dwarf galaxy and cluster analyses.

Pinetti, Elena [CCA, New York; Perimeter Inst. The↗

DOE OSTI2024

Measurement of the background in the CMS muon detector in ${p}{p}$-collisions at $\sqrt{s} = 13$ TeV

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ($\mathcal{L}$) of 1 x 10 34 cm –2 s –1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of $\mathcal{L}$ = 5 x 10 34 cm –2 s –1 and increasing ultimately to $\mathcal{L}$ = 7.5 x 10 34 cm –2 s –1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

Tytgat, M. (ORCID:0000000239902074)↗

DOE OSTI2024

Cosmic Background Rejection of the ICARUS experiment at Fermilab

The Short Baseline Neutrino program at Fermilab aims to explore significant regions of parameter space, applicable to sterile neutrinos at the eV mass scale, as suggested by existing experimental anomalies. To this purpose it exploits Liquid Argon Time Projection Chamber detectors located along the Booster Neutrino Beamline to measure both νe appearance and νµ disappearance: the Short Baseline Neutrino Detector and the ICARUS-T600 detector at 110 and 600 m from the neutrino source, respectively. The ICARUS T-600 Far Detector, located at shallow depth, is surrounded by a Cosmic Ray Tagger system to mitigate the cosmic ray background. On average ~ 11 muon tracks are expected to cross the detector during the ~ 1 ms drift time. The cosmic ray tagger is composed of plastic scintillator bars, ensuring near 4π coverage of the detector aiming at tagging cosmic muons and thus reject 𝛾s produced by muon interactions in the surrounding materials that can generate an electromagnetic showers mimicking a νe signal. The system allows one to disentangle cosmic rays from particles originated in a neutrino interaction inside the detector by measuring their position and crossing time. A synchronization of the cosmic ray tagger with the ICARUS photon detection system with a nanosecond accuracy allows one to reject cosmic particles recorded during the beam spill and thus select an enriched sample of neutrino triggered events ahead of the event reconstruction. An overview of the cosmic ray tagger system as well as its role in the neutrino events identification and cosmic background rejection will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

A Magnetized Strongly Turbulent Corona as the Source of Neutrinos from NGC 1068

Abstract The cores of active galactic nuclei are potential accelerators of 10–100 TeV cosmic rays, in turn producing high-energy neutrinos. This picture was confirmed by the compelling evidence of a TeV neutrino signal from the nearby active galaxy NGC 1068, leaving open the question of what is the site and mechanism of cosmic-ray acceleration. One candidate is the magnetized turbulence surrounding the central supermassive black hole. Recent particle-in-cell simulations of magnetized turbulence indicate that stochastic cosmic-ray acceleration is nonresonant, in contrast to the assumptions of previous studies. We show that this has important consequences on a self-consistent theory of neutrino production in the corona, leading to a more rapid cosmic-ray acceleration than previously considered. The turbulent magnetic-field fluctuations needed to explain the neutrino signal are consistent with a magnetically powered corona. We find that strong turbulence, with turbulent magnetic energy density higher than 1% of the rest-mass energy density, naturally explains the normalization of the IceCube neutrino flux, in addition to the neutrino spectral shape. Only a fraction of the protons in the corona, which can be directly inferred from the neutrino signal, are accelerated to high energies. Thus, in this framework, the neutrino signal from NGC 1068 provides a testbed for particle acceleration in magnetized turbulence.

Fiorillo, Damiano F. G. (ORCID:0000000349279850)↗

DOE OSTI2025

Search for Extremely-High-Energy Neutrinos and First Constraints on the Ultrahigh-Energy Cosmic-Ray Proton Fraction with IceCube

Here, we present a search for the diffuse extremely-high-energy neutrino flux using 12.6 years of IceCube data. The nonobservation of neutrinos with energies well above 10 PeV constrains the all-flavor neutrino flux at $10^{18}$ eV to a level of $E^{2}Φ_{ν_{e}+ν_{μ}+ν_{τ}}≃10^{-8}$ GeV cm$^{-2}$ s$^{-1} sr$^{-1}$, the most stringent limit to date. Using these data, we constrain the proton fraction of ultrahigh-energy cosmic rays (UHECRs) above ≃30 EeV to be ≲70% (at 90% CL) if the cosmological evolution of the sources is comparable to or stronger than the star formation rate. This is the first result to disfavor the "proton-only" hypothesis for UHECR in this evolution regime using neutrino data. This result complements direct air-shower measurements by being insensitive to uncertainties associated with hadronic interaction models. We also evaluate the tension between IceCube's nonobservation and the ∼200 PeV KM3NeT neutrino candidate (KM3-230213A), finding it to be ∼2.9σ based on a joint-livetime fit between neutrino datasets.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗

