Coherent Optical Signatures of Electron Microbunching in Laser-Driven Plasma Accelerators
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Overview of RENEW project that facilitates the education and mentorships of underrepresented students in isotope production research.
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This report presents multi-physics analyses of the target cooling system of the accelerator driven system (ADS) of the Kharkiv Institute of Physics and Technology (KIPT) using MCNP and Fluent computer programs. MCNP has been used to transport electrons, gammas, and neutrons, and to calculate the energy deposition in the target using a mesh-tally. The mesh-tally data have been imported in Fluent by a C subroutine that has been compiled and linked to Fluent as a user defined function. The KIPT ADS is in operation and Fluent used the CAD model from the manufacturing process of the target. The Fluent results for the reference case match very well the literature results obtained by STAR-CCM+ during the design phase. Other cases that differ from the reference one have been analyzed; in these cases, it is assumed a malfunction of the electron accelerator control or the primary water coolant pump. The target cooling system operates normally for all the analyzed cases except when the inlet water mass flow rate is decreased. If the water coolant mass flow decreases to 25%, the water maximum temperature exceeds the boiling point. However, the transient analysis showed that the target cooling system can operate for 180 seconds when the inlet water mass flow rate is decreased down by 50%.
Superconducting magnets are critical components in particle accelerators and are used to generate and sustain the large magnetic fields needed for High Energy Physics programs. One significant issue with current epoxy insulated Nb$_{3}$Sn magnets is the long training process required before stable magnet performance can be realized. It is believed that training can be significantly reduced by addressing magnet quenching through improvements in the epoxy electrical insulation. In this work, two approaches for insulation modification have been undertaken: (1) addition of thermally conductive fillers to help with quench management and (2) development of insulation resins with high strain capability at cryogenic temperatures. This paper will discuss the characterization of these insulation systems to verify their performance prior to evaluation in subscale Nb$_{3}$Sn canted cosine theta accelerator dipole magnets.
Abstract Laser-plasma accelerators (LPAs) driven by picosecond-scale, kilojoule-class lasers can generate particle beams and x-ray sources that could be utilized in experiments driven by multi-kilojoule, high-energy-density science (HEDS) drivers such as the OMEGA laser at the Laboratory for Laser Energetics (LLE) or the National Ignition Facility at Lawrence Livermore National Laboratory. This paper reports on the development of the first LPA driven by a short-pulse, kilojoule-class laser (OMEGA EP) connected to a multi-kilojoule HEDS driver (OMEGA). In experiments, electron beams were produced with electron energies greater than 200 MeV, divergences as low as 32 mrad, charge greater than 700 nC, and conversion efficiencies from laser energy to electron energy up to 11%. The electron beam charge scales with both the normalized vector potential and plasma density. These electron beams show promise as a method to generate MeV-class radiography sources and improved-flux broadband x-ray sources at HEDS drivers.
Artificial intelligence research at Fermilab plays an important role in every aspect of high-energy physics: in the operation of particle accelerators, the analysis of data captured by particle detectors, sweeping surveys of stars and galaxies, quantum simulations of physical phenomena.
Stable regions in four-dimensional phase space were observed by following the motion of accelerated proton beams subject to nonlinear forces. Here, this provides insights into the physics of dynamical systems and may lead to improved accelerator designs.
The US particle physics community planning exercise (a.k.a. “Snowmass”) is organized every 7 to 9 years to provide a forum for discussions among the entire particle physics community to develop a scientific vision for the future of particle physics in the U.S. and its international partners. The Snowmass'21 Accelerator Frontier activities include discussions on high-energy hadron and lepton colliders, high-intensity beams for neutrino research and for “Physics Beyond Colliders”, accelerator technologies, science, education and outreach as well as the progress of core accelerator technologies, including RF, magnets, targets and sources. Here we summarize the Snowmass'21 discussions on future HEP accelerator facilities.
Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field is often limited by the lack of openly available large scale datasets, as well as standardized evaluation tasks and metrics. Furthermore, the specialized knowledge and software typically required to process particle physics data pose significant barriers to interdisciplinary collaboration with the broader machine learning community. This work introduces a large, openly accessible dataset of 10 million simulated proton-proton collisions, designed to support self-supervised training of foundation models. To facilitate ease of use, the dataset is provided in a common NumPy format. In addition, it includes 70,000 labeled examples spanning three well defined downstream tasks: track finding, particle identification, and noise tagging, to enable systematic evaluation of the foundation model's adaptability. The simulated data are generated using the Pythia Monte Carlo event generator at a center of mass energy of $\sqrt{s}$ = 200 GeV and processed with Geant4 to include realistic detector conditions and signal emulation in the sPHENIX Time Projection Chamber at the Relativistic Heavy Ion Collider, located at Brookhaven National Laboratory. This dataset resource establishes a common ground for interdisciplinary research, enabling machine learning scientists and physicists alike to explore scaling behaviors, assess transferability, and accelerate progress toward foundation models in nuclear and high energy physics. The complete simulation and reconstruction chain is reproducible with the sPHENIX software stack. All data and code locations are provided under Data Accessibility.
This document provides a concise overview of a research program developed in support of the DOE Genesis Mission, illustrating how a modern semantic AI system can accelerate conceptual exploration in fundamental physics. The work summarized here accompanies three Fermilab Technical Notes that present a speculative—yet rigorously structured—framework for a pre-geometric cosmology emerging from a finite spectral substrate.
