Correcting for neutron width fluctuations in Hauser-Feshbach gamma branching ratios
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Physics - Nuclear physics and radiation physics↗
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127 Xe quantification method development and intercomparison exercise
Monitoring of the atmosphere for fission products ( 131m Xe, 133m Xe, 133 Xe, and 135 Xe) is performed by various laboratories to detect nuclear explosions. Quantification of 127 Xe is not routinely performed by laboratories measuring atmospheric radioxenon because it is not a fission product. 127 Xe was recently detected by a ground-based beta-gamma air monitoring system. When measured using beta-gamma coincidence detector systems, such as those in use on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), 127 Xe can interfere with the quantification of fission product radioxenon due to overlap of the 127 Xe beta-gamma coincidence signatures with those of fission product radioxenon. Here, this work demonstrates quantification of 127 Xe at different laboratories with different measurement techniques. Production and purification of 127 Xe was performed by neutron activation of enriched 126 Xe. The purified 127 Xe was then split between laboratories, and detection and quantification methods were developed. At Idaho National Laboratory, a quantification method involving high purity germanium detectors was devised that included self-attenuation correction. At AWE, a beta-gamma coincidence counting method, as used in support of the IMS, was modified to enable the measurement and analysis of the 127 Xe samples. Corrections were made for self-attenuation, which showed a strong xenon volume dependency, for some coincidence signatures. The gas sample activity concentration was used as the comparison metric and it showed excellent agreement between the methods.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Accelerated 133 Xe Quantification in Samples Containing Significant 133 mXe
The quantification of 133 Xe in the presence of its mother radionuclide 133 mXe requires the full quantification of both to perform the ingrowth correction for 133 Xe. Due to the nature of both of these radionuclides, the 133 mXe requires significantly more time to quantify by High Purity Germanium (HPGe) detectors due to lower production yields, lower gamma emission probabilities, and lower detection efficiencies. This work shows that 133 Xe and 133 mXe quantification can be accelerated by measuring the 133m:133 activity ratio for a large batch of material and applying this activity ratio to assays of lower activity subsamples of the same batch of material. Included in this report are derivations of the required decay correction equations, and experiments using actual samples to validate the performance of these equations. A detector calibration method is also shown that leverages this method as an alternative to existing calibration methods for 133 mXe quantification.
133mXe↗
Software Verification of VARPOW
The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power densities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.
97 MATHEMATICS AND COMPUTING↗
Software Verification of VARPOW
The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power desnities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Software Verification of VARPOW
The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power desnities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. Recently the clad neutron damage calculation capability was introduced into VARPOW, and it now allows a pathway to get distributions of clad DPA. The purpose of this work is to verify the power distribution, fast neutron flux and clad DPA results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.
Zhong, Zhaopeng [Argonne National Laboratory (ANL)↗
Sustainable production of radionuclidically pure antimony-119
Background Radiopharmaceutical therapy (RPT) uses radionuclides that decay via one of three therapeutically relevant decay modes (alpha, beta, and internal conversion (IC) / Auger electron (AE) emission) to deliver short range, highly damaging radiation inside of diseased cells, maintaining localized dose distribution and sparing healthy cells. Antimony-119 ( 119 Sb, t 1/2 = 38.19 h, EC = 100%) is one such IC/AE emitting radionuclide, previously limited to in silico computational investigation due to barriers in production, chemical separation, and chelation. A theranostic (therapeutic/diagnostic) pair can be formed with 119 Sb’s radioisotopic imaging analogue 117 Sb (t 1/2 = 2.80 h, E γ = 158.6 keV, I γ = 85.9%, β + = 262.4 keV, I β+ = 1.81%). Results Within, we report techniques for sustainable and cost-effective production of pre-clinical quality and quantity, radionuclidically pure 119 Sb and 117 Sb, novel low energy photon measurement techniques for 119 Sb activity determination, and physical yields for various tin target isotopic enrichments and thicknesses using (p, n) and (d, n) nuclear reactions. Additionally, we present a two-column separation providing a radioantimony yield of 73.1% ± 6.9% (N = 3) and tin separation factor of (6.8 ± 5.5) x 10 5 (N = 3). Apparent molar activity measurements for deuteron produced 117 Sb using the chelator TREN-CAM were measured at 42.4 ± 25 MBq 117 Sb/µmol (1.14 ± 0.68 mCi/µmol), and we recovered enriched 119 Sn target material at a recycling efficiency of 80.2% ± 5.5% (N = 6) with losses of 11.6 mg ± 0.8 mg (N = 6) per production. Conclusion We report significant steps in overcoming barriers in 119 Sb production, chemical isolation and purification, enriched target material recycling, and chelation, helping promote accessibility and application of this promising therapeutic radionuclide. We describe a method for 119 Sb activity measurement using its low energy gamma (23.87 keV), negating the need for attenuation correction. Finally, we report the largest yet-measured 119 Sb production yields using proton and deuteron irradiation of natural and enriched targets and radioisotopic purity > 99.8% at end of purification.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function
ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.
