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Overview of the New Beam Physics Research at the IOTA/FAST Facility

The Fermilab Accelerator Science and Technology (FAST) facility is dedicated to the exploration of novel concepts in accelerator and beam physics, and the development of a robust workforce, in order to enable and enhance next-generation particle accelerators. FAST comprises a high-brightness superconducting electron linac, and a storage ring, the Integrable Optics Test Accelerator (IOTA). Experiments in the most recent operational run include studies of nonlinear integrable lattices; tracking of single electrons; precise characterization of undulator radiation; studies with low-momentum-compaction lattices; and ultra-wide range beam diagnostics based on Photomultiplier tubes. In the linac, experiments on noise in intense electron bunches were conducted. The IOTA proton injector, currently being commissioned, will enable a diverse program on space-charge-dominated beams. Research areas include non-invasive beam profile monitoring for proton beams; beam dynamics with electron lenses; halo suppression, feedback systems, and electron cooling. In this presentation, we provide an overview of the recent results and highlight future plans together with opportunities for collaboration.

43 PARTICLE ACCELERATORS

Equivariant, safe and sensitive — graph networks for new physics

This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integrating equivariance in the rapidity-azimuth plane with IRC-safe principles, our model significantly reduces computational overhead while ensuring theoretical consistency in identifying BSM scenarios amidst Quantum Chromodynamics backgrounds. The proposed GNN architecture demonstrates superior performance in tagging semi-visible jets, highlighting its potential as a robust tool for advancing BSM search strategies at high-energy colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

PAIReD jet: A multi-pronged resonance tagging strategy across all Lorentz boosts

We propose a new approach of jet-based event reconstruction that aims to optimally exploit correlations between the products of a hadronic multi-pronged decay across all Lorentz boost regimes. The new approach utilizes clustered small-radius jets as seeds to define unconventional jets, referred to as PAIReD jets. The constituents of these jets are subsequently used as inputs to machine learning-based algorithms to identify the flavor content of the jet. We demonstrate that this approach achieves higher efficiencies in the reconstruction of signal events containing heavy-flavor jets compared to other event reconstruction strategies at all Lorentz boost regimes. Classifiers trained on PAIReD jets also have significantly better background rejections compared to those based on traditional event reconstruction approaches using small-radius jets at low Lorentz boost regimes. The combined effect of a higher signal reconstruction efficiency and better classification performance results in a two to four times stronger rejection of light-flavor jets compared to conventional strategies at low Lorentz-boosts, and rejection rates similar to classifiers based on large-radius multi-pronged jets at high Lorentz-boost regimes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

JuTrack: A Julia package for auto-differentiable accelerator modeling and particle tracking

Efficient accelerator modeling and particle tracking are key for the design and configuration of modern particle accelerators. In this work, we present JuTrack, a nested accelerator modeling package developed in the Julia programming language and enhanced with compiler-level automatic differentiation (AD). With the aid of AD, JuTrack enables rapid derivative calculations in accelerator modeling, facilitating sensitivity analyses and optimization tasks. Here we demonstrate the effectiveness of AD-derived derivatives through several practical applications, including sensitivity analysis of space-charge-induced emittance growth, nonlinear beam dynamics analysis for a synchrotron light source, and lattice parameter tuning of the future Electron-Ion Collider (EIC). Through the incorporation of automatic differentiation, this package opens up new possibilities for accelerator physicists in beam physics studies and accelerator design optimization.

43 PARTICLE ACCELERATORS

Measurement of groomed event shape observables in deep-inelastic electron-proton scattering at HERA

The H1 Collaboration at HERA reports the first measurement of groomed event shape observables in deep inelastic electron-proton scattering (DIS) at $\sqrt{s} =319$ GeV, using data recorded between the years 2003 and 2007 with an integrated luminosity of 351 pb -1 . Event shapes provide incisive probes of perturbative and non-perturbative QCD. Grooming techniques have been used for jet measurements in hadronic collisions; this paper presents the first application of grooming to DIS data. The analysis is carried out in the Breit frame, utilizing the novel Centauro jet clustering algorithm that is designed for DIS event topologies. Events are required to have squared momentum-transfer $Q^2 > 150$ GeV 2 and inelasticity $0.2< y < 0.7$. We report measurements of the production cross section of groomed event 1-jettiness and groomed invariant mass for several choices of grooming parameter. Monte Carlo model calculations and analytic calculations based on Soft Collinear Effective Theory are compared to the measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Search for hadronic decays of feebly-interacting particles at NA62

