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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field

he fourth Fermi Large Area Telescope catalog (4FGL) contains 5064 $\ γ$-ray sources detected at high significance, but 26% of them still lack associations at other wavelengths. The SPT-SZ survey, conducted between 2008 and 2011 with the South Pole Telescope (SPT), covers 2500 deg 2 of the southern sky in three millimeter-wavelength (mm) bands and was used to construct a catalog of nearly 5000 emissive sources. In this study, we introduce a new cross-matching scheme to search for multiwavelength counterparts of extragalactic $\ γ$-ray sources using a mm catalog. We apply a Poissonian probability to evaluate the rate of spurious false associations and compare the multiwavelength associations from the radio, mm, near-infrared, and X-ray with 4FGL $\ γ$-ray sources. In the SPT-SZ survey field, 85% of 4FGL sources are associated with mm counterparts. These mm sources include 94% of previously associated 4FGL sources and 56% of previously unassociated 4FGL sources. The latter group contains 40 4FGL sources for which SPT has provided the first identified counterparts. Nearly all of the SPT-associated 4FGL sources can be described as flat-spectrum radio quasars or blazars. We find that the mm band is the most efficient wavelength for detecting $\ γ$-ray blazars when considering both completeness and purity. We also demonstrate that the mm band correlates better to the $\ γ$-ray band than the radio or X-ray bands. With the next generation of CMB experiments, this technique can be extended to greater sensitivities and more sky area to further complete the identifications of the remaining unknown $\ γ$-ray blazars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

X-ray and γ-ray beam interstellar communication and implications for SETI

The possibility of detecting artificial signals transmitted by alien civilizations via collimated X-ray or gamma-ray beams is investigated. The prospect of using such beams for human communication within the solar system and beyond is also discussed. Detector responses were simulated for input signals and analyzed using relative entropy. For simplicity, all signals were assumed to use on-off keying (OOK) modulation. “Real” signals were generated by taking digital files and sequentially feeding their raw binary data to the detector simulator, the resulting normalized information content of the detector signals was plotted and compared to random noise signals. Since jpeg files contain compressed information, these served as a proxy for artificial alien signals. This showed that there is a clear difference in measured information content between natural and artificial signals, even with relatively poor time resolution in the detector causing the signals to be smeared (dead-time/rise-time intervals many times longer than the duration between signal pulses). It was found that so long as the signal lasts for at least several rise-time/dead-time intervals, the distinction between random and artificial signals is obvious. A space-telescope with high time resolution for searching for such signals is briefly described and its basic requirements are outlined.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Conceptual design of DIII-D experiments to diagnose the lifetime of spin polarized fuel

Abstract In magnetic fusion experiments, the cross sections for the D-T and D- 3 He fusion reactions are increased by as much as 50% if the fuel remains spin polarized parallel to the magnetic field. The goal of this study is to assess the feasibility of lifetime measurements of spin polarization, in magnetic fusion relevant conditions, on the DIII-D tokamak using relative changes in charged fusion product (CFP) loss measurements that depend upon the differential fusion cross section d σ /dΩ. Relative measurements that capture changes in the escaping CFP pitch, poloidal, and energy distributions are studied in two realistic TRANSP calculated plasma scenarios: (a) vector-polarized 3 He and D pellets are injected into a hot hydrogen plasma to produce thermonuclear reactions, and (b) a tensor-polarized deuterium pellet is injected into an L-mode hydrogen background plasma that includes unpolarized 3 He neutral beam injection. Ideal CFP signals in both scenarios show substantial pitch sensitivity to polarization for 14.7 MeV proton detection at a poloidal angle of − 56 ∘ (on the outer wall in the ion ∇ B direction), and strong sensitivity to polarization for 3.6 MeV alpha flux detection by an array of poloidal detectors. Energy-resolved measurements of 14.7 MeV protons are also sensitive to the degree of polarization for the − 56 ∘ port in the beam-plasma scenario. A realistic assessment of CFP signals in the thermonuclear scenario show count rates in the range of 2 × 10 4 cps for pitch-resolved proton detection and 2 × 10 5 cps for alpha flux measurements. Reduced chi-squared χ r 2 calculations show polarization lifetime measurements are feasible for either proton or alpha detection of both enhanced or suppressed polarization for the thermonuclear scenario. Measurements of gamma rays produced in the weak D + 3 He → γ + 5 Li branch complement the CFP measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Constraints on the Intergalactic Magnetic Field Using Fermi-LAT and H.E.S.S. Blazar Observations