Wolfson, Molly↗
Implementation of Johnson Noise Thermometry into Radiation Hardened Electronics
The random motion of charge carriers in an electrical conductor is a function of its temperature. This phenomenon generates an electrical signal, referred to as Johnson noise, that is present in all analog signals. Conversely, the temperature dependence of the Johnson noise spectrum also enables a direct measurement of absolute temperature, which can provide a secondary measurement of temperature when quantified using sensors such as resistive temperature devices (RTDs) in a process called Johnson noise thermometry (JNT). For nuclear environments, this is of particular interest in correcting for RTDs signal drift caused by accumulation, transmutation, and displacement damage caused by neutron and gamma irradiation.
42 ENGINEERING↗
Detailed Characterization of CZT Detector Response for Improved Coded-Aperture Imaging Performance
Gamma-ray imaging is a powerful method for locating and quantifying sources of radiation. The coded-aperture technique demonstrates superior angular resolution in comparison to other methods (e.g., Compton reconstruction). In this method, a mask constructed of highly attenuating material encodes the scene as a shadow pattern on a position-sensitive detector; this pattern can then be used to recreate the origin(s) of incident radiation. This is typically done through convolution of the mask and shadow patterns. Iterative methods which attempt to reconstruct the observed shadow pattern using a weighted combination of simulated patterns may also be employed. In either case, errors in event position reconstruction due to detector imperfections alter the shadow pattern and will therefore degrade system performance and may introduce imaging artifacts. These effects can be mitigated with a detailed understanding of such errors – allowing for the generation of representative simulations that include the errors and/or correction of raw imager data to remove the errors. We present a calibration process for a commercially available cadmium zinc telluride (CZT) gamma imager which provides a comprehensive characterization of the spatial and energy dependence of event reconstruction. By illuminating a mask featuring a regular grid of pinholes with a calibration source, the localized response of the detector can be measured with fine granularity. These local responses are combined to generate a full detector response map which can be used to distort simulations in a manner that is representative of the observed detector data. Details of the calibration procedure and an assessment of the impact of its end products on the performance of iterative imaging methods will be presented.
Ziock, Klaus-Peter↗
Applying simulation-based inference to spectral and spatial information from the Galactic Center gamma-ray excess
Abstract The two most favored explanations of theFermiGalactic Center gamma-ray excess (GCE) are millisecond pulsars and self annihilation of the smooth dark matter halo of the galaxy. In order to distinguish between these possibilities, we would like to optimally use all information in the available data, including photon direction and energy information.To date, analyses of the GCE have generally treated directional and energy information separately, or have ignored one or the other completely.Here, we develop a method for analyzing the GCE that relies on simulation-basedinference with neural posterior models to jointly analyze photon directional and spectral information while correctly accounting for the spatial and energy resolution of the telescope, here assumed to be theFermiLarge Area Telescope (LAT).Our results also have implications for analyses of the diffuse gamma-ray background, which we discuss.
Astronomy & Astrophysics↗
Plausible indication of gamma-ray absorption by dark matter in NGC 1068
NGC 1068 is the brightest extragalactic source in high-energy neutrinos as seen by IceCube, yet the accompanying gamma-ray flux is orders of magnitude weaker. It has been argued that this indicates that the bulk of neutrinos and gamma rays are emitted in the innermost vicinity of the central supermassive black hole, which is transparent to neutrinos, but opaque to gamma rays. Even in such extreme scenarios for the acceleration of cosmic rays, astrophysical models typically overestimate the low-energy gamma-ray flux and/or require some fine-tuning in the physical parameters. Here, in this work, we suggest instead that the dark matter surrounding the supermassive black hole may absorb the gamma rays, inducing the observed deficit. We show that for a dark matter–photon scattering cross section in the range σ DM−γ /m DM ≃ 10 −28 −10 −30 cm 2 /GeV, Fermi-LAT measurements can be well reconciled with IceCube data. We also present some simple particle physics examples that achieve the correct spectral energy dependence while respecting complementary constraints.
