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At least 127 records · Page 7

Persistent mysteries of jet engines, formation, propagation, and particle acceleration: Have they been addressed experimentally?

Here, the physics of astrophysical jets can be divided into three regimes: (i) engine and launch (ii) propagation and collimation, (iii) dissipation and particle acceleration. Since astrophysical jets comprise a huge range of scales and phenomena, practicality dictates that most studies of jets intentionally or inadvertently focus on one of these regimes, and even therein, one body of work may be simply boundary condition for another. We first discuss long standing persistent mysteries that pertain the physics of each of these regimes, independent of the method used to study them. This discussion makes contact with frontiers of plasma astrophysics more generally. While observations theory, and simulations, and have long been the main tools of the trade, what about laboratory experiments? Jet related experiments have offered controlled studies of specific principles, physical processes, and benchmarks for numerical and theoretical calculations. We discuss what has been accomplished on these fronts. Although experiments have indeed helped us to understand certain processes, proof of principle concepts, and benchmarked codes, they have yet to solved an astrophysical jet mystery on their own. A challenge is that experimental tools used for jet-related experiments so far, are typically not machines originally designed for that purpose, or designed with specific astrophysical mysteries in mind. This presents an opportunity for a different way of thinking about the development of future platforms: start with the astrophysical mystery and build an experiment to address it.

79 ASTRONOMY AND ASTROPHYSICS↗

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Potential for tensor polarized deuterons in Hall D at Jefferson lab

Hall D at Jefferson lab is an ideal place to install a polarized deuteron target which can be “tensor polarized”, allowing the separation of the spin states m = 0, ±1 or the measurement of tensor asymmetries. The bremsstrahlung photon beam with 3 - 12 GeV endpoint provides very little heating or radiation damage compared to an electron beam, allowing the target to be run in frozen spin mode. Adiabatic fast passage spin manipulations can then be used to greatly enhance the population of the m = 0 spin state of the deuteron. Coherent photoproduction of ρ mesons from deuterium is sensitive to double-scattering at high momentum transfer and in the m = 0 spin state an additional sensitivity at intermediate momentum transfer opens up. In conclusion, we propose a frozen spin target for Hall D and the measurement of ρ photoproduced coherently from the deuteron as a flagship measurement.

43 PARTICLE ACCELERATORS↗

Pursuing the Ultimate Power of Xenon Dark Matter Detectors (Annual Progress Report)

Liquid xenon-based experiments have been leading direct searches for dark matter – a cornerstone of modern cosmology and particle physics. Despite rapid improvement of experimental sensitivities in the past two decades, no definitive dark matter interactions have been observed. This project aims to expand the physics reach of existing and future xenon dark matter experiments, especially for low-mass dark matter interactions that would fall below the energy thresholds of current detectors. The main approach is to thoroughly characterize and to suppress the low-energy electron background observed in dual-phase xenon Time Projection Chambers (TPCs), which has so far prevented these detectors from achieving lower energy thresholds. Per recent discussion with and approval from the program manager, we have added a new task of experimentally measuring the Migdal effect to this project. The Migdal effect predicts that ultra-low energy dark matter interactions may produce detectable electron recoil signals in liquid xenon at the keV level in addition to much lower energy nuclear recoils. If this effect is experimentally measured, it will drastically improve xenon detectors’ sensitivity to subGeV dark matter interactions. This new task shares strong synergy with the original project goal of pursuing the ultimate power of xenon dark matter experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Model emulation and closure tests for (3+1)D relativistic heavy-ion collisions

In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated in heavy ion collisions. However, computational demands pose challenges, motivating using Gaussian Process emulators for efficient parameter extraction via Bayesian calibration. We conduct a comparative analysis of Gaussian Process emulators in heavy-ion physics to identify the most adept emulator for parameter extraction with minimal uncertainty. Furthermore, our study contributes to advancing computational techniques in heavy-ion physics, enhancing our ability to interpret experimental data and understand QGP properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hopf Solitons in Helical and Conical Backgrounds of Chiral Magnetic Solids

Three-dimensional topological solitons attract a great deal of interest in fields ranging from particle physics to cosmology, but remain experimentally elusive in solid-state magnets. Here we numerically predict magnetic heliknotons, an embodiment of such nonzero-Hopf-index solitons localized in all spatial dimensions while embedded in a helical or conical background of chiral magnets. In this work we describe conditions under which heliknotons emerge as metastable or ground-state localized nonsingular structures with fascinating knots of magnetization field in widely studied materials. We demonstrate magnetic control of three-dimensional spatial positions of such solitons, as well as show how they interact to form moleculelike clusters and possibly even crystalline phases comprising three-dimensional lattices of such solitons with both orientational and positional order. Finally, we discuss both fundamental importance and potential technological utility of magnetic heliknotons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Particle Theory and Cosmology

