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Old Dominion University

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Articles 1 - 30 of 395

Full-Text Articles in Engineering Physics

Explainable Physics-Based Constraints On Reinforcement Learning For Accelerator Optimization, Jonathan Colen, Malachi Schram, Kishansingh Rajput, Armen Kasparian Jan 2026

Explainable Physics-Based Constraints On Reinforcement Learning For Accelerator Optimization, Jonathan Colen, Malachi Schram, Kishansingh Rajput, Armen Kasparian

Data Science Faculty Publications

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 …

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The Shms 11 Gev/C Spectrometer In Hall C At Jefferson Lab, S. Ali, A. Ahmidouch, G. R. Ambrose, A. Asaturyan, C. Ayerbe Gayoso, J. Benesch, V. Berdnikov, H. Bhatt, D. Bhetuwal, D. Biswas, P. Brindza, M. Bukhari, M. Burton, R. Carlini, M. Carmignotto, M. E. Christy, C. Cotton, J. Crafts, D. Day, S. Danagoulian, A. Dittmann, D. H. Dongwi, B. Duran, D. Dutta, R. Ent, H. Fenker, M. Fowler, D. Gaskell, A. Hamdi, N. Heinrich, W. Henry, N. Hlavin, T. Horn, G. M. Huber, Y. Ilieva, J. Jarrell, S. Jia, M. K. Jones, M. Junaid, M. L. Kabir, N. Kalantarians, A. Karki, S. J.D. Kay, C. E. Keppel, V. Kumar, S. Lassiter, W. B. Li, D. Mack, S. Malace, J. Mcmahan, A. Mkrtchyan, H. Mkrtchyan, P. Monaghan, C. Morean, P. Nadel-Turonski, G. Niculescu, M. I. Niculescu, A. Nadeeshani, E. Pooser, A. Ramos, J. Reinhold, B. Sawatzky, H. Szumila-Vance, V. Tadevosyan, R. L. Trotta, A. Usman, C. Yero, M. Yurov, S. Zhamkochyan, S. A. Wood, J. Zhang Jan 2026

The Shms 11 Gev/C Spectrometer In Hall C At Jefferson Lab, S. Ali, A. Ahmidouch, G. R. Ambrose, A. Asaturyan, C. Ayerbe Gayoso, J. Benesch, V. Berdnikov, H. Bhatt, D. Bhetuwal, D. Biswas, P. Brindza, M. Bukhari, M. Burton, R. Carlini, M. Carmignotto, M. E. Christy, C. Cotton, J. Crafts, D. Day, S. Danagoulian, A. Dittmann, D. H. Dongwi, B. Duran, D. Dutta, R. Ent, H. Fenker, M. Fowler, D. Gaskell, A. Hamdi, N. Heinrich, W. Henry, N. Hlavin, T. Horn, G. M. Huber, Y. Ilieva, J. Jarrell, S. Jia, M. K. Jones, M. Junaid, M. L. Kabir, N. Kalantarians, A. Karki, S. J.D. Kay, C. E. Keppel, V. Kumar, S. Lassiter, W. B. Li, D. Mack, S. Malace, J. Mcmahan, A. Mkrtchyan, H. Mkrtchyan, P. Monaghan, C. Morean, P. Nadel-Turonski, G. Niculescu, M. I. Niculescu, A. Nadeeshani, E. Pooser, A. Ramos, J. Reinhold, B. Sawatzky, H. Szumila-Vance, V. Tadevosyan, R. L. Trotta, A. Usman, C. Yero, M. Yurov, S. Zhamkochyan, S. A. Wood, J. Zhang

Physics Faculty Publications

The Super High Momentum Spectrometer (SHMS) has been built for Hall C at the Thomas Jefferson National Accelerator Facility (Jefferson Lab). With a momentum capability reaching 11 GeV/c, the SHMS provides measurements of charged particles produced in electron-scattering experiments using the maximum available beam energy from the upgraded Jefferson Lab accelerator. The SHMS is an ion-optics magnetic spectrometer comprised of a series of new superconducting magnets which transport charged particles through an array of triggering, tracking, and particle-identification detectors that measure momentum, energy, angle and position in order to allow kinematic reconstruction of the events back to their origin at …

