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At least 289 records · Page 16

Experimental search for the chiral magnetic effect in relativistic heavy-ion collisions: A perspective

The chiral magnetic effect (CME) refers to generation of the electric current along a magnetic field in a chirally imbalanced system of quarks. The latter is predicted by quantum chromodynamics to arise from quark interaction with nontrivial topological fluctuations of the vacuum gluonic field. The CME has been actively searched for in relativistic heavy-ion collisions, where such gluonic field fluctuations and a strong magnetic field are believed to be present. The CME-sensitive observables are unfortunately subject to a possibly large non-CME background, and firm conclusions on a CME observation have not yet been reached. In this perspective, we review the experimental status and progress in the CME search, from the initial measurements more than a decade ago to the dedicated program of isobar collisions in 2018 and the release of the isobar blind analysis result in 2022 to intriguing hints of a possible CME signal in Au + Au collisions, and discuss future prospects of a potential CME discovery in the anticipated high-statistic Au + Au collision data at the Relativistic Heavy-Ion Collider by 2025. We hope such a perspective will help sharpening our focus on the fundamental physics of the CME and steer its experimental search.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Scattering Calorimeter FY24 Deliverable Report

A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Efficient simulation of optical spectra via machine learning and physical decomposition of environmental effects

Simulations of optical spectra can provide key insights to aid experimental interpretation of electronic excitation phenomena. For chromophores in the condensed phase, these spectra, which incorporate the coupling between electronic excitation and molecular and solvent nuclear motions, can be simulated using excitation energies obtained from molecular dynamics simulations of the chromophore and solvent. Here, we present a hybrid scheme that exploits machine learning and physically informed spectral densities to show that as few as 25 ground and excited state energetic gradient calculations can be used to construct models that accurately predict environment-influenced vibronic coupling in optical spectra. We demonstrate our approach for the green fluorescent protein chromophore in water and the cresyl violet chromophore in methanol. We show that our hybrid approach, employing a machine learning model for the high-frequency spectral density and an ab initio parameterized Debye spectral density for the low-frequency, results in a systematic improvement of the optical absorption lineshape, leading to a simple machine learning scheme that can be used for the simulation of spectral densities and optical spectra.

Snider, Andrew [Univ. of California, Merced, CA (U↗

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discovering nuclear models from symbolic machine learning

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated Symbolic Regression approach that handles symbolic regressions over multiple target observables, accounts for experimental uncertainties and is robust against high-dimensional problems. As a proof of principle, we applied this method to describe the nuclear binding energies and charge radii of light and medium mass nuclei. Our approach identified simple analytical relationships based on the number of protons and neutrons, providing interpretable models with precision comparable to state-of-the-art nuclear models. Additionally, we integrated this ML-discovered model with an existing complementary model to estimate the limits of nuclear stability. These results highlight the potential of symbolic ML to develop accurate nuclear models and guide our description of complex many-body problems.

Nuclear structure↗

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dynamic modeling for heavy-ion collisions

Recent theory progress in (3+1)D dynamical descriptions of relativistic nuclear collisions at finite baryon density are reviewed. Heavy-ion collisions at different collision energies produce strongly coupled nuclear matter to probe the phase structure of Quantum Chromodynamics (QCD). Dynamical frameworks serve as a quantitative tool to study properties of hot QCD matter and map collisions to the QCD phase diagram. Outstanding challenges are highlighted when confronting theoretical models with the current and forthcoming experimental measurements from the RHIC beam energy scan program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evolution of Λ polarization in the hadronic phase of heavy-ion collisions

Using the AMPT+MUSIC+URQMD hybrid model, we study the global and local spin polarizations of Λ hyperons as functions of the freeze-out temperature of the spin degree of freedom in the hadronic phase of Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV. Including contributions from both the thermal vorticity and thermal shear of the hadronic matter, we find that with the spin freeze-out temperature dropping from the hadronization temperature of 160 MeV to 110 MeV at the kinetic freeze-out, both the global and local spin polarizations of Λ hyperons due to the thermal vorticity decrease by a factor of 2, while those due to the thermal shear decrease quickly and become negligibly small at 140 MeV. Here our results thus suggest that it is important to take into account the evolution of the spin degree of freedom in the hadronic stage of relativistic heavy-ion collisions when theoretically predicted global and local Λ spin polarizations are compared with the experimental measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dynamical model of J/ψ photoproduction on the nucleon