This project covered theoretical studies in particle physics, particle astrophysics and cosmology, aiming to bridge theoretical models with observable phenomena. The central focus was on exploring innovative mechanisms that could simultaneously address several outstanding puzzles in these areas, including the nature of dark matter, the muon g-2 anomaly, the existence of topologically stable monopoles, the generation of observable gravitational waves from early universe phenomena and high energy cosmic rays. One of the major achievements of this project was the development of models that predict new physics accessible through current and forthcoming experimental setups, both in particle colliders and astrophysical observations. These models have been instrumental in proposing verifiable predictions concerning supersymmetric extensions, the dynamics of cosmic strings and monopoles, and the intricate processes underpinning baryogenesis and reheating post-inflation. In tackling the dark matter conundrum, the project proposed several candidates within extended frameworks, such as light Z' models, pseudo-Goldstone dark matter, and scenarios integrating dark matter with inflationary cosmology. Each model outlined pathways for detection through direct, indirect, and collider search strategies, marking significant strides in the hunt for dark matter. Another cornerstone of the project was the in-depth analysis of inflationary models compliant with the Trans-Planckian Censorship Conjecture, highlighting the compatibility of axion dark matter within such frameworks. This not only provided a coherent picture of early universe cosmology but also delineated clear experimental signatures. The exploration of grand unified theories yielded insights into the potential discovery of monopoles and novel particle configurations at energy scales accessible to current and future colliders. This endeavor expanded the predictive power of these theories, particularly in the context of proton decay and the properties of Higgs-portal dark matter. Throughout the project, significant emphasis was placed on ensuring the theoretical developments were grounded in experimental testability. This led to a series of publications across prestigious journals, each contributing to the vibrant discourse at the intersection of particle physics and cosmology. In summary, this project has elucidated pathways beyond the Standard Model that are ripe for exploration through both ongoing and upcoming experimental efforts. The comprehensive approach adopted herein not only enhances our understanding of the fundamental forces and constituents of the universe but also propels the field towards new frontiers in high-energy physics and cosmology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental impact of jet fragmentation reference frames at particle colliders

In collider physics, the properties of hadronic jets are often measured as a function of their lab-frame momenta. However, jet fragmentation must occur in a particular rest frame defined by all color-connected particles. Since this frame may not be the lab frame, the fragmentation of a jet depends on the properties of its sibling objects. This non-factorizability of jets has consequences for experimental jet techniques such as jet tagging, boosted boson measurements, and searches for physics Beyond the Standard Model. In this paper, we will describe the effect and show its impact as predicted by simulation.

Fragmentation into hadrons↗

Celeritas: GPU-accelerated particle transport for detector simulation in High Energy Physics experiments

Within the next decade, experimental High Energy Physics (HEP) will enter a new era of scientific discovery through a set of targeted programs recommended by the Particle Physics Project Prioritization Panel (P5), including the upcoming High Luminosity Large Hadron Collider (LHC) HL-LHC upgrade and the Deep Underground Neutrino Experiment (DUNE). These efforts in the Energy and Intensity Frontiers will require an unprecedented amount of computational capacity on many fronts including Monte Carlo (MC) detector simulation. In order to alleviate this impending computational bottleneck, the Celeritas MC particle transport code is designed to leverage the new generation of heterogeneous computer architectures, including the exascale computing power of U.S. Department of Energy (DOE) Leadership Computing Facilities (LCFs), to model targeted HEP detector problems at the full fidelity of Geant4. This paper presents the planned roadmap for Celeritas, including its proposed code architecture, physics capabilities, and strategies for integrating it with existing and future experimental HEP computing workflows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New electric force and charge exchange modules in discrete element model enables particle dynamics simulation in electric field

Discrete element modeling (DEM) is an important technique for particle dynamics simulation. The field of metal additive manufacturing often utilizes DEM to simulate the rheological behaviors of powder. Standard contact and short-range interactions are sufficient in most cases but insufficient to describe the particle dynamics with the influence of an electric field. Modeling such a system requires additional physics to describe the particle–field interactions. The relevant physics has been experimentally understood but is not yet available in DEM. Here, we develop a charge exchange and an electric force module. The electric force module governs particle response to the electric field, while the charge exchange module enables particles to acquire proper charge during contact with charged geometries. We validate the modules against analytical calculations and high-speed videos of electrostatic powder deposition experiments. Notably, the model struggles to capture the initial particle levitation. We later deploy a modified electric field, as supported by static electric field simulation, to better approximate the electric field penetration into the powder layer. This modification improves the model’s capability of simulating realistic particle levitation. The results highlight the challenges of modeling particle behaviors in the electric field while demonstrating the feasibility of obtaining quantitative results, which are difficult to measure experimentally.