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The Xpdirc Concept For Next-Generation Dirc Detectors, R. Dzhygadlo, J. Datta, K. Dehmelt, A. Deshpande, T. K. Hemmick, Md. I. Hossain, C. E. Hyde, Y. Ilieva, G. Kalicy, W. J. Llope, P. Nadel-Turonski, C. Schwarz, J. Schwiening, N. Shankman, J. Stevens, N. Wickramaarachchi, C. Woody Jan 2026

The Xpdirc Concept For Next-Generation Dirc Detectors, R. Dzhygadlo, J. Datta, K. Dehmelt, A. Deshpande, T. K. Hemmick, Md. I. Hossain, C. E. Hyde, Y. Ilieva, G. Kalicy, W. J. Llope, P. Nadel-Turonski, C. Schwarz, J. Schwiening, N. Shankman, J. Stevens, N. Wickramaarachchi, C. Woody

Physics Faculty Publications

The next-generation DIRC (xpDIRC) represents a novel detector geometry concept currently being developed for advanced particle identification systems in high-energy physics experiments. Building upon the high-performance DIRC (hpDIRC) designed for the ePIC detector at the Electron-Ion Collider, the xpDIRC introduces a hybrid optical architecture that combines enhanced focusing optics, a wide plate light guide, and a compact expansion volume. Comprehensive Geant4 simulations demonstrate that the xpDIRC hybrid geometry achieves state-of-the-art performance in π/K separation across the entire range of operation.

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K-Long Facility At Jlab, Moskov Amaryan Jan 2026

K-Long Facility At Jlab, Moskov Amaryan

Physics Faculty Publications

In this talk I present the outline of K-long Facility (KLF) at JLab [1]. It was approved by PAC48 in 2020 to run for 200 days of beamtime, equally divided between liquid hydrogen and deuterium targets, to measure dozens of hyperon states predicted by CQM and LQCD but not yet established. This facility also will allow to measure Kπ scattering in different channels to observe the so-called ᴷ scalar meson and measure its width and position with unprecedented accuracy. Finally, it will be shown that exotic baryons can be measured at this facility in formation reactions with a two-body final …

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Geometry Of Almost-Conserved Quantities In Symplectic Maps: Approximate Invariants In Nonlinear Accelerator Systems, T. Zolkin, S. Nagaitsev, I. Morozov, S. Kladov Jan 2026

Geometry Of Almost-Conserved Quantities In Symplectic Maps: Approximate Invariants In Nonlinear Accelerator Systems, T. Zolkin, S. Nagaitsev, I. Morozov, S. Kladov

Physics Faculty Publications

We present a perturbative method for constructing approximate invariants of motion directly from the equations of discrete-time symplectic systems. This framework offers a natural nonlinear extension of the classic Courant-Snyder (CS) theory for systems with 1 degree of freedom—a foundational cornerstone in accelerator physics now spanning seven decades and historically focused on linear phenomena. The original CS formalism emerged under conditions where nonlinearities were weak, design goals favored linear motion, and analytical tools—such as the Kolmogorov-Arnold-Moser theory—had not yet been fully developed. While various normal-form methods have been proposed to treat near-integrable dynamics, the approach introduced here stands out for …

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Ai-Enabled Digital Twins And Optimization Workflows For Accelerator Control, M. Yadav, A. Seryi, B. Terzic, J. Bird, J. Delayen, K. Makino, K. Ahmed, L. Van Riesen-Haupt, Q. Su, S. De Silva, S. Hossain, T. Griffin, T. Satogata Jan 2026

Ai-Enabled Digital Twins And Optimization Workflows For Accelerator Control, M. Yadav, A. Seryi, B. Terzic, J. Bird, J. Delayen, K. Makino, K. Ahmed, L. Van Riesen-Haupt, Q. Su, S. De Silva, S. Hossain, T. Griffin, T. Satogata