Magnetic fields in galaxies and galaxy clusters are believed to be the result of the amplification of intergalactic seed fields during the formation of large-scale structures in the universe. However, the origin, strength, and morphology of this intergalactic magnetic field (IGMF) remain unknown. Lower limits on (or indirect detection of) the IGMF can be obtained from observations of high-energy gamma rays from distant blazars. Gamma rays interact with the extragalactic background light to produce electron-positron pairs, which can subsequently initiate electromagnetic cascades. The gamma-ray signature of the cascade depends on the IGMF since it deflects the pairs. Here we report on a new search for this cascade emission using a combined data set from the Fermi Large Area Telescope and the High Energy Stereoscopic System. Using state-of-the-art Monte Carlo predictions for the cascade signal, our results place a lower limit on the IGMF of B > 7.1 × 10 -16 G for a coherence length of 1 Mpc even when blazar duty cycles as short as 10 yr are assumed. This improves on previous lower limits by a factor of 2. For longer duty cycles of 10 4 (10 7 ) yr, IGMF strengths below 1.8 × 10 -14 G (3.9 × 10 -14 G) are excluded, which rules out specific models for IGMF generation in the early universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

GRB 180128A: A second magnetar giant flare candidate from the Sculptor Galaxy

Magnetars are slowly rotating neutron stars that possess the strongest magnetic fields known in the cosmos (10 14 − 10 15 G). They display a range of transient high-energy electromagnetic activity. The brightest and most energetic of these events are the gamma-ray bursts (GRBs) known as magnetar giant flares (MGFs), with isotropic energies E iso ≈ 10 44 − 10 46 erg. Only seven MGF detections have been made to date: three unambiguous events occurred in our Galaxy and the Magellanic Clouds, and the other four MGF candidates are associated with nearby star-forming galaxies. As all seven identified MGFs are bright at Earth, additional weaker events likely remain unidentified in archival data. We conducted a search of the Fermi Gamma-ray Burst Monitor database for candidate extragalactic MGFs and, when possible, collected localization data from the Interplanetary Network (IPN) satellites. Our search yielded one convincing event, GRB 180128A. IPN localizes this burst within NGC 253, commonly known as the Sculptor Galaxy. The event is the second MGF in modern astronomy to be associated with this galaxy and the first time two bursts have been associated with a single galaxy outside our own. Here we detail the archival search criteria that uncovered this event and its spectral and temporal properties, which are consistent with expectations for a MGF. We also discuss the theoretical implications and finer burst structures resolved from various binning methods. Our analysis provides observational evidence of an eighth identified MGF.

Trigg, Aaron C. (ORCID:000900068598728X)↗
DOE OSTI2020

A systematic study of hidden sector dark matter: application to the gamma-ray and antiproton excesses

In hidden sector models, dark matter does not directly couple to the particle content of the Standard Model, strongly suppressing rates at direct detection experiments, while still allowing for large signals from annihilation. In this paper, we conduct an extensive study of hidden sector dark matter, covering a wide range of dark matter spins, mediator spins, interaction diagrams, and annihilation final states, in each case determining whether the annihilations are s-wave (thus enabling efficient annihilation in the universe today). We then go on to consider a variety of portal interactions that allow the hidden sector annihilation products to decay into the Standard Model. We broadly classify constraints from relic density requirements and dwarf spheroidal galaxy observations. In the scenario that the hidden sector was in equilibrium with the Standard Model in the early universe, we place a lower bound on the portal coupling, as well as on the dark matter’s elastic scattering cross section with nuclei. We apply our hidden sector results to the observed Galactic Center gamma-ray excess and the cosmic-ray antiproton excess. We find that both of these excesses can be simultaneously explained by a variety of hidden sector models, without any tension with constraints from observations of dwarf spheroidal galaxies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Monte Carlo simulation of the passage of $\gamma$-rays and $\alpha$-particles in CsI

