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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Compact Coaxial HOM Damper for SRF Cavities

SRF technology enable particle accelerators operate with greater average beam currents and higher duty cycles. In these regimes parasitic excitation of the cavity HOM spectrum become the limiting factor due to extra RF losses and instabilities appearing in the beam. We discuss the limitations of HOMs for large accelerator projects as the Fermilab MI upgrade and the proposed future circular and linear colliders EIC and ILC. A new compact HOM damper concept is suggested providing required HOM suppression. The idea is based on an oversized coaxial line with radial sections, which is directly connected to the axial region of the SRF cavity. Such radially sectioned coaxial works as a filter for the operating mode, while being transparent for the HOMs. Implementations of this design for the accelerator and crab cavities developed for the MI and EIC machines, respectively, are discussed.

Lunin, A. [Fermilab]↗
DOE OSTI2023

A Simplified Method to Evaluate Energy Life Cycle Cost Effectiveness for Electron Ion Collider Infrastructure Design

The new DOE Order 436.1A approved on April 25 th provides instructions to incorporate principles of sustainability early in the project planning and design process. Integral to the principles of sustainability is life cycle cost effectiveness Life Cycle Cost (LCC) Analysis is vital to the sustainable energy efficient design and construction of the Electron Ion Collider (EIC). Reducing energy consumption has a direct impact on reducing life cycle operating costs with benefits to the environment. The early stages of the project are the most influential where design decisions and so life-cycle considerations during this stage can result in significant impacts to the energy footprint of the design. For example, when comparing between various options, it is necessary to compare the energy savings in $\frac{US$}{kWh}$ to the capital cost in US$. And although uncertain by nature, it is important to factor in the expected inflation and discount of future spendings to compare with the cost of immediate capital investment. This tech note presents a tool that engineers can readily use to analyze energy operating costs using an incremental life cycle cost method when comparing different design alternative.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

EIC-related Generic Detector R&D Program

This program will support advanced R&D on innovative, cost-effective detector concepts which reduce risk and that either the one detector in the project scope or a second detector could incorporate. (The term "generic" conveys this duality.) The program is supported through R&D funds provided to Jefferson Lab by the DOE Office of Nuclear Physics, and is open to all segments of the EIC community. It is expected to be funded at an annual level of $2M, subject to availability of funds from DOE NP.

Mack, David↗
DOE OSTI2020

Neutral Pion Electroproduction and development of a Neutral Particle Spectrometer