DOE OSTI2024

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry↗

DOE OSTI2022

Sensitivity of the GAPS experiment to low-energy cosmic-ray antiprotons

The General Antiparticle Spectrometer (GAPS) is an upcoming balloon mission to measure low-energy cosmic-ray antinuclei during at least three ~35-day Antarctic flights. With its large geometric acceptance and novel exotic atom-based particle identification, GAPS will detect ~500 cosmic antiprotons per flight and produce a precision cosmic antiproton spectrum in the kinetic energy range of ~0.07–0.21 GeV/n at the top of the atmosphere. With these high statistics extending to lower energies than any previous experiment, and with complementary sources of experimental uncertainty compared to traditional magnetic spectrometers, the GAPS antiproton measurement will be sensitive to dark matter, primordial black holes, and cosmic ray propagation. The antiproton measurement will also validate the GAPS antinucleus identification technique for the antideuteron and antihelium rare-event searches. Finally, this analysis demonstrates the GAPS sensitivity to cosmic-ray antiprotons using a full instrument simulation and event reconstruction, and including solar and atmospheric effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Calibration of the DUNE Far Detector Using Cosmic-ray Muon Events

The Deep Underground Neutrino Experiment (DUNE) aims to set new limits on parameters associated with neutrino oscillations, neutrino astrophysics, and beyond the Standard Model (SM) searches such as nucleon decay. DUNE will quantify the magnitude of CP violation in the lepton sector, and determine the neutrino mass ordering. These benefit highly from the large target mass and excellent imaging, tracking, and particle identification capabilities of Liquid Argon Time Projection Chambers (LArTPCs). Detector calibration is essential to make precise physics measurements. For instance, accurate energy reconstruction is necessary for measuring many of the aforementioned quantities with the precision required for discovering new physics and fully exploiting the capabilities of the detector. Cosmic muons are a freely available natural source of calorimetric data and can be used for calibrating various detector parameters. This thesis provides an analysis of simulated cosmic-ray muon events generated with the Muon Simulation Underground (MUSUN) generator in the DUNE horizontal drift (HD) far detector (FD). The study focuses on analysing the energy and angular distribution of various classes of muon events, as well as characterising the different particles produced by cosmic muon interactions. The analysis of π0 → 2γ events within the cosmic-ray muon sample is presented in this thesis with a detailed study of reconstructing electromagnetic showers. The π0 mass is reconstructed within the DUNE FD, yielding a value of (136 ± 7) MeV/c2. Additionally, the thesis introduces methods for dE/dx calibration using simulated and reconstructed muon tracks. A calibration constant Ccal = (5.469 ± 0.003) × 10−3 ADC × tick/e is obtained through a model-dependent calibration process, where 1 tick corresponds to 500 ns of sampling time of an ADC. Furthermore, a calibration technique is presented, demonstrating precise translation from dQ/dx to dE/dx. This calibration method is applied to stopping muons, charged pions, and protons in the DUNE FD, addressing the measurement of energy loss in the detector volume. These are important calibrations of the DUNE FD and will contribute to achieving the exciting physics goals of the experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Production and Persistence of Extreme Two-temperature Plasmas in Radiative Relativistic Turbulence

Turbulence is a predominant process for energizing electrons and ions in collisionless astrophysical plasmas, and thus is responsible for shaping their radiative signatures (luminosity, spectra, and variability). To better understand the kinetic properties of a collisionless radiative plasma subject to externally driven turbulence, we investigate particle-in-cell simulations of relativistic plasma turbulence with external inverse Compton cooling acting on the electrons. We find that ions continuously heat up while electrons gradually cool down (due to the net effect of radiation), and hence the ion-to-electron temperature ratio T i /T e grows in time. Furthermore, we show that Ti/Te is limited only by the size and duration of the simulations (reaching ${T}_{i}/{T}_{e}\sim {10}^{3}$), indicating that there are no efficient collisionless mechanisms of electron–ion thermal coupling. This result has implications for models of radiatively inefficient accretion flows, such as observed in the Galactic center and in M87, for which so-called two-temperature plasmas with ${T}_{i}/{T}_{e}\gg 1$ have been invoked to explain their low luminosity. Additionally, we find that electrons acquire a quasi-thermal distribution (dictated by the competition of turbulent particle energization and radiative cooling), while ions undergo efficient nonthermal acceleration (acquiring a harder distribution than in equivalent nonradiative simulations). There is a modest nonthermal population of high-energy electrons that are beamed intermittently in space, time, and direction; these beamed electrons may explain rapid flares in certain high-energy astrophysical systems (e.g., in the Galactic center). These numerical results demonstrate that extreme two-temperature plasmas can be produced and maintained by relativistic radiative turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Fermi-LAT Detection of the Supernova Remnant G312.4-0.4 in the Vicinity of 4FGL J1409.1-6121e

Abstract Gamma-ray emission provides constraints on the nonthermal radiation processes at play in astrophysical particle accelerators. This allows both the nature of accelerated particles and the maximum energy that they can reach to be determined. Notably, it remains an open question to what extent supernova remnants contribute to the sea of Galactic cosmic rays. In the Galactic plane, at around 312° of Galactic longitude, Fermi-LAT observations show an extended source (4FGL J1409.1−6121e) around five powerful pulsars. This source is described by one large disk of 0.°7 radius with a high significance of 45σin the 4FGL-DR3 catalog. Using 14 yr of Fermi-LAT observations, we revisited this region with a detailed spectro-morphological analysis in order to disentangle its underlying structure. Three sources have been distinguished, including the supernova remnant G312.4−0.4 whose gamma-ray emission correlates well with the shell observed at radio energies. The hard spectrum detected by the LAT, extending up to 100 GeV without any sign of a cutoff, is well reproduced by a purely hadronic model.