In this work, theoretical and computational methods for simulating the creation of ionization tracks by fast ions in solids were applied to the passage of a-particles in CsI, an inorganic scintillator commonly used for radiation detection. The methods were implemented in a Monte Carlo program to simulate the interaction of $\alpha$-particles, with incident energies of up to 1 MeV, with CsI. The simulations followed the fate of individual electron-hole pairs and thus allowed for a detailed description of the microscopic structure of ionization tracks created by incident radiation. Simulations were also performed with $\gamma$-rays of the same energy to compare and contrast the ionization tracks obtained with both types of particle. Intrinsic properties such as the mean energy per electron-hole pair, Fano factor, maximum theoretical light yield, and spatial distributions of electron-hole pairs were computed for both $\alpha$-particles and $\gamma$-rays. $\alpha$-particles created cylindrical tracks that were initially aligned with the incident direction and with initial radii of a few nanometers, whereas $\gamma$-rays showed significant scattering, resulting in probability distributions with lower intensities and much greater radial extents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Precision measurement of Compton scattering in silicon with a skipper CCD for dark matter detection

Experiments aiming to directly detect dark matter through particle recoils can achieve energy thresholds of $\mathcal{O}(1\,\mathrm{eV})$. In this regime, ionization signals from small-angle Compton scatters of environmental $\gamma$-rays constitute a significant background. Monte Carlo simulations used to build background models have not been experimentally validated at these low energies. We report a precision measurement of Compton scattering on silicon atomic shell electrons down to 23$\,$eV. A skipper charge-coupled device (CCD) with single-electron resolution, developed for the DAMIC-M experiment, was exposed to a $^{241}$Am $\gamma$-ray source over several months. Features associated with the silicon K, L$_{1}$, and L$_{2,3}$-shells are clearly identified, and scattering on valence electrons is detected for the first time below 100$\,$eV. We find that the relativistic impulse approximation for Compton scattering, which is implemented in Monte Carlo simulations commonly used by direct detection experiments, does not reproduce the measured spectrum below 0.5$\,$keV. The data are in better agreement with $ab$$initio$ calculations originally developed for X-ray absorption spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A Preliminary Investigation for the Use of Digital Gamma-Gamma Coincidence Spectrometry to Determine 239 Pu

Gamma-ray spectrometry is one of the most effective ways to determine the activity of 239 Pu, depending on activity levels. However, often high backgrounds in complex spectra with low amounts of 239 Pu can increase detection limits. The effectiveness of the use of gamma-gamma spectrometry in the characterization of 239 Pu was studied for the first time. Using the XIA Pixie-16 digital pulse processor, the gamma-gamma system was studied to establish unshielded background radiation, source to detector distances, Poisson statistics and gating of several gamma-rays from 239 Pu. The results clearly show that the distance between gamma ray spectrometers has a much bigger effort in counting statistics for the gamma-gamma coincidence detectors than a single detector. In addition, measurements demonstrated the background radiation to be virtually negligible, meaning gammagamma spectroscopy can still be very effective without requiring the usual lead shielding. Other measurements were taken to assure Poisson statistics were attained in the digital system. Preliminary measurements revealed 3 orders of magnitude background reduction for the measurement of 239 Pu using gated gamma-rays.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Rapid neutron and gamma-ray source localization using machine learning

Rapid localization of radiation sources is critical for applications including nuclear emergency response, safeguards, and security. However, conventional imaging systems such as neutron scatter cameras and Compton cameras depend on rare coincidence events, which often result in long acquisition times. In this work, we address the challenge of rapid source localization by developing a machine learning approach to predict the direction of a single radiation source using only count rates from an array of neutron and gamma-ray detectors. The proposed model is a fully connected neural network (FCNN) trained using Monte Carlo simulation data from a 252 Cf source. The model hyperparameters are optimized with a small set of routine 252 Cf measurements. We benchmarked the performance of the trained and optimized machine learning model using additional 252 Cf , 137 Cs , and PuBe measurements under laboratory conditions with varying source-detector configurations. For these measurements, the machine learning model achieved a mean localization error smaller than 30° with 3 x 10 3 system counts, corresponding to 8 s measurement time for the imaging system used in this work. In this low-statistics regime, the method outperformed traditional scatter-based imaging by more than 75% in localization accuracy for the evaluated measurement configurations. These results demonstrate that a machine learning-based approach can significantly reduce the time required for accurate single-source localization, providing a robust and computationally efficient alternative to traditional imaging systems in time-critical nuclear security and emergency response scenarios.

