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The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗

Performance Improvements for the Griffin Transport Solvers

Griffin is a Multiphysics Object-Oriented Simulation Environment based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. Griffin includes a variety of deterministic radiation transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. A code assessment performed in FY-20 identified two significant issues with the transport solvers in Griffin: first, the primary heterogeneous SN (discrete ordinates) transport solver based on continuous finite element methods required significant mesh refinement and higher memory usage compared to solvers based on the method of characteristic for equivalent accuracy. Second, the homogeneous PN (spherical harmonics expansion) transport solver did not adequately support polynomial refinement, which is a feature usually required for problems with spatial homogenization and pronounced streaming, typical in fast or gas-cooled reactor systems. To address the first issue, the development effort focused on the more promising discontinuous finite element method (DFEM)-based SN transport solver in Griffin. The addition of an asynchronous parallel transport sweeper and coarse mesh finite difference (CMFD) acceleration have rendered a superior heterogeneous SN transport capability for multiphysics problems that requires far less computing resources in terms of both CPU time and memory usage. This is demonstrated with typical thermal- and fast-spectrum reactor benchmark problems, including 2D Transient Reactor Test, 3D Advanced Burner Test Reactor (ABTR), and 2D and 3D Empire microreactor. For the second issue, the development effort focused on a new transport solver based on the hybrid finite element PN method (HFEM-PN), equivalent to the variational nodal method, as well as a new diffusion solver based on HFEM-Diffusion. This solver is intended for homogenized domains with multiphysics coupling (i.e., supports mesh displacement, seamless temperature feedback, etc.). Initial calculations with the HFEM-Diffusion implementation show very good parallel efficiency for the residual evaluations with the 2D ABTR benchmark. A future development effort will be centered on further improvements to the CMFD, HFEM-PN, and DFEM diffusion solvers to ensure Griffin meets performance and software quality assurance requirements for advanced reactor design and analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Strong QCD Insights from Excited Nucleon Structure Studies with CLAS and CLAS12

Studies of the spectrum of hadrons and their structure in experiments with electromagnetic probes offer unique insight into many facets of the strong interaction in the regime of large quark-gluon running coupling, i.e. the regime of strong QCD. The experimental program within Hall B at Jefferson Laboratory based on data acquired with the CLAS spectrometer using electron and photon beams with energies up to 6 GeV has already considerably extended the scope of research in hadron physics in joint efforts between experiment and phenomenological data analysis. Impressive progress in relating the hadron structure observables inferred from the data to the strong QCD mechanisms underlying hadron mass generation has been achieved in the past decade. Furthermore, these results will be considerably extended with data from the experimental program with the new CLAS12 spectrometer that has begun data taking using electron beams with energies up to 11 GeV. With this extended kinematic reach the structure of nucleon resonances will be probed at the highest photon virtualities ever achieved in the studies of exclusive electroproduction, which will allow for the exploration of the distance scale where>98% of light hadron mass emerges from QCD in the transition of the strong interaction from the regime of quark-gluon confinement to perturbative QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multiquanta flux jumps in superconducting fractal

We study the magnetic field response of millimeter scale fractal Sierpinski gaskets (SG) assembled of superconducting equilateral triangular patches. Directly imaged quantitative induction maps reveal hierarchical periodic filling of enclosed void areas with multiquanta magnetic flux, which jumps inside the voids in repeating bundles of individual flux quanta Φ 0 . The number N s of entering flux quanta in different triangular voids of the SG is proportional to the linear size s of the void, while the field periodicity of flux jumps varies as 1/s. We explain this behavior by modeling the triangular voids in the SG with effective superconducting rings and by calculating their response following the London analysis of persistent currents, J s , induced by the applied field H a and by the entering flux. With changing H a , J s reaches a critical value in the vertex joints that connect the triangular superconducting patches and allows the giant flux jumps into the SG voids through phase slips or multiple Abrikosov vortex transfer across the vertices. The unique flux behavior in superconducting SG patterns, may be used to design tunable low-loss resonators with multi-line high-frequency spectrum for microwave technologies.