Protons and neutrons, i.e. nucleons, are the basic building blocks of the matter in the visible universe. The strong force binds the nucleons to form nuclei. The electromagnetic force forms the atoms by binding the electrons with the nuclei. The electromagnetic interaction is well understood by Quantum Electrodynamics (QED), which shows the most precise predictability amongst all the theories in physics. In QED, charges interact with each other by exchanging photons. The Quantum Chromodynamics (QCD) describes the strong interaction. Its degrees of freedom are quarks and gluons, the fundamental constituents of the nucleons. The quarks interact with each other by exchanging gluons. However, unlike QED, the gluons interact amongst themselves. This feature of self bindings of the gluons confines the quarks and gluons in the nucleons/hadrons, never to be seen as free. In order to study some of the features of QCD, such as confinement or the structure of the nucleon, one usually needs to rely on experiments. Electromagnetic probes, governed by the well-understood QED, are excellent tools to probe the nucleon. In general, different scales, e.g. electron beam energies, probe different regions of the nucleon. At low energy, of the order of a few GeV, the electron probes the nucleon in the valence quark region. As its energy increases, the electron probes the sea quark and gluon regions. The study of the nucleon structure in all these regions is needed to fully understand QCD. Form factors and parton distribution functions measured from elastic scattering and deep inelastic scattering of leptons off nucleons have provided a partial view of the internal structure of the nucleon. In the mid-1990s, Generalized Parton Distributions (GPDs) were developed. These new objects are a generalization of the form factors and parton distribution functions, but contain richer information on the nucleon internal structure. GPDs are accessible experimentally by deep exclusive reactions. Deeply virtual Compton scattering (DVCS) and deeply virtual meson production (DVMP) are some examples. The first dedicated DVCS/DVMP experiment took place in 2004 in Hall A at The Thomas Jefferson National Accelerator Facility, i.e. Jefferson Lab, in Virginia, U.S.A. A new DVCS/DVMP experiment, after the beam energy upgrade of Jefferson Lab, was carried out in Hall A in a wider kinematic range. Its data were taken from 2014 to 2016. In Hall C at Jefferson Lab, the next DVCS/DVMP experiment will take place. The Hall C experiment will further exploit the kinematic range with higher precision. A Neutral Particle Spectrometer (NPS) is in development to measure DVCS/DVMP events under high background conditions. Jefferson Lab will provide the highest precision data in the valence quark region for various exclusive reactions. The Electron-Ion Collider (EIC) is a future experimental facility currently planned to start operations around 2030 in the U.S.A. Its high energy and high luminosity will probe the sea quark and gluon regions providing answers to the outstanding questions of QCD, in particular in the region where matter is dominated by gluons. First of all, this document describes the data analysis and results of the Hall A neutral pion electroproduction off the proton, from the data taken in 2014-2016. Later, some of the developments towards the construction of the electromagnetic calorimeter of the NPS for the upcoming DVCS/DVMP experiment in Hall C are presented. Finally, one of the candidate materials for the EIC calorimeter, a glass scintillator, will be briefly introduced. I have participated to all these projects, in collaboration with many colleagues. I present in this thesis my contributions to each of these projects. My contributions to the neutral pion data analysis were focused on background subtractions on the calorimeter, acceptance calculations, and the estimation of the systematic uncertainty associated to the event selection cuts. Some necessary information on calibrations of the detectors and data analysis methods are also described. In the NPS project, I performed background dose calculations and energy and position resolution studies of the calorimeter, all using Monte Carlo simulations, with realistic geometries of the experimental apparatus. Characterization of the crystals of the calorimeter was also done. Additionally, I measured the radiation hardness of some glass scintillator in its early stage of development. In order to have a future reference when the glass calorimeter prototype will be tested, I simulated the energy resolution of the prototype.

Ko, Ho-San↗
DOE OSTI2023

Detector requirements and simulation results for the EIC exclusive, diffractive and tagging physics program using the ECCE detector concept

This article presents a collection of simulation studies using the ECCE detector concept in the context of the EIC’s exclusive, diffractive, and tagging physics program, which aims to further explore the rich quark–gluon structure of nucleons and nuclei. To successfully execute the program, ECCE proposed to utilize the detector system close to the beamline to ensure exclusivity and tag ion beam/fragments for a particular reaction of interest. Preliminary studies confirm the proposed technology and design satisfy the requirements. Further, the projected physics impact results are based on the projected detector performance from the simulation at 10 or 100 fb -1 of integrated luminosity. Additionally, insights related to a potential second EIC detector are documented, which could serve as a guidepost for future development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Near-infrared noise in intense electron beams

Requirements for the noise in electron beams (NEB) have recently approached the Shot-noise level in some new applications. The density fluctuations of intense beams in the near-infrared (NIR) region are being measured at the Fermilab Accelerator Science and Technology (FAST) facility. The main goal of the experiment is to accurately compare the Shot-noise model with the observations of optical transition radiation (OTR) generated by the gamma=63 electron beam transiting an Al metal surface. In addition, evidence for longitudinal-space-charge-induced microbunching for the chicane-compressed beam was obtained with coherent enhancements up to 100 in the various bandwidth-filtered NIR OTR photodiode signals. With micropulse charges up to 1 nC, the beam parameters are close to those proposed for a stage in an Electron-Ion Collider (EIC) with coherent electron cooling (CEC). In this paper we present the current progress of the NEB project and compare the low electron energy measurements with ImpactX simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Near-Infrared Noise in Intense Electron Beams