Gamma-ray imaging↗
DOE OSTI2022

Characterisations of the HinOTORI telescope with a three-color imager at Ali Observatory in Western Tibet

HinOTORI is a new telescope supported by an international collaboration project between China and Japan. It is a 50 centimeter telescope equipped with simultaneous three-color imagers (u',R C , and I C bands). It is located at Ali Observatory at an altitude of 5100m. Thanks to the high altitude and extreme dryness, Ali site is one of the most suitable sites for optical astrometry. HinOTORI telescope aims at detecting optical transients such as the counterparts of gravitational wave (GW) sources, supernovae, gamma-ray bursts (GRB) and so on. This paper describes the site information, design of simultaneous three-color optical layout, system instruments and whole control system. We also report some telescope characterisations for three bands (u'/R C /I C ) respectively, such as Hartmann constant (0.49"/0.56"/0.60"), best focus position (3.922/3.920/3.903 mm), PSF FWHM size (3.755/3.328/3.167pixels), total transmittance and limiting magnitude (15.69/17.57/17.05mag, 10 σ 30 seconds exposure time). With different airmass observation data, the atmospheric extinction coefficients of three bands (0.366/0.061/0.026) were also derived.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Scoping Study: Scintillator Array for Fission Correlation Studies

This scoping study uses a simulation based on the PROSPECT (1) detector to assess the conceptual design of a modular system that could efficiently and simultaneously measure the Prompt Fast Neutron Spectrum (PFNS), the prompt fission neutron multiplicity, the prompt fission gamma-ray multiplicity and total energy, as well as temporal and angular correlations between the detected particles. The proposed experiment would require a mono-energetic pulsed neutron beam incident on an actinide target in the center of the detector. Beam induced backgrounds due to elastic and inelastic neutron scattering on the target are considered, while other backgrounds are ignored for this study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detection of Anomalies in Environmental Gamma Radiation Background with Hopfield Artificial Neural Network - Consortium on Nuclear Security Technologies (CONNECT) Q3 Report

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to investigate performance of a Hopfield Neural Network (HNN) in in detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign. One data set contained a 137 Cs source, and another dataset contained a 131 I source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Development of Hopfield Artificial Neural Network for Anomaly Detection in Environmental Gamma Radiation Background: Consortium on Nuclear Security Technologies (CONNECT) (Q2 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore supervised machine learning (ML) algorithms for development of a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm for detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Detection of Anomalies in Gamma Background Radiation Data with K-Means and Self-Organizing Map Clustering Algorithms (Consortium on Nuclear Security Technologies (CONNECT) Q1 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. The challenge is that spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Neutrinos from the Galactic Center Hosting a Hypernova Remnant

Similar to star-forming galaxies or starburst galaxies, star-forming regions in our Galaxy can host cosmic-ray (CR) accelerators and rich gas as targets of hadronuclear interaction. By our estimations, the IceCube neutrino observatory might detect muon neutrinos from a CR accelerator associated with a molecular cloud complex in our Galaxy. The associated high-energy gamma-ray emission might be observed by the Cherenkov Telescope Array (CTA), High-Altitude Water Cherenkov Gamma-Ray Observatory (HAWC), and Large High Altitude Air Shower Observatory (LHAASO). Furthermore, taking the Galactic Center (GC) region as an example, we assume that a hypernova exploded in the past in the GC. We simulate the acceleration of CRs in the hypernova remnant (HNR) as well as their confinement and escape. The high-energy protons escape from the HNR, diffuse around the GC, interact with molecular clouds, and then produce gamma-rays and neutrinos. In the optimal cases, the GC would be a promising 100 TeV gamma-ray source for LHAASO’s one-month observation. We propose that neutrino-induced searching for starting track-like and high-energy starting events (HESEs) observed by IceCube, from the GC region with a radius of 1°.8, would help us discover the particle accelerator in the GC or constrain our models. Under the constraint from high-energy gamma-ray observations by the H.E.S.S. telescope, we estimate the exposure time needed to make a significant discovery for the optimal cases. The analysis combining observations of IceCube and ANTARES, starting track-like events and HESEs, future observations by neutrino detectors IceCube-Gen2 and KM3net, and gamma-ray telescopes CTA, HAWC, and LHAASO would help to constrain our models.

79 ASTRONOMY AND ASTROPHYSICS↗