The NA62 experiment at CERN has the capability to collect data in a beam-dump mode, where 400 GeV protons are dumped on an absorber. In this configuration, New Physics particles, including dark photons, dark scalars, and axion-like particles, may be produced in the absorber and decay in the instrumented volume beginning approximately 80 m downstream of the dump. A search for these particles decaying in flight to hadronic final states is reported, based on an analysis of a sample of 1.4 x 10 17 protons on dump collected in 2021. No evidence of a New Physics signal is observed, excluding new regions of parameter spaces of multiple models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,

An extraction scheme for future CEBAF FFA based energy upgrade

Jefferson lab is considering an energy increase from current 12 GeV to 22 GeV for its CEBAF accelerator. This will be accomplished by recirculating 5-6 additional turns through two parallel CEBAF LINACs using an FFA arc at each end of the racetrack. The total recirculation turns would be 10 times, the first four turns use present conventional arcs to make the 180-degree bends from one LINAC to the other. However, the last 5-6 turns will all share a single beam line inside two FFA arcs. This reduces the footprint and the cost of the project significantly. On the other hand, having the trajectories of last 5-6 recirculating beams close to each other makes it challenging to extract beams from different passes with different energies. In this paper we will explain our present extraction system for 12 GeV, our challenges and limitations, and a possible extraction solution for the 22 GeV upgrade with the goal of extracting beam at different turns/energies to different experimental halls.

Accelerator Physics

Design of a microbunched electron cooler energy recovery linac

Microbunched electron Cooling (MBEC), a type of Coherent electron Cooling (CeC), is a possible way to cool high energy protons; such an electron cooler can be driven by an energy recovery linac (ERL). The beam parameters of this design are based on cooling 275 and 100 GeV protons at the Electron-Ion Collider (EIC), requiring 150 and 55 MeV electrons, respectively. If implemented, a high energy cooler would serve to increase the average luminosity of the collider by mitigating the emittance growth caused by various processes. This ERL is designed to deliver a bunch charge of 1 nC, an average current of 100 mA, and strict requirements on the transverse emittance, slice energy spread, and longitudinal distribution profile. This paper covers the current state of the design.

Accelerator Physics

Multi-GeV FFA beam transport test at CEBAF

Jefferson National Lab plans an upgrade project to reach 22 GeV high polarization electron beam by using Fixed Field Alternating-gradient (FFA) magnets. The utilization of the FFA magnets for 10-22 GeV beam energy range is unexampled, therefore those magnets need an experimental validation before their full installation to form an arc in the Continuous Electron Beam Accelerator Facility (CEBAF). For this reason, JLAB is also considering the design of an FFA magnet test bench, i.e. a half or full FFA cell, that would be deployed in the current CEBAF in order to serve as the highest energy demonstration for the FFA field uniformity, permanent magnet resiliency with the beam as well as enabling beam optics measurements with the 5-11 GeV range highly polarized beams which closely resembles the full energy range of the 22 GeV upgrade. In this report, we present the status of the planned beamline for the FFA beam transport test at CEBAF.

Accelerator Physics

Simulations of positron injector for Ce+BAF

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. This concept is based on the generation of CW longitudinally polarized positrons by a high-current, polarized electron beam (1 mA, 130‑370 MeV, and 90% longitudinal polarization) that passes through a rotating, water-cooled, tungsten target. The simulation results for the Ce+BAF injector at the Low Energy Recirculator Facility (LERF) are presented, including positron beam generation, capture, energy selection, and acceleration to 123 MeV. The positron yield (or positron current) and longitudinal polarization are calculated considering the longitudinal and transverse CEBAF acceptances (<1% energy spread, <1 mm bunch length and normalized emittance of <100 mm mrad). The impact of target thickness, drive electron beam energy, and transverse size on positron yield within the required emittance limit is evaluated.