charge exchange↗

A novel closed-form inversion of the convection–diffusion equation for rapid convection, diffusion, and source profile estimation

To simplify and routinize particle transport analysis in fusion devices, a novel closed form linear inversion of the 1-D convection diffusion equation to estimate diffusion and convection profiles D(r ⃗ ), v(r ⃗ ) and source distribution s(r ⃗ ), of a single species from measured data is derived and demonstrated on synthetic data. Profile estimates of D(r ⃗ ), v(r ⃗ ), s(r ⃗ ) and their uncertainties are given as a matrix expression constructed directly from the incoming density data of the transported species in space and time, as well as physics assumptions such as particle conservation and experimental geometry. The derived matrix expression can be applied to a pumped or non-pumped recycling species, or a non-recycling species that is effectively “pumped” by plasma-facing surfaces.

Hinson, Edward [ORNL] (ORCID:000000019713140X)↗

Multiparticle-hole excitations in nuclei near N = Z = 20: $^{41}$K

This experimental study of high-spin structure near the N = Z = 20 region focuses on 41 K and also reports three newly observed γ transitions in 41 Ca from the same reaction. High-spin states were populated using the 26 Mg( 18 O, p2nγ) 41 K and 26 Mg( 18 O, 3nγ) 41 Ca reactions at a beam energy of 50 MeV at the Florida State University John D. Fox Superconducting Linear Accelerator Laboratory, employing the FSU high-purity germanium detector array. The level scheme of 41 K was extended to 12325 keV, possibly up to J π = 25/2 − or 27/2 + , by means of 25 new γ-ray transitions, and that of 41 Ca to 9916 keV. Linear polarization and angular-distribution measurements were used to provide spin and parity information for several states in the 41 K decay scheme. The results are compared with spsdpf cross-shell shell-model calculations using the FSU interaction. Configurations involving zero or one nucleon promoted from the sd to the fp shell reproduce the energies of many known states reasonably well, while multi-particle excitations reveal a more complex interplay of single-particle motion, collective pairing, and deformation, posing an interesting challenge for future theoretical work.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pedestal main ion particle transport inference through gas puff modulation with experimental source measurements

Abstract Transport in the DIII-D high confinement mode (H-mode) pedestal is investigated through a periodic edge gas puff modulation (GPM) which perturbs the deuterium density and source profiles. By using absolutely calibrated experimental edge ionization profile measurements, radial profiles of diffusion ( D ) and convection ( v ) are calculated into the pedestal region without depending on modeling the edge ionization source. An analytic approach with closed-form expressions for the D and v profiles and a more advanced Bayesian approach show evidence of an inward particle convection on the order of 1 m s −1 extending to normalized poloidal flux ( Ψ N ) of 0.98. Meanwhile, diffusion reaches a minimum value of ( 0.03 ± 0.02 ) m 2 s −1 in the pedestal region. Notably, the Bayesian approach, which utilizes the Aurora 1.5 D forward model inside the IMPRAD OMFIT module, provides radially resolved transport profiles with associated uncertainty without requiring an explicit form for the perturbation to the density profile or source. The combination of experimental ionization measurements and Bayesian inference provides an enhanced robust framework for investigating edge particle transport coefficients to experimentally test transport physics in order to improve predictive capabilities in the tokamak edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Beam Dump eXperiment