36 MATERIALS SCIENCE↗

Design workflow of a symmetric traveling wave antenna for fast ion production on DD tokamaks

Initial computational plasma physics scoping and a finite element method antenna modeling design workflow for a symmetric center-fed high-field side high harmonic fast wave traveling wave array (TWA) antenna are reported here. The TWA is designed to generate a test population of fast deuterium ions in an existing D–D tokamak by heating neutral beam deuterium ions, accelerating them from 80 keV to several hundred keV. The resulting fast particles are tailored to mimic key reactor energetic particle parameters with regards to exciting Alfven eigenmode instabilities, allowing for a D–D tokamak like DIII-D or ASDEX-U to replicate reactor-relevant conditions experimentally. Initial scenario scoping for high single-pass absorption as well as good preferential fast ion damping relative to electron damping was completed using the ray-tracing/Fokker–Planck codes GENRAY and CQL3D. Python RF network analysis packages were used to create a custom TWA optimization tool to inform a COMSOL flat antenna design, and Petra-M was used to study cold plasma effects. The TWA produced by this workflow has several novel features when compared to previous TWA studies, including symmetric center feeding, and passive end straps for image current cancellation for reduced impurity production. We show here that the antenna design workflow can readily produce TWA antennas optimized for reflection coefficient, image current cancellation, and launched power spectrum shape; and that a population of fast ions can be generated in the correct region of parameter space, warranting future more detailed studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Large-scale cascading of first-order FBG array in a highly multimode coreless fiber using femtosecond laser for distributed thermal sensing

This research focuses on the performance analysis and characterization of a fiber Bragg gratings (FBGs) array, consisting of 10 first-order FBGs inscribed by a femtosecond (FS) laser in a highly multimode coreless fiber. The study evaluates the FBG array's ability to function as a distributed thermal sensing (DTS) platform, with the coreless fiber chosen as the sensing element due to its immunity to dopant migration at high temperatures. The design of a large cascaded first-order FBG array effectively eliminates unwanted harmonic peaks across a wide spectrum range. In contrast, higher-order FBGs introduce limitations due to the overlapping of Bragg peaks with harmonics. The FBG array's performance is evaluated by measuring the reflection spectrum of each grating at different temperatures, showing a high temperature sensitivity of 15.05 pm/°C at a Bragg wavelength of 1606.3 nm, with a linear response in the temperature range of 24 - 1100 °C. The FBG array was designed for a spatial resolution of 5 mm. A mode scrambler in the sensing network is employed, which suppresses multimodal interference, characterizes FBG peak visibility, and stabilizes the interference spectrum. The stability of the FBG array is also assessed over 24 hrs at 1100 °C, and it is observed to be stable during thermal treatment. Heat treatment at 1100°C improves the signal to noise ratio of the FBG array, demonstrating the robustness and suitability of the proposed FBG array on highly multimode coreless fiber as a potential sensing platform for DTS applications in harsh environmental conditions, overcoming the issues of dopant migration presented by dopes silica optical fibers at high temperatures.

47 OTHER INSTRUMENTATION↗

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗

Construction of Photo‐Responsive Pd 2 L 4 ‐Type Nanocages based on Feringa's Second‐Generation Motor and Its Guest Binding Ability for C 60

Abstract We present the construction of a M 2 L 4 ‐type metal‐organic nanocage featuring four endohedral Feringa's motor motifs and its adaptive encapsulation towards a C 60 guest molecule. The structure of the cage, though complicated on the 1 H NMR spectrum due to the adoption of mixed ligands, was unambiguously characterized with a combination of ESI‐MS, 2D DOSY, 13 C NMR and particularly the SAXS technique. The molecular motor within the cage demonstrated similar photophysical properties to the uncoordinated one, indicating the motor's function was not compromised when it was anchored in such a confined nanospace. Furthermore, the nanocage showed good guest encapsulation ability towards C 60 , and a guest induced‐fit behavior of the cage was revealed based on the extensive SAXS analysis and molecular dynamics simulation. The adaptive motorized nanocage reported here represents one of the very few examples of integrating individual motors into a discrete nanoconfined system and offers prospects to achieve its non‐equilibrium functions.