Active Galactic Nuclei↗
QED corrections to the thermal neutrino interaction rate
Abstract Motivated by precision computations of neutrino decoupling at MeV temperatures, we show how QED corrections to the thermal neutrino interaction rate can be related to the electron-positron spectral function as well as an effective$$\overline{\nu }\nu \gamma $$vertex. The spectral function is needed both in a timelike and in a spacelike domain, and for both of its physical polarization states (transverse and longitudinal with respect to spatial momentum). Incorporating an NLO evaluation of this spectral function, an estimate of the$$\overline{\nu }\nu \gamma $$vertex, and HTL resummation of scatterings mediated by soft Bose-enhancedt-channel photons, we compute the interaction rate as a function of the neutrino momentum and flavour. Effects on the – (0. . .2)% level are found, noticeably smaller than a previous estimate of a related quantity.
Physics↗
H420 Imager Calibration Procedure: Field of View Scan
Gamma-ray imagers with coded apertures have a finite field of view (FOV) within which an image of a source can be generated. A “FOV scan” is a facet of imager calibration procedure that involves collecting specialized data for a range of source locations filling the FOV in order to understand and correct for differences in imager performance. Systematic distortions reveal relative displacements between internal imager components, which can be accounted for in data analysis. The success of this scan requires a stable imager position during the full measurement duration (~hours). This document summarizes the hardware and software tools required to conduct a FOV calibration scan of an H3D H420 Coded Aperture Gamma-Ray Imager.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra
A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network
The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Radiological Source Term Estimation and Isotopic Identification with Parallel Log Domain Particle Filters
This paper presents a parallel log-domain particle filtering algorithm combined with gamma spectrum unfolding to perform localization, identification, and evaluation of multiple point sources of various isotopes in an environment with attenuating obstacles. The method uses sets of precomputed attenuation kernels that map the attenuation characteristics of the environment. These kernels are specific to the energy level of a photopeak of interest. The spectral measurements are deconvolved into count measurements of each photopeak. These count measurements are fed into a set of parallel particle filters using attenuation kernels computed for that photopeak’s energy level. The individual regularized particle filters perform all likelihood calculations in the logarithmic domain to mitigate the effects of particle degeneracy. The output of each particle filter is combined to estimate which isotopes are present as well as their positions and strengths. The performance of the algorithm is characterized in a lab-scale environment using a mobile robot equipped with a gamma ray spectrometer in the presence of up to three different radioactive isotopes simultaneously. The sources were localized to within 10 cm, and their strengths were estimated within 10% of their true values. Furthermore, the isotopes were all correctly identified, and no spurious sources were reported.
42 ENGINEERING↗
CTA and SWGO can discover Higgsino dark matter annihilation
Thermal Higgsino dark matter (DM), with a mass near 1.1 TeV, is one of the most well-motivated and untested DM candidates. Leveraging recent hydrodynamic cosmological simulations that give DM density profiles in Milky Way analog galaxies we show that the linelike gamma-ray signal predicted from Higgsino annihilation in the Galactic Center could be detected at high significance with the upcoming Cherenkov Telescope Array (CTA) and Southern Wide-field Gamma-ray Observatory (SWGO) for all but the most pessimistic DM profiles. We perform the most sensitive search to-date for the linelike signal using 15 years of data from the Fermi Large Area Telescope, coming within an order one factor of the necessary sensitivity to detect the Higgsino for some Milky Way analog DM density profiles. We show that H.E.S.S. has subleading sensitivity relative to Fermi for the Higgsino at present. In contrast, we analyze H.E.S.S. inner Galaxy data for the thermal wino model with a mass near 2.8 TeV; we find no evidence for a DM signal and exclude the wino by over a factor of two in cross section for all DM profiles considered. In the process, we identify and attempt to correct what appears to be an inconsistency in previous H.E.S.S. inner Galaxy analyses for DM annihilation related to the analysis effective area, which may weaken the DM cross-section sensitivity claimed in those works by around an order of magnitude.
79 ASTRONOMY AND ASTROPHYSICS↗