Physics Faculty Publications

We propose to develop advanced ML models, such as physics informed neural network (PINN) based surrogate models, to accurately represent accelerator phase space transport. These surrogate models will enable precise diagnosis and prediction of beam phase space evolution along the beamline, facilitating real-time control and optimization. The developed models will be tested using the Upgraded Injector Test Facility (UITF) at Thomas Jefferson National Accelerator Facility (JLab), providing a pathway toward ML-driven enhanced diagnostics and beamline control in operational accelerator environments. The primary aim will be to facilitate this by developing machine learning models that outperform traditional simulations in speed and …

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Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard Jan 2026

Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Accurately forecasting the operating temperature of lithium-ion batteries (LIBs) is essential for preventing thermal runaway, extending service life, and ensuring the safe operation of electric vehicles and stationary energy-storage systems. This work introduces a unified, physics-informed, and data-driven temperature-prediction framework that integrates mathematically governed preprocessing, electrothermal decomposition, and sequential deep learning architectures. The methodology systematically applies the governing relations to convert raw temperature measurements into trend, seasonal, and residual components, thereby isolating long-term thermal accumulation, reversible entropy-driven oscillations, and irreversible resistive heating. These physically interpretable signatures serve as structured inputs to machine learning and deep learning models trained on temporally …

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Mtl_Tx: A Multi-Task Transformer Model For Improved Radiation Time-Series Estimation, Hongfang Zhang, Adam Stavola, Hal Ferguson, Bence Budavari, Hongyi Wu, Chiman Kwan, Jiang Li Jan 2026

Mtl_Tx: A Multi-Task Transformer Model For Improved Radiation Time-Series Estimation, Hongfang Zhang, Adam Stavola, Hal Ferguson, Bence Budavari, Hongyi Wu, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed …

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Variational Autoencoder Inverse Mapper For Extraction Of Compton Form Factors: Benchmarks And Conditional Learning, Douglas Adams, Md Fayaz Bin Hossen, Joshua Bautista, Gia-Wei Chern, Simonetta Liuti, Marie Boër, Marija Čuić, Michael Engelhardt, Gary R. Goldstein, Huey-Wen Lin, Yaohang Li Jan 2026

Variational Autoencoder Inverse Mapper For Extraction Of Compton Form Factors: Benchmarks And Conditional Learning, Douglas Adams, Md Fayaz Bin Hossen, Joshua Bautista, Gia-Wei Chern, Simonetta Liuti, Marie Boër, Marija Čuić, Michael Engelhardt, Gary R. Goldstein, Huey-Wen Lin, Yaohang Li

Computer Science Faculty Publications

Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from generalized parton distributions (GPDs) via Fourier transform relative to proton momentum transfer. QCD factorization theorems enable DVES to be parameterized by Compton form factors (CFFs), which are convolutions of GPDs with perturbatively calculable kernels. Accurate extraction of CFFs from DVCS, benefiting from interference with the Bethe–Heitler (BH) process and a simpler final state structure, is essential for inferring GPDs. This paper focuses on extracting CFFs from DVCS data using a variational autoencoder inverse mapper (VAIM) and …

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A Survey On Generative Ai For Detector Effects Unfolding In Particle And Nuclear Physics, Tareq Alghamdi, Tommaso Vittorini, Jitao Xu, Marco Battaglieri, Derek I. Glazier, Glòria Montaña, Giorgio Foti, Alessandro Pilloni, Nobuo Sato, Yaohang Li Jan 2026

A Survey On Generative Ai For Detector Effects Unfolding In Particle And Nuclear Physics, Tareq Alghamdi, Tommaso Vittorini, Jitao Xu, Marco Battaglieri, Derek I. Glazier, Glòria Montaña, Giorgio Foti, Alessandro Pilloni, Nobuo Sato, Yaohang Li

Computer Science Faculty Publications

In particle and nuclear physics, “detector effects unfolding” can be viewed as a highdimensional inverse problem whose goal is to recover the true event distributions from observed experimental data corrupted by detector-induced distortions. Recent advances in generative AI have positioned data-driven and machine learning-based approaches as powerful alternatives to traditional unfolding techniques, offering superior scalability to high-dimensional data, capability of learning complex detector responses, and the ability to operate directly at the event level. We survey state-of the-art generative AI-based models for detector folding and unfolding. We review existing architectures and training strategies, and highlight recent methodological advances and open …