Chemistry↗

The Carnegie Supernova Project I: Spectroscopic analysis of stripped-envelope supernovae

An analysis leveraging 170 optical spectra of 35 stripped-envelope (SE) core-collapse supernovae (SNe) observed by the Carnegie Supernova Project I and published in a companion paper is presented. Mean template spectra were constructed for the SNe IIb, Ib, and Ic subtypes, and parent ions associated with designated spectral features are identified with the aid of the spectral synthesis code SYNAPPS. Our modeled mean spectra suggest the ~6150 Å feature in SNe IIb may have an underlying contribution due to silicon, while the same feature in some SNe Ib may have an underlying contribution due to hydrogen. Standard spectral line diagnostics consisting of pseudo-equivalent widths (pEWs) and blue-shifted Doppler velocity were measured for each of the spectral features. Correlation matrices and rolling mean values of both spectral diagnostics were constructed. A principle component analysis (PCA) was applied to various wavelength ranges of the entire dataset and suggests clear separation among the different SE SN subtypes, which follows from trends previously identified in the literature. In addition, our findings reveal the presence of two SNe IIb subtypes, a select number of SNe Ib displaying signatures of weak, high-velocity hydrogen, and a single SN Ic with evidence of weak helium features. Our PCA results can be leveraged to obtain robust subtyping of SE SNe based on a single spectrum taken during the so-called photospheric phase, separating SNe IIb from SNe Ib with ~80% completion.

79 ASTRONOMY AND ASTROPHYSICS↗

Ordered magnetic fields around the 3C 84 central black hole

Context. 3C 84 is a nearby radio source with a complex total intensity structure, showing linear polarisation and spectral patterns. A detailed investigation of the central engine region necessitates the use of very-long-baseline interferometry (VLBI) above the hitherto available maximum frequency of 86 GHz.Aims. Using ultrahigh resolution VLBI observations at the currently highest available frequency of 228 GHz, we aim to perform a direct detection of compact structures and understand the physical conditions in the compact region of 3C 84.Methods. We used Event Horizon Telescope (EHT) 228 GHz observations and, given the limited (u, v)-coverage, applied geometric model fitting to the data. Furthermore, we employed quasi-simultaneously observed, ancillary multi-frequency VLBI data for the source in order to carry out a comprehensive analysis of the core structure.Results. We report the detection of a highly ordered, strong magnetic field around the central, supermassive black hole of 3C 84. The brightness temperature analysis suggests that the system is in equipartition. We also determined a turnover frequency of νm = (113 ± 4) GHz, a corresponding synchrotron self-absorbed magnetic field of BSSA = (2.9 ± 1.6) G, and an equipartition magnetic field of Beq = (5.2 ± 0.6) G. Three components are resolved with the highest fractional polarisation detected for this object (mnet = (17.0 ± 3.9)%). The positions of the components are compatible with those seen in low-frequency VLBI observations since 2017–2018. We report a steeply negative slope of the spectrum at 228 GHz. We used these findings to test existing models of jet formation, propagation, and Faraday rotation in 3C 84.Conclusions. The findings of our investigation into different flow geometries and black hole spins support an advection-dominated accretion flow in a magnetically arrested state around a rapidly rotating supermassive black hole as a model of the jet-launching system in the core of 3C 84. However, systematic uncertainties due to the limited (u, v)-coverage, however, cannot be ignored. Our upcoming work using new EHT data, which offer full imaging capabilities, will shed more light on the compact region of 3C 84.Key words: techniques: high angular resolution / techniques: interferometric / galaxies: active / galaxies: individual: NGC 1275 / galaxies: jets