Jefferson Lab (JLab) is developing a concept to upgrade the Continuous Electron Beam Accelerator Facility (CEBAF) to additionally deliver spin-polarized continuous-wave positron beams for its nuclear physics program users (Ce+BAF 12 GeV). The concept involves repurposing the Low Energy Recirculator Facility (LERF) at JLab as a dual injector, first producing 100-300 MeV spin-polarized electron beams which are subsequently used for the generation and formation of 123 MeV continuous-wave positron beams. The positron beams are transported to CEBAF and injected for acceleration up to 12 GeV, tailored to the requirements of its four experimental halls. Given the higher emittance of the secondary positron beams, the CEBAF optics are optimized for low dispersion and low beta functions to enhance transmission within the Ce+BAF acceptance limits and with an R56 to manage the positron beams bunch length and energy spread. Potential bottlenecks are being investigated through both optical modeling and measurements using an electron beam, as well as degraded electron beams, to map the 6d acceptance of CEBAF as it is today. This presentation shares preliminary results from multi-particle tracking simulations of the positron beam up to 12 GeV, including spatial, momentum, and spin characteristics, and explores the feasibility of delivering beams simultaneously to multiple experimental halls via extraction optics.
The PHENIX experiment at the Relativistic Heavy Ion Collider has measured low-mass vector-meson (𝜔+𝜌 and 𝜙) production through the dimuon decay channel at forward rapidity (1.2 < |y| < 2.2) in 𝑝 + 𝑝 and Au + Au collisions at $\sqrt{𝑠_{𝑁𝑁}}$ = 200 GeV. The low-mass vector-meson yield and nuclear-modification factor were measured as a function of the average number of participating nucleons, ⟨𝑁 part ⟩, and the transverse momentum 𝑝 𝑇 . These results were compared with those obtained via the kaon decay channel in a similar 𝑝 𝑇 range at midrapidity. The nuclear-modification factors in both rapidity regions are consistent within the uncertainties. A comparison of the 𝜔 + 𝜌 and 𝐽/𝜓 mesons reveals that the light and heavy flavors are consistently suppressed across both 𝑝 𝑇 and ⟨𝑁 part ⟩. Finally, in contrast, the 𝜙 meson displays a nuclear-modification factor consistent with unity, suggesting strangeness enhancement in the medium formed.
Abstract Stress relaxation cracking (SRC) has been reported as a dominant failure mechanism for 347H stainless steel welds at elevated service temperatures, occurring in either the heat-affected zone (HAZ) or fusion zone (FZ). In this study, SRC susceptibility of physically simulated HAZ and cross-welded E347-347H stainless steel welds was studied using a four-step accelerated SRC test with a thermomechanical physical simulator. The stress and temperature range studied represents weld-induced residual stress at 150–600 MPa and post-weld heat treatment temperatures between 800 and 1050 °C. For all temperature conditions, the cross-welded samples failed at a lower critical stress threshold than the simulated HAZ. A finite element model of a 50.8-mm-thick single-V groove weld was used to generate the residual stress maps induced by a 40-pass welding procedure, which in combination with the experimental threshold stress map predicted potential SRC failure locations. Postmortem microstructural evaluations were performed to identify contributing characteristics to SRC. It was found that HAZ samples exhibited a combination of creep void development, secondary cracks with intergranular fracture near grain boundary carbides, and eutectic phases. FZ samples showed brittle fracture with cracks propagating along straight, non-tortuous interdendritic grain boundaries.
The McMillan electron lens will be one of the experimental implementations of nonlinear integrable lattices in the Fermilab Integrable Optics Test Accelerator (IOTA). We describe the physics of the nonlinear McMillan lens and calculate the tune dependence with amplitude from the experimental parameters. Some of the implications for the design of experiments in IOTA are discussed.
This report summarizes the work of the Computational Frontier topical group on theoretical calculations and simulation for Snowmass 2021. We discuss the challenges, potential solutions, and needs facing six diverse but related topical areas that span the subject of theoretical calculations and simulation in high energy physics (HEP): cosmic calculations, particle accelerator modeling, detector simulation, event generators, perturbative calculations, and lattice QCD (quantum chromodynamics). The challenges arise from the next generations of HEP experiments, which will include more complex instruments, provide larger data volumes, and perform more precise measurements. Calculations and simulations will need to keep up with these increased requirements. The other aspect of the challenge is the evolution of computing landscape away from general-purpose computing on CPUs and toward special-purpose accelerators and coprocessors such as GPUs and FPGAs. These newer devices can provide substantial improvements for certain categories of algorithms, at the expense of more specialized programming and memory and data access patterns.
Particle accelerators are vital tools in physics, medicine, and industry, requiring precise tuning to ensure optimal beam performance. However, real-world deviations from idealized simulations make beam tuning a time-consuming and error-prone process. In this work, we propose an explanation-driven framework for providing actionable insight into beamline operations, with a focus on the injector beamline at the Continuous Electron Beam Accelerator Facility (CEBAF). We represent beamline configurations as heterogeneous graphs, where setting nodes represent elements that human operators can actively adjust during beam tuning, and reading nodes passively provide diagnostic feedback. To identify the most influential setting nodes responsible for differences between any two beamline configurations, our approach first predicts the resulting changes in reading nodes caused by variations in settings, and then learns importance scores that capture the joint influence of multiple setting nodes. Experimental results on real-world CEBAF injector data demonstrate the framework’s ability to generate interpretable insights that can assist human operators in beamline tuning and reduce operational overhead.