Requirements for the noise in electron beams (NEB) have recently approached the Shot-noise level in some new applications. The density fluctuations of intense beams in the near-infrared (NIR) region are being measured at the Fermilab Accelerator Science and Technology (FAST) facility. The main goal of the experiment is to accurately compare the Shot-noise model with the observations of optical transition radiation (OTR) generated by a relativistic electron beam ($\gamma \approx 63$), transiting an Aluminium metal surface. In addition, some evidence for longitudinal space-charge-induced microbunching for the chicane-compressed beam was obtained with coherent enhancements up to 100 in the various bandwidth-filtered NIR OTR photodiode signals. With micropulse charges up to 1 nC, the beam parameters are close to those proposed for a stage in an Electron-Ion Collider (EIC) with coherent electron cooling (CEC). In this paper we present the current progress of the NEB project and compare the low electron energy measurements with ImpactX simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

EIC Detector Overview

The Electron Ion Collider will have two interaction regions that can be instrumented with detectors. Here, the first region will be instrumented as part of the project and needs to be capable of delivering the physics that has been outlined by the National Academy of Sciences and ready at the start of beam commissioning near the end of this decade. Plans for a second complementary detector to be located at a second interaction region are already in progress and will hopefully come to fruition just few years after the first detector comes online. While the basic parameters of these detectors are being selected using conventional approaches, the optimization of the detectors is already being enhanced by making use of advanced optimization techniques.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Towards a RAG-based summarization for the Electron Ion Collider

Abstract The complexity and sheer volume of information — encompassing documents, papers, data, and other resources — from large-scale experiments demand significant time and effort to navigate, making the task of accessing and utilizing these varied forms of information daunting, particularly for new collaborators and early-career scientists.To tackle this issue, a Retrieval Augmented Generation (RAG)-based Summarization AI for EIC (RAGS4EIC) is under development. This AI-Agent not only condenses information but also effectively references relevant responses, offering substantial advantages for collaborators. Our project involves a two-step approach: first, querying a comprehensive vector database containing all pertinent experiment information; second, utilizing a Large Language Model (LLM) to generate concise summaries enriched with citations based on user queries and retrieved data. We describe the evaluation methods that use RAG assessments (RAGAs) scoring mechanisms to assess the effectiveness of responses. Furthermore, we describe the concept of prompt template based instruction-tuning which provides flexibility and accuracy in summarization. Importantly, the implementation relies on LangChain [1], which serves as the foundation of our entire workflow. This integration ensures efficiency and scalability, facilitating smooth deployment and accessibility for various user groups within the Electron Ion Collider (EIC) community. This innovative AI-driven framework not only simplifies the understanding of vast datasets but also encourages collaborative participation, thereby empowering researchers. As a demonstration, a web application has been developed to explain each stage of the RAG Agent development in detail. The application can be accessed athttps://rags4eic-ai4eic.streamlit.app.[A tagged version of the source code can be found inhttps://github.com/ai4eic/EIC-RAG-Project/releases/tag/AI4EIC2023_PROCEEDING.]

Instruments & Instrumentation↗
DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A numerical evaluation of the ambient air temperature in the Electron-Ion Collider tunnel

The Electron-Ion Collider (EIC) is a next-generation collider-accelerator that may require consistent operating temperature conditions for the beams within the accelerator tunnels to maintain stable operation. Variations in ambient temperature within the tunnel can cause thermal expansion of beampipe and component supports and can negatively affect the tunnel equipment, impacting the stability of the beamline. Modifications will be made to the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) to create the EIC, which necessitates a temperature model that addresses these modifications. To approach this problem, the consistency of temperature changes in different tunnel sections was first evaluated by plotting RHIC tunnel temperature data at various times of the day and year. From this data, a tunnel section was selected and a 2D temperature model was created for RHIC, EIC, and EIC with added cooling configurations. Soil temperature data was analyzed to determine the maximum, average, and mode soil temperatures, which were used as boundary conditions in different temperature scenarios. Computational fluid dynamics modeling was used to create 2D temperature profiles for the configurations. From this model, the predicted temperatures indicate that further analysis is required to validate the boundary conditions and benchmark the current conditions to allow the prediction of the tunnel ambient conditions at EIC. This research can be used as a preliminary model to create an EIC tunnel cooling system that will increase the operational stability of the EIC. As a result of my work this summer, I have become familiar with computational fluid dynamics, including creating fluid dynamic simulations using ANSYS Fluent and related software. I have also learned about the project process required for planning large-scale engineering projects.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Fluid dynamic simulation and analysis of water-cooling systems for the Electron-Ion Collider