79 ASTRONOMY AND ASTROPHYSICS↗

Development of a Fast Spectrum Test Loop at the Advanced Test Reactor

The United States currently has no infrastructure to provide a fast neutron flux for research purposes. With the increased interest in Sodium Fast Reactor (SFR) technology, this type of infrastructure is necessary for further development of key components such as Versatile Test Reactor. The purpose of this research is to characterize the thermal hydraulics of a test loop capable of providing SFR like operating conditions. This includes showcasing feasibility in mechanical design, reaching a high fast to thermal neutron flux ratio ideally near 15, an inlet temperature of 600 K, a temperature increase of 50 K from inlet to outlet, and test chamber radial temperature profiles similar to SFR fuel rods. Existing infrastructure must be used to provide the neutron flux for the test loop, and it was decided that the Advanced Test Reactor (ATR) was the optimal choice due to its availability and previous work conducted similar to this project. To achieve the goals of this project, several mechanical designs were put forward with the most feasible design being chosen. The neutronics and thermal hydraulics analysis were conducted in tandem, with an iterative process used to maximize efficiency of both systems. Analysis of the neutronics system was done using Attila and MCNP while the thermal hydraulic analysis was done using RELAP5. This document outlines the thermal hydraulic analysis, though it includes the results from the mechanical design and neutronics analysis. The loop design includes a primary system with molten sodium, a set of “booster fuel plates” to increase the fast flux within the test section, a water system to cool the booster fuel plates, a helium system to separate the sodium and water systems, and a thermal neutron shield to decrease the thermal flux. Each of these systems is modeled in the neutronics and thermal hydraulic analyses. The RELAP5 model showcased the feasibility of the design proposed by this report. For all designs tested, the desired 50 K temperature increase from inlet to outlet was reached. The fuel rod radial temperature profile was lower than was expected, likely due to a lower rod thermal power than expected. A parametric study was also conducted to characterize the system with three fuel pins. This study showed the effect of thermal power, fluid pressure, fluid velocity, and inlet temperature on the system. ©Copyright by Anton Higgins December 11, 2019 All Rights Reserved

99 GENERAL AND MISCELLANEOUS↗

Analysis of direct and indirect noise in a next-generation aviation gas turbine combustor

A large-eddy simulation (LES) of a next-generation combustor is performed to examine effects of this combustor concepts on direct and indirect combustion noise characteristics. Direct noise is computed considering the unsteady heat release predictions while entropy fluctuations in the downstream part of the combustor are used to estimate indirect noise through the transfer function of the outlet nozzle. A low-order acoustic reconstruction technique, which utilizes the Green’s function of the configuration, is developed to compute the acoustics inside the combustor. Comparisons to experimental results are reported, showing the reasonable accuracy of the LES and combustion noise computations. The direct noise spectrum peaks at frequencies around 3 kHz because of the fast timescales associated with the chemical reactions inside the combustor. In addition, the indirect noise is dominant at low frequencies, i.e., less than 400 Hz, because of the characteristics of the entropy spectrum at the outlet nozzle. Further, compared to a conventional rich-quench-lean (RQL) combustor configuration, significant differences in the acoustics are observed, and are explained by two specific technological novelties. Firstly, the direct noise spectrum peaks at significantly higher frequencies due to the combustor’s compactness. Secondly, the entropy inhomogeneties downstream of the combustion region are an order of magnitude smaller in amplitude due to the lack of dilution with cold air. This leads to a significant reduction in the indirect noise amplitude at low frequencies, where it is the dominant source of noise. These results suggest opportunities for advanced combustion technologies to achieve substantial reductions in combustion-related noise.