Hadronic matter makes about 14% of the known universe. The remaining 86% is Dark Matter (DM). Since it does not interact with the ordinary matter via electromagnetic force, DM is not visible and, to date, it escaped detection. The search for Dark Matter (DM) is one of the hottest topic in modern physics. Despite the increasing number of astrophysical and cosmological observations proving the existence, so far no particle physics experiment has detected DM yet. Up to now, most of the experimental efforts have been focused on the so called WIMP (Weakly Interacting Massive Particle) paradigm, which predicts heavy DM (10 GeV-10 TeV mass range) interacting with Standard Model (SM) particles via the weak force mediators (W or Z bosons). More recently, due to the lack of clear evidence of WIMPs, other models of DM gained the interest of the physics community. These models consider Light DM particles (LDM), in MeV-GeV mass range. Among LDM theories, the Dark Photon theory predicts the existence of a Dark Sector interacting with SM particles via a new massive vector boson (Dark Photon, Heavy Photon or A0), mediator of a new force. This scenario, despite being theoretically well motivated, is remarkably experimentally unexplored. The Beam Dump eXperiment (BDX), is an approved experiment at Jefferson Lab (JLab), aiming to discover the DM predicted witihn the Dark Photon theory. The experiment uses the CEBAF (Continuous Electron Beam Accelerator Facility) 11 GeV electron beam, impinging on the JLab Hall-A beam-dump, to produce a beam of DM particles, detected by a ~ 1 m3 detector made of thallium doped cesium iodide (CsI(Tl)) crystals located ~ 20 m downstream. In order to achieve excellent background rejection, the experimental setup includes active vetos and passive shielding surrounding CsI(Tl) crystals. Given the weakness of the DM-SM interaction, the scattering of a DM particle in the BDX detector is a rare event. Therefore, the characterization of the expected background is a critical aspect of the experiment. Both cosmogenic and penetrating SM particles produced by the beam interaction in the dump contribute to the background of the experiment. While the cosmogenic contribution can be measured during the experiment when the beam is off, beam-related background can only be estimated via Monte Carlo (MC) simulations. Therefore, a careful assessment of possible systematics introduced by the MC is needed. The beam-correlated background characterization was made by measuring the muon flux produced by the interaction of the CEBAF beam with Hall-A dump in a dedicated experimental campaign in spring 2018 [1]. The comparison to the ?ux predicted by MC allowed us to validate the BDX simulation framework. The reach of BDX, i.e. the region that the experiment can probe in the LDM theory parameter space, depends critically on the background rejection capability and signal detection effciency. For this reason, the detector setup was fine-tuned through a dedicated study. The response to LDM and background events was evaluated for different setups and selection cuts. As a result of this procedure, the configuration resulting in the best sensitivity was selected [2]. The reach calculation was performed taking into account the different LDM production mechanisms, including the contribution of secondary particles produced in the beam-dump. In particular, the effect of the secondary positrons annihilation was found to be extremely significant. In the majority of the sensitivity studies, this contribution is neglected, but recent results [3] [4] demonstrated that this process significantly enhances the sensitivity of lepton beam-dump experiments. Currently, the BDX collaboration is focused on the deployment and operation of a small detector, called BDX-MINI, built to perform a preliminary physics measurement searching for LDM at JLab. This test will pave the way to the realization of the full BDX experiment. The measurement is currently ongoing but results are expected by the end of this year. During my PhD I was involved in all aspects of the BDX experiment: design, simulation, prototyping and data analysis. The main results of my work are reported in this thesis. This manuscript is organized as follows: the first Chapter provides an introduction to the theory of LDM, with particular attention to the Dark Photon paradigm; the second Chapter illustrates the BDX experimental setup, the LDM production and detection mechanisms and the expected backgrounds; Chapter 3 and 4 describe, respectively, the BDX-HODO measurement, with a detailed description of the simulations, and the BDX experimental setup and analysis cuts optimization. Chapter 5 reports about BDXMINI detector characterization, calibration and sensitivity estimate. Finally, Chapter 6 describes in detail the calculation of the secondary positron annihilation contribution to the sensitivity of BDX and other electron-beam thick-target experiment.

Marsicano, Luca↗

SUSY 2025 at UC Santa Cruz (Final Technical Report)

The 32nd International Conference on Supersymmetry and the Unification of Fundamental Interactions (SUSY 2025) took place from August 18--23, 2025. During the week preceding the SUSY 2025 conference, the associated pre-SUSY school took place from August 11--15, 2025. Both events were organized and hosted by the Santa Cruz Institute for Particle Physics at the University of California, Santa Cruz. The SUSY 2025 conference brought together theorists and experimentalists specializing in particle physics, astroparticle physics, cosmology, mathematical physics, and string theory to discuss recent developments in these areas, with a focus on theoretical aspects and experimental searches associated with phenomena that lie beyond the Standard Model of particle physics and the standard mathematical framework of modern cosmology. The pre-SUSY school provided advanced pedagogical lectures for graduate students and early-career postdoctoral researchers on many of the foundational topics that were subsequently addressed in the main SUSY 2025 conference that followed. DOE support helped increase accessibility for early-career scientists by covering conference support costs that enabled free participation in the pre-SUSY school and substantially reduced registration fees for students attending the conference.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Publishing statistical models: Getting the most out of particle physics experiments

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