The Electron-Ion Collider is the newest large-scale project at Brookhaven National Laboratory. The collider’s purpose is to provide further advancements in the knowledge of the universe’s origin by accelerating particles near the speed of light. Our project for this 3.8 km ring was to create a thermal hydraulic steady-state simulation design of the water-cooling system to be cost-effective and energy efficient, as envisioned by Charlie Foltz, the EIC Infrastructure Division Director. The system would include a supply and return header, which cools several thousand components of the ring. The water would then be returned and cooled down using a system of cooling towers and plate and frame heat exchangers. Due to the size of the system and the complexity of the network analysis, a fluid dynamic simulation software, AFT Fathom, was used. Since previous methods of maintaining systems relied on building upon smaller real-life models and implementing empirical data, this flow model was unique and first of a kind in the domain of accelerator design, construction and operation. Therefore, our hydraulic team piloted a new method to perform network analysis on a large scale cooling system. We successfully created several test scenarios for system behavior in a shorter time compared to the method of performing hand calculations. Cooling specifications for heat rejection, pressure drop, flow rate, and pipe sizing were changed based on the individual systems of the vacuum, radio frequency (RF), magnet and power supply, and cryogenics sections. Finally, we used DOE guidelines to perform life-cycle cost analysis with net present value and carbon saving analysis on the systems where pipe size could be optimized.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision

Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape cosmic evolution. This whitepaper presents a vision for how Artificial Intelligence (AI) can accelerate discovery in this field. We outline grand challenges that must be addressed to enable transformative breakthroughs and describe how current and planned experimental facilities can implement this vision to advance our understanding of the vast and complex physical world from the smallest to the largest scales. We show how facilities currently under construction, such as the HL-LHC, DUNE and soon EIC, can both benefit from and serve as proving grounds for this vision, while also enabling a longer-term goal for how future experiments -- like FCC-ee at CERN, IceCube-Gen2, a Muon Collider in the U.S., and smaller to mid-scale projects -- can be fully AI-native. We describe how a truly national-scale collaboration, jointly managed across large funding partners, and involving both DOE laboratories and universities, can make this happen.

Aarrestad, Thea Klaeboe [ETH, Zurich (main)]↗
DOE OSTI2021

3D Mechanical Analysis of a Compact Nb 3 Sn IR Quadrupole for EIC

Abstract-The Electron Ion Collider (EIC) will require large aperture quadrupole magnets for the Hadron beam in the insertion region. Key requirements include high field, compact size, and tight control of the fringe fields. A 120 mm aperture, 308.4 mm outer diameter actively shielded Nb 3 Sn quadrupole model is under development to support these goals. This work is being carried out by a collaboration of BNL, JLAB and LBNL. A compact shell-based structure preloaded with a bladder and key system was developed for this project. In this paper, the effect of the compact structure on the mechanical behavior was investigated. In particular, the impact of the assembly tolerances and coil size variations on the actual coil stresses and bladder pressures was computed and compared with results from larger bladder and key structures developed for the LHC IR. The longitudinal preload is provided by stainless steel rods. Differently from other bladder and key magnets, the rods are first preloaded axially before coil axial load is applied. This new design aims to increase the overall stiffness of the system and reduce the longitudinal coil displacement during powering. Based on the results of a 3D mechanical analysis, the preliminary preload targets for the EIC quadrupole assembly will be reviewed and discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Design of the Electron–Ion Collider

The Electron–Ion Collider (EIC) is under construction at Brookhaven National Laboratory partnering with Jefferson Laboratory. The collider is designed for collisions of 70% polarized electrons and ions with luminosi ties up to $L$ = 1 × 10 34 cm -2 sec -1 at the center-of-mass energies up to 140 GeV. The report summarizes the requirements, describes the design of the collider, and presents the present status of the project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