42 ENGINEERING↗

MYC transcription factors coordinate tryptophan–dependent defence responses and compromise seed yield in Arabidopsis

Robust plant immunity negatively affects other fitness traits, including growth and seed production. Jasmonate (JA) confers broad-spectrum protection against plant consumers by stimulating the degradation of JASMONATE ZIM-DOMAIN (JAZ) proteins, which in turn relieves repression on transcription factors (TFs) coincident with reduced growth and fecundity. The molecular mechanisms underlying JA-mediated decreases in fitness remain largely unknown. To assess the contribution of MYC TFs to growth and reproductive fitness at high levels of defence, we mutated three MYC genes in a JAZ-deficient mutant (jazD) of Arabidopsis thaliana that exhibits strong defence and low seed yield. Genetic epistasis analysis showed that de-repression of MYC TFs in jazD not only conferred strong resistance to insect herbivory but also reduced shoot and root growth, fruit size and seed yield. We also provided evidence that the JAZ–MYC module coordinates the supply of tryptophan with the production of indole glucosinolates and the proliferation of endoplasmic reticulum bodies that metabolise glucosinolates through the action of b-glucosidases. Our results establish MYCs as major regulators of growth- and reproductive–defence tradeoffs and further indicate that these factors coordinate tryptophan availability with the production of amino acid-derived defence compounds.

59 BASIC BIOLOGICAL SCIENCES↗

A Business Case Evaluation of Gas Switching Reforming (GSR) Technology: A Promising Technology for Natural Gas Reforming with Integrated CO2 Capture

Hydrogen is essential in the transition to sustainable energy, and developing low-carbon production methods is a key research focus. Traditional steam methane reforming (SMR) dominates the hydrogen industry but contributes substantially to CO2 emissions. In response, Gas Switching Reforming (GSR) has emerged as a novel process that integrates carbon capture and utilizes process heat more efficiently. Unlike other reforming methods, GSR consolidates oxidation and reduction reactions within a single reactor, which minimizes external energy inputs and simplifies scaling. Like conventional steam methane reforming (SMR), GSR can be integrated with water-gas shift and pressure swing adsorption units for pure hydrogen production. This work presents a comprehensive business case analysis of GSR technology based on experimental results in Technology Readiness Level 3, Life Cycle Assessment (LCA) and Techno-Economic (TEA) evaluation incorporating ASPEN Plus process modeling considering different configurations and energy scenarios. The TEA incorporates data from kinetic experiments from various catalysts to evaluate the GSR process under various conditions. The goal of this work is to evaluate GSR’s potential to serve as a low-carbon alternative to SMR, focusing on global warming potential and additional impact categories to evaluate a wide spectrum of environmental impacts. Comparative assessments were conducted with SMR, chemical loop reforming (CLR), and proton exchange membrane (PEM) electrolysis to explore trade-offs across environmental metrics. The environmental impact assessment of this work encompasses the entire hydrogen production lifecycle from raw material extraction to plant decommissioning, using a cradle-to-gate boundary. Preliminary findings highlight that GSR, when integrated with low-carbon energy sources, could significantly reduce environmental impacts, making it a promising candidate for low-carbon hydrogen infrastructure. The insights from this business case evaluation aim to guide industry in scale-up and commercialization of this promising clean energy technology.

03 NATURAL GAS↗

Cumulative short-lived photofission product yields for nuclear forensic application