Here, a dynamical model based on a phenomenological charm quark-nucleon (c – N) potential v cN and the Pomeronexchange mechanism is constructed to investigate the J/ψ photoproduction on the nucleon from threshold to invariant mass W = 300 GeV. The J/ψ – N potential, V J/ψN (r), is constructed by folding v cN into the wave function φ J/ψ ($c\bar{c}$) of J/ψ within a constituent quark model (CQM) of Segovia et al. [Int. J. Mod. Phys. E 22, 1330026 (2013)]. A photoproduction amplitude is also generated by v cN by a $c\bar{c}$–loop integration over the γ → $c\bar{c}$ vertex function and φ J/ψ ($c\bar{c}$). No commonly used vector meson dominance assumption is used to define this photoproduction amplitude which is needed to describe the data near the threshold. The c – N potential v cN (r) is parameterized in a form such that the predicted V J/ψN (r) at large distances has the same Yukawa potential form extracted from a lattice QCD (LQCD) calculation of Kawanai and Sasaki, [Phys. Rev. D 82, 091501(R) (2010)]. The parameters of vcN are determined by fitting the total cross-section data of Jefferson Laboratory (JLab) by performing calculations that include J/ψ – N final-state interactions (FSI). The resulting differential cross sections dσ /dt are found in good agreements with the data. It is shown that the FSI effects dominate the cross section in the very near-threshold region, allowing for sensitive testing of the predicted J/ψ – N scattering amplitudes. By imposing the constraints of J/ψ – N potential extracted from the LQCD calculation of Kawanai and Sasaki, [Phys. Rev. D 82, 091501(R) (2010)], we have obtained three J/ψ – N potentials which fit the JLab data equally well. The resulting J/ψ – N scattering lengths are in the range of a = [-0.05, -0.25] fm. With the determined v cN (r) and the wave functions generated from the same CQM, the constructed model is used to predict the cross sections of photoproduction of η c (1S) and ψ(2S) mesons for future experimental tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of a New Criticality Safety Training Program for College Students

Nuclear criticality safety (NCS) expertise remains a crucial workforce need within the US Department of Energy (DOE) laboratory complex. To address this challenge, a novel university/laboratory-based nuclear criticality training certificate program is being developed through a collaborative effort between the Georgia Institute of Technology, Texas A&M University, and Oak Ridge National Laboratory. This comprehensive program implements a two-tiered certification approach that combines online theoretical coursework with hands-on experimental training to create a sustainable pipeline of nuclear criticality specialists. The program specifically targets undergraduate and graduate students in engineering, physics, and mathematics disciplines across the United States. Through integration of fundamental nuclear physics principles, practical safety applications, and experiential learning opportunities, this initiative aims to establish a standardized pathway for developing the next generation of NCS professionals.

K-Effective↗

Preliminary Plan to Inform Testing of a Heat Exchanger Test Article

This report presents a preliminary plan to guide the qualification testing of advanced heat exchanger (HX) components for nuclear-to-industrial heat transfer applications. The objective is to establish a defensible, physics-based methodology that integrates computational modeling, targeted experimentation, and in-service inspection considerations to demonstrate component performance and reliability under representative reactor conditions. The analysis identifies Sodium-cooled Fast Reactor (SFR) and High-Temperature Gas-cooled Reactor (HTGR) systems as reference configurations in terms of temperature, pressure, and chemical environment. Within these operating envelopes, dominant degradation mechanisms— including creep–fatigue interaction, flow-induced vibration, corrosion, and diffusion-bond deterioration—were evaluated to define test requirements. A comprehensive computationalexperimental framework is proposed to support life prediction and qualification activities. The framework couples high-fidelity structural-mechanics, thermal-hydraulic, and fluid-structure interaction models with accelerated degradation testing to produce a traceable linkage between microstructural evolution, mechanical performance, and remaining useful life (RUL). The approach adheres to established Verification, Validation, and Uncertainty Quantification (VVUQ) standards (ASME V&V 10/20; NUREG-2152) and incorporates a digital-twin architecture for continuous model refinement through data assimilation. The plan further outlines testing methodologies, including pre-test analyses, test-loop design parameters, and sensor placement strategies that maximize information yield while maintaining mechanistic fidelity. Complementary sections describe in-service inspection (ISI), on-line monitoring (OLM), and structural-health-monitoring (SHM) techniques applicable to compact HX geometries typical of advanced reactors. Collectively, these activities establish the technical foundation for demonstrating 40-60-year equivalent service life of advanced heat exchangers in support of the U.S. Department of Energy’s Advanced Reactor and Integrated Energy Systems programs. The forthcoming phase will execute the defined pre-test analyses, initiate hardware fabrication, and implement the integrated testing campaign to validate the proposed qualification methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Densities and momentum distributions in A ≤ 12 nuclei from chiral effective field theory interactions