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Polarized Positrons At Ce⁺Baf, A. Ushakov, J. Benesch, M. Bruker, L. Cardman, J. Conway, S. Covrig Dusa, P. Degtiarenko, Y. Enomoto, S. Gessner, P. Ghoshal, S. Gopinath, J. Grames, C. Gulliford, S. Habet, G. Hays, C. Hernández-García, A. Hofler, R. Kazimi, M. Kostin, V. O. Kostroun, F. Lin, V. Lizárraga-Rubio, K. Mahler, Y. Morikawa, S. Nagaitsev, S. Ogur, G. Palacios-Serrano, N. Raut, B. Rimmer, Y. Roblin, A. Seryi, K. Smolenski, M. Stutzman, R. Suleiman, A. Sy, N. Taylor, D. Turner, A. Ushakov, C. Valerio-Lizarraga, E. Voutier, S. Wang, Y. Zhang Jan 2025

Polarized Positrons At Ce⁺Baf, A. Ushakov, J. Benesch, M. Bruker, L. Cardman, J. Conway, S. Covrig Dusa, P. Degtiarenko, Y. Enomoto, S. Gessner, P. Ghoshal, S. Gopinath, J. Grames, C. Gulliford, S. Habet, G. Hays, C. Hernández-García, A. Hofler, R. Kazimi, M. Kostin, V. O. Kostroun, F. Lin, V. Lizárraga-Rubio, K. Mahler, Y. Morikawa, S. Nagaitsev, S. Ogur, G. Palacios-Serrano, N. Raut, B. Rimmer, Y. Roblin, A. Seryi, K. Smolenski, M. Stutzman, R. Suleiman, A. Sy, N. Taylor, D. Turner, A. Ushakov, C. Valerio-Lizarraga, E. Voutier, S. Wang, Y. Zhang

Mechanical & Aerospace Engineering Faculty Publications

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab [1]. This concept is based on positron beam generation by a high current polarized electron beam (1 mA, 120 MeV, >85% polarization) irradiating a rotating water-cooled tungsten target or liquid metal target. The update on the development of the Ce⁺BAF injector concept including the polarized electron source, the development of high power targets, simulations of positron capture, the design of the transport line from the positron injector to the CEBAF North Linac and the planned experiment …

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Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks, Jonathon E. Slightam, Logan E. Beaver Jan 2025

Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks, Jonathon E. Slightam, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

Autonomous robotic manipulation in unstructured environments faces many challenges and is hindered by capabilities that bridge the gap between perception and acting on the world. Action plans that are centric to object motion rather than end-of-arm tooling behavior may aid this. This paper presents an autonomous action planner for a feedback linearizeable system comprised of three base motions that can be leveraged on their own or in combination to give custom motion plans. The optimization routine for the three different types of motion are presented, which are integrated into physics informed neural networks. A component of this is the autonomy …

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Geometric Gnns For Charged Particle Tracking At Gluex, Ahmed Hossam Mohammed, Kishansingh Rajput, Simon Taylor, Denis Furletov, Sergey Furletov, Malachi Schram Jan 2025

Geometric Gnns For Charged Particle Tracking At Gluex, Ahmed Hossam Mohammed, Kishansingh Rajput, Simon Taylor, Denis Furletov, Sergey Furletov, Malachi Schram

Computer Science Faculty Publications

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this …

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Harnessing The Power Of Gradient-Based Simulations For Multi-Objective Optimization In Particle Accelerators, Kishansingh Rajput, Malachi Schram, Auralee Edelen, Jonathan Colen, Armen Kasparian, Ryan Roussel, Adam Carpenter, He Zhang, Jay Benesch Jan 2025

Harnessing The Power Of Gradient-Based Simulations For Multi-Objective Optimization In Particle Accelerators, Kishansingh Rajput, Malachi Schram, Auralee Edelen, Jonathan Colen, Armen Kasparian, Ryan Roussel, Adam Carpenter, He Zhang, Jay Benesch

Data Science Faculty Publications

Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-objective optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithms (GAs), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems in particle accelerators using a deep differentiable reinforcement learning (DDRL) algorithm. We compare the DDRL algorithm with model-free reinforcement learning (MFRL), GA, and Bayesian optimization (BO) for simultaneous optimization of heat load and trip rates in the continuous electron beam accelerator facility. The …