Experiments have long been carried out with linear accelerator (linac) produced bremsstrahlung X-rays to study high-energy photon-induced fission, known as “photofission”. One benefit of photofission, when compared with neutron-induced fission, is the ability to investigate fundamental physics of fission at excitation energies lower than what is possible with neutrons [1]. Absorption of an incident neutron results in a compound nucleus with an excitation energy at least equal to the neutron binding energy; thus, the lowest energy region of the fission barrier cannot be studied. Fission product yield distributions are dependent on the incident particle energy and the target nucleus mass. They are generally represented by a double-humped curve, with low and high mass “peaks” and an intermediate mass “valley”. As incident particle energy increases, the excitation energy of the nucleus increases, thereby increasing the overall yield of isotopes in the valley with respect to the two maxima or peaks of the fission product curve [3]. Photofission is most probable for incident photons around 14 MeV due to the giant dipole resonance. Induced photofission around this energy results in a fission product yield distribution that resembles 14 MeV DT neutron fission more than thermal or fast (500 keV) neutron fission. In post-detonation nuclear forensics, the peak-to-valley ratio of the fission product yield curve could be used for characterizing device type by providing an indication of the neutron energy spectrum that had induced fission (e.g., 500 keV vs. 14 MeV). The goal of this work is to improve nuclear data for isotopes of interest in nuclear forensics and special nuclear material (SNM) detection, specifically the fission product yield data via photofission experiments for the isotopes of 238U and 232Th. Photofission has been proposed as a less costly and more flexible production method for the valley isotopes that are representative of DT neutron fission product yield distributions, which would benefit nuclear forensics exercises in testing for analysis techniques. Natural uranium and thorium targets were irradiated with bremsstrahlung photons (nominal endpoint energies of 8, 14, and 20 MeV), generated via impingement of high-energy electrons on a tungsten electron-to-photon radiator. Gamma-ray spectroscopy was used to observe and identify the decay of the resulting fission products. The photofission yields of 102 fission products were measured for the set of the 238U and 232Th targets at the three bremsstrahlung X-ray endpoint energies 8, 14, and 20 MeV. These fragments included masses ranging from A=84 to A=144, with half-lives as short as 1.07 seconds.

07 ISOTOPE AND RADIATION SOURCES↗

A practical way to regularize unfolding of sharply varying spectra with low data statistics

Unfolding is a well-established tool in particle physics. However, a naive application of the standard regularization techniques to unfold the momentum spectrum of protons ejected in the process of negative muon nuclear capture led to a result exhibiting unphysical artifacts. A finite data sample limited the range in which unfolding can be performed, thus introducing a cutoff. A sharply falling “true” distribution led to low data statistics near the cutoff, which exacerbated the regularization bias and produced an unphysical spike in the resulting spectrum. An improved approach has been developed to address these issues and is illustrated using a toy model. The approach uses full Poisson likelihood of data, and produces a continuous, physically plausible, unfolded distribution. Here, the new technique has a broad applicability since sharply falling spectra are common.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quantum and classical spin dynamics across temperature scales in the S = 1 / 2 Heisenberg antiferromagnet

Using the framework of semiclassical Landau-Lifshitz dynamics (LLD), we conduct a systematic investigation of the temperature-dependent spin dynamics in the S = 1 / 2 Heisenberg square-lattice antiferromagnet (SAFM). By performing inelastic neutron scattering measurements on Zn 2 VO ( PO 4 ) 2 (ZVPO) and corresponding finite-temperature spin dynamics simulations based on LLD, we present a comprehensive analysis that bridges quantum and classical spin dynamics over a broad temperature range. First, remarkable agreement between experimental data and LLD simulations is found in the paramagnetic phase of ZVPO, demonstrating the capability of LLD in accurately determining the spin Hamiltonian of S = 1 / 2 systems and capturing the quantum-to-classical crossover of their spin dynamics. Second, by analyzing the discrepancies between the experimental data and the LLD simulations at lower temperatures, we determine the experimental temperature dependence of the quantum effects in the excitation spectrum of the S = 1 / 2 SAFM: the quantum renormalization factor for the magnon energies and the quantum continuum above the one-magnon bands. Notably, the emergence of each quantum effect is found to correlate with the formation of three-dimensional long-range order. This work demonstrates the utility of LLD in gaining experimental insights into the temperature-induced modifications of quantum spin dynamics and their convergence towards classical expectations at higher temperatures. This motivates further applications to more challenging quantum antiferromagnets dominated by stronger quantum fluctuations. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