Accelerator Physics

Second-stage acceleration in a limb-occulted flare

From radio observations it is known that two distinct groups of phenomena occur in large solar flares. The phenomena are related to an impulsive phase of approximately 100 s duration in the early stage of a flare and a following second phase lasting for tens of minutes. A study is presented of the limb-occulted flare event of July 22, 1972, giving particular attention to the second stage particle acceleration. The study takes into account hard X-ray, energetic particle, and radio observations. The conducted analysis shows that second stage acceleration is physically distinct from the impulsive phase, and is characterized by continuous and widespread electron acceleration to high energies, most likely by the type II burst shock wave.

Hudson, H. S.

EUV FEL light source based on energy recovery linac with on-orbit laser plasma injection

We report on a week-long study of a conceptual design of EUV FEL light source based on an energy recovery linac with on-orbit laser plasma accelerator injection scheme. We carried out this study during USPAS Summer 2023 session of Unifying Physics of Accelerators, Lasers and Plasma applying the art of inventiveness TRIZ. An ultrashort Ti-sapphire laser accelerates electron beams from a gas target with mean energy of 20 MeV, which are then ramped up to 1 GeV in a five-turn scheme with a series of fixed field alternating magnets and two superconducting RF cavities (100 MeV per cavity per turn). The electron beam is then bypassed to an undulator line optimized to generate EUV light of 13.5 nm at kW level in a single pass.

43 PARTICLE ACCELERATORS

Frequency dependence of BCS and residual resistance using multi-mode measurement of nitrogen-doped single-cell elliptical cavities

Various cavity surface treatments have been found to significantly improve cavity quality factor, Q0, with one such treatment being nitrogen-doping (N-doping). N-doped 1.3 GHz cavities were the first found to exhibit anti-Q slope, the increase of Q0 with accelerating field, Eacc. However, even with the use of the same N-doping recipes, this anti-Q slope behavior has not been realized in sub-GHz frequency cavities. In this study, we measured the Q0 and surface resistance, RS, of our N-doped, single-cell, elliptical cavity for both the 644 MHz fundamental mode (FM) and 1.45 GHz higher-order mode (HOM). As a result of multi-mode measurements, the BCS and residual resistances, the temperature-dependent and temperature-in-dependent RF surface resistances, could be determined without the influence of cavity-to-cavity surface treatment variations. We will discuss the frequency-dependent behaviors of the BCS and residual resistances.

Accelerator Physics

Plasma processing of SRF cavities at Jefferson Lab: Experiment results and simulation insight

Plasma processing of superconducting radio frequency (SRF) cavities has been an active research effort at Jefferson Lab (JLab) since 2019, aimed at enhancing cavity performance by removing hydrocarbon contaminants and reducing field emission. In this experiment, processing using argon-oxygen and helium-oxygen gas mixtures to find minimum ignition power at different cavity pressure was investigated. Ongoing simulations are contributing to a better understanding of the plasma surface interactions and the fundamental physics behind the process. These simulations, combined with experimental studies, guide the optimization of key parameters such as gas type, RF power, and pressure to ignite plasma using selected higher-order mode (HOM) frequencies. This paper presents experimental data from argon-oxygen and helium-oxygen gas mixture C75 and C100 cavity plasma ignition studies, as well as simulation results for the C100-type cavity based on the COMSOL model previously applied to the C75 cavity.

Accelerator Physics

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability

Fermilab Phoebus

The Fermilab Phoebus code contains FNAL site-specific code to customize the Control Systems Studio Phoebus application. Phoebus is a tool used to create and present graphical displays based on current real-time and historic values of sensors, gauges, alarms, and many other devices in accelerators and physics experiments here and at other laboratories around the world.

Velarde, Mariana González [Fermi National Accelera

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.

Lee, Jonathan E. [Department of Chemical and Envir