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Vaim-Cff: A Variational Autoencoder Inverse Mapper Solution To Compton Form Factor Extraction From Deeply Virtual Compton Scattering, Manal Almaeen, Tareq Alghamdi, Brandon Kriesten, Douglas Adams, Yaohang Li, Huey-Wen Lin, Simonetta Liuti Jan 2025

Vaim-Cff: A Variational Autoencoder Inverse Mapper Solution To Compton Form Factor Extraction From Deeply Virtual Compton Scattering, Manal Almaeen, Tareq Alghamdi, Brandon Kriesten, Douglas Adams, Yaohang Li, Huey-Wen Lin, Simonetta Liuti

Computer Science Faculty Publications

We develop a new methodology for extracting Compton form factors (CFFs) from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse mapper (VAIM). The VAIM-CFF framework not only allows us access to a fitted solution set possibly containing multiple solutions in the extraction of all 8 CFFs from a single cross section measurement, but also accesses the lost information contained in the forward mapping from CFFs to cross section. We investigate various assumptions and their effects on the predicted CFFs such as cross section organization, number of extracted …

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Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver Jan 2025

Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

This work develops a control-centric framework for a custom 4-DOF rigid-body manipulator by coupling a reduced-order Pontryagin’s Maximum Principle (PMP) controller with a physics-informed Gradient Descent stage. The reduced PMP model provides a closed-form optimal control law for the joint accelerations, while the Gradient Descent module determines the corresponding time horizons by minimizing a cost functional built directly from the full Rigid-Body Dynamics. Structural-mechanics reaction analysis is used only to initialize feasible joint velocities—most critically the azimuthal component—ensuring that the optimizer begins in a physically admissible region. The resulting kinematic trajectories and dynamically consistent time horizons are then supplied to …

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Decode The Workload: Training Deep Learning Models For Efficient Compute Cluster Representation, Ahmed Hossam Mohammed, Mark Jones, Diana Mcspadden, Malachi Schram, Bryan Hess, Kishansingh Rajput Jan 2025

Decode The Workload: Training Deep Learning Models For Efficient Compute Cluster Representation, Ahmed Hossam Mohammed, Mark Jones, Diana Mcspadden, Malachi Schram, Bryan Hess, Kishansingh Rajput

Computer Science Faculty Publications

In this study, we address the mounting challenge of monitoring high throughput computing clusters running computationally intensive jobs, which increasingly strains system administrators. We develop autoencoders that analyze traces of Linux kernel CPU metrics to capture salient system features by producing robust compressed embeddings for various downstream tasks. In addition, we employ graph neural networks to incorporate contextual information from surrounding CPUs and assess their performance. We also demonstrate the enhanced job differentiation achieved by increasing the sampling rate of these traces. Our models are evaluated based on their ability to generate meaningful latent representations, detect anomalies, and distinguish between …

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Physics Case For Quarkonium Studies At The Electron Ion Collider, Daniël Boer, Chris A. Flett, Carlo Flore, Daniel Kikoła, Jean-Philippe Lansberg, Maxim Nefedov, Charlotte Van Hulse, Shohini Bhattacharya, Jelle Bor, Mathias Butenschoen, Federico Ceccopieri, Longjie Chen, Vincent Cheung, Umberto D'Alesio, Miguel Echevarria, Yoshitaka Hatta, Charles E. Hyde, Raj Kishore, Leszek Kosarzewski, Cédric Lorcé, Wenliang Li, Xuan Li, Luca Maxia, Andreas Metz, Asmita Mukherjee, Carlos Muñoz Camacho, Francesco Murgia, Pawel Nadel-Turonski, Cristian Pisano, Jian-Wei Qiu, Sangem Rajesh, Matteo Rinaldi, Jennifer Rittenhouse West, Vladimir Saleev, Nathaly Santiesteban, Chalis Setyadi, Pieter Taels, Zhoudunmin Tu, Ivan Vitev, Ramona Vogt, Kazuhiro Watanabe, Xiaojun Yao, Yelyzaveta Yedelkina, Shinsuke Yoshida Jan 2025