Astronomy & Astrophysics↗

DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗

DOE OSTI2026

First operation of superconducting quantum bits as particle detectors

Transmon qubits are among the leading technologies for the development of future quantum computers. However these superconducting devices are sensitive to ionizing radiation, which reduces their coherence time and leads to correlated errors. This study represents the first quantitative estimation of cosmic rays and ambient radiation impact on transmon qubits. In the shielded underground facility at the Laboratori Nazionali del Gran Sasso (LNGS), errors induced by the interaction of a radioactive source were reconstructed with an efficiency of about 10%. In contrast, in the unshielded above-ground facility at the Fermi National Accelerator Laboratory (FNAL), cosmic and ambient radiation impacts were detected with an efficiency ranging from 10% to 20% by modifying the acquisition protocol. Lastly, the simultaneous readout of three transmons in coincidence was demonstrated, achieving an event reconstruction efficiency of 90% when the devices were illuminated with an LED.

Bonomo, Camilla [Rome U.; INFN, Rome]↗

DOE OSTI2022

Slow control and data acquisition systems in the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinolessconversion of a muon into an electron in the field of an aluminum nucleus with a sensitivityimprovement by a factor of 10,000 over existing limits. The Mu2e Trigger and Data AcquisitionSystem (TDAQ) usesotsdaqas the online Data Acquisition System (DAQ) solution. Developed atFermilab,otsdaqintegrates both theartdaqDAQ and theartanalysis frameworks for event transfer,filtering, and processing.otsdaqis an online DAQ software suite with a focus on flexibility andscalability and provides a multi-user, web-based, interface accessible through a web browser. Thedata stream from the detector subsystems is read by a software filter algorithm that selects eventswhich are combined with the data flux coming from a Cosmic Ray Veto System. The DetectorControl System (DCS) has been developed using the Experimental Physics and Industrial ControlSystem (EPICS) open source platform for monitoring, controlling, alarming, and archiving. TheDCS System has been integrated intootsdaq. A prototype of the TDAQ and the DCS systems hasbeen built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress ofthe integration of this prototype in the onlineotsdaqsoftware.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Online DAQ and slow control interface for the Mu2e experiment

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Non-destructive evaluation and machine learning methods for inspection of spent nuclear fuel canisters: A state-of-the-art review

Nuclear energy is among the cleanest and most efficient energy sources currently available. The operation of nuclear power plants (NPPs) produces large amounts of high-level radioactive waste known as spent nuclear fuel (SNF). Currently, large amounts of SNF is stored in dry cask storage systems (DCSSs) for extended interim storage until a permanent disposal solution becomes available. During the extended interim storage, the DCSS, particularly the SNF canisters, may degrade and abnormal conditions may occur. Therefore, non-destructive evaluation (NDE) and machine learning (ML) approaches are necessary for inspection of SNF canisters. This paper presents a state-of-the-art review of literature by summarizing recent progress made on the applications of NDE and ML for inspection of SNF canisters. Sixteen NDE methods are examined and compared: visual inspection, ultrasonic guided waves (UGWs), laser-based approaches, acoustic emission (AE), eddy current testing (ECT), non-invasive acoustic sensing, dynamic modal testing, cosmic ray muons tomography, neutron imaging, gamma rays detection, fiber optical sensors, through-wall communications, X-ray computed tomography (CT), vibrothermography, monoenergetic photon sources, and surface acoustic wave (SAW) sensors. The technology readiness level (TRL) for each method is assessed and compared. Recent publications on ML-enhanced visual inspection, AE, non-invasive acoustic sensing, dynamic modal testing, and neutron imaging for SNF canisters are summarized and future research needs are identified. In conclusion, this review article provides a convenient reference on the state-of-the-art applications of NDE and ML methods for inspection of SNF canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Status of the data acquisition, trigger, and slow control systems of the Mu2e experiment at Fermilab

The Mu2e experiment at the Fermilab will search for a coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. In this work, the Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq framework as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates several framework components — an artdaq-based DAQ, an art-based event processing, and an EPICS-based detector control system (DCS), and provides a uniform multi-user interface to its components through a web browser. Data streams from the Mu2e tracker and calorimeter are handled by the artdaq-based DAQ and processed by a one-level software trigger implemented within the art framework. Events accepted by the trigger have their data combined, post-trigger, with the separately read out data from the Mu2e Cosmic Ray Veto system. Foundation of the Mu2e DCS, EPICS – an Experimental Physics and Industrial Control System – is an open-source platform for monitoring, controlling, alarming, and archiving. A prototype of the TDAQ and the DCS systems has been built and tested over the last three years at Fermilab’s Feynman Computing Center, and now the production system installation is underway. This work presents their status and focus on the installation plans and procedures for racks, workstations, network switches, gateway computers, DAQ hardware, slow controls implementation, and testing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