Current and future electron and neutrino scattering experiments will be greatly aided by a better understanding of the role played by short-range correlations in nuclei. Two-body physics, including nucleon-nucleon correlations and two-body electroweak currents, is required to explain the body of experimental data for both static and dynamical nuclear properties. In this work, we focus on examining nucleon-nucleon correlations from a chiral effective field theory perspective and provide a comprehensive set of new variational Monte Carlo calculations of one- and two-body densities and momentum distributions based on the Norfolk many-body nuclear Hamiltonians for A ≤ 12 systems. Here, online access to detailed tables and figures is available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct Measurement of the Be 7 L / K Capture Ratio in Ta-Based Superconducting Tunnel Junctions

We report a high-statistics measurement of the L / K orbital electron capture ratio in 7 Be embedded in cryogenic Ta. The thin Ta film formed part of a high-resolution superconducting tunnel junction radiation detector that was used to identify the signals from different decay channels. The measured L/K capture ratio of 0.070(7) is significantly larger than the only previous measurement of this quantity and the theoretical predictions that include in-medium effects. This value is a uniquely sensitive probe of the 1s and 2s orbital overlaps with the nucleus and is of relevance to nuclear and atomic physics, as well as Li production in novae and other astrophysical scenarios. Furthermore, this is the first experiment that uses superconducting tunnel junctions for nuclear-recoil detection, opening a new experimental avenue for low-energy precision measurements with rare isotopes.

6 ≤ A ≤ 19↗

Mechanistic Fission Gas Release Uncertainty Induced by Microstructure Data

Fission Gas Release (FGR) is an important engineering safety parameter for nuclear fuel. While fuel performance modeling with BISON currently relies on mechanistic models to predict it, comparison with experimental data shows both under or over prediction depending on operation mode (steady or transient).Predicting microstructure data is essential to accurately predicts the engineering scale parameters. An important source of uncertainty in mechanistic models arises from the missing captured physics. Continuous validation and refinement of these models against experimental data are also necessary to ensure their reliability and accuracy in predicting engineering parameters.

36 - MATERIALS SCIENCE↗

Experimental validation of scintillator detector response to correlated neutrons with MCNP and associated packages

Time, energy, and angle correlated neutrons are emitted in nuclear fission. New, physics-based fission event generators that capture these correlations have been incorporated into MCNP6.2 because correlations can impact nuclear non-proliferation and safeguards systems response. DRiFT is a detector response code that takes MCNP outputs and reproduces laboratory analogous detector quantities. Previous work has compared DRiFT to single detector experiment data and has discussed recent updates to DRiFT specific to correlated fission experiments. In this work, we demonstrate a validation of recent updates to DRiFT for organic scintillator response in correlated fission neutron experiments using a 252Cf source. Furthermore, outputs from MCNP with the FREYA fission event generator were post-processed with DRiFT and compared to experiment data. Simulation and experiment results are in reasonably good agreement for multiple correlated neutron quantities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deciphering Fingerprints of Stellar Nucleosynthesis Through Nuclear Reaction Rate Measurements and Isotopic Analyses of Stardust

Microscopic stardust grains, found in trace amounts in primitive meteorites, afford a unique opportunity to study stellar nucleosynthesis in the laboratory by measuring their heavy element isotopic compositions. Applying LLNL’s state-of-the art material characterization capabilities to these micrometer-sized grains yields large new datasets with unprecedented precision. However, the astrophysical models necessary to interpret the isotopic record require improved nuclear physics data to constrain stellar nucleosynthesis conditions. For example, the branch point in the s-process path at 95 Zr controls the relative amounts of heavier nuclides but is poorly understood. We conducted a coordinated effort across disciplines to combine a new determination of the neutron capture cross section of 95 Zr with the laboratory analysis of hundreds of stardust grains to yield a view into stellar interiors. We developed new methods to quantify multiple isotopic systems simultaneously (e.g., Zr, Ba, and W) in stardust grains and improved the determination of the neutron capture cross section of unstable 95 Zr via the surrogate reaction method. This interdisciplinary approach is allowing us to fill gaps in our understanding of the environments in which elements are produced while enhancing LLNL’s experimental and theoretical capabilities relevant to nuclear threat reduction missions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