Physics Case For Quarkonium Studies At The Electron Ion Collider, Daniël Boer, Chris A. Flett, Carlo Flore, Daniel Kikoła, Jean-Philippe Lansberg, Maxim Nefedov, Charlotte Van Hulse, Shohini Bhattacharya, Jelle Bor, Mathias Butenschoen, Federico Ceccopieri, Longjie Chen, Vincent Cheung, Umberto D'Alesio, Miguel Echevarria, Yoshitaka Hatta, Charles E. Hyde, Raj Kishore, Leszek Kosarzewski, Cédric Lorcé, Wenliang Li, Xuan Li, Luca Maxia, Andreas Metz, Asmita Mukherjee, Carlos Muñoz Camacho, Francesco Murgia, Pawel Nadel-Turonski, Cristian Pisano, Jian-Wei Qiu, Sangem Rajesh, Matteo Rinaldi, Jennifer Rittenhouse West, Vladimir Saleev, Nathaly Santiesteban, Chalis Setyadi, Pieter Taels, Zhoudunmin Tu, Ivan Vitev, Ramona Vogt, Kazuhiro Watanabe, Xiaojun Yao, Yelyzaveta Yedelkina, Shinsuke Yoshida

Physics Faculty Publications

The physics case for quarkonium-production studies accessible at the US Electron Ion Collider is described.

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Thermal Analysis For The Fundamental Power Coupler Of The 197 Mhz Crab Cavity For Eic, A. Castilla, J. Guo, N. Huque, S. De Silva, Jean Delayen Jan 2025

Thermal Analysis For The Fundamental Power Coupler Of The 197 Mhz Crab Cavity For Eic, A. Castilla, J. Guo, N. Huque, S. De Silva, Jean Delayen

Physics Faculty Publications

The Electron-Ion Collider (EIC) is being designed by BNL in collaboration with Jefferson Lab. The Phase-I design includes the installation of two cryomodules of 197 MHz crabbing cavities installed at the Hadron Storage Ring (HSR) at the interaction region, IP6 that has a crossing angle of 25 mrad. Each cryomodule consists of two 197 MHz RFD type crabbing cavities. The first article cavity has been designed following the machine requirements and specifications including the fundamental power coupler (FPC), higher order mode couplers, and field probes. A detailed rf analysis has been completed to determine the worst operational case of the …

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Sensitivity Analysis Of The 197 Mhz Prototype Crab Cavity For Eic, Subashini De Silva, Jean R. Delayen, B. Xiao, E. Drachuk, I. H. Senevirathne, A. Castilla, N. Huque, Z. Li Jan 2025

Sensitivity Analysis Of The 197 Mhz Prototype Crab Cavity For Eic, Subashini De Silva, Jean R. Delayen, B. Xiao, E. Drachuk, I. H. Senevirathne, A. Castilla, N. Huque, Z. Li

Physics Faculty Publications

The Electron-Ion Collider at BNL requires several crabbing systems that will be operating at 197 MHz and 394 MHz to compensate for the loss of luminosity due to the large crossing angle of the colliding beams. Two 197 MHz crab cavity cryomodules containing two cavities each will be installed in the Hadron Storage Ring (HSR) at the IP6 interaction region. Due to its large size compared to previously developed crabbing cavities, the 197 MHz crabbing cavity system was identified as one of the critical rf systems in the EIC. Therefore, a cavity has been designed including the ancillaries, and is …

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Point Cloud-Based Diffusion Models For The Electron-Ion Collider, Jack Y. Araz, Vinicius Mikuni, Felix Ringer, Nobuo Sato, Fernando Torales Acosta, Richard Whitehill Jan 2025

Point Cloud-Based Diffusion Models For The Electron-Ion Collider, Jack Y. Araz, Vinicius Mikuni, Felix Ringer, Nobuo Sato, Fernando Torales Acosta, Richard Whitehill

Physics Faculty Publications

At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standard Model, and inference tasks. In particular, it has been demonstrated that score-based diffusion models can generate high-fidelity and accurate samples of jets or collider events. This work expands on previous generative models in three distinct ways. First, our model is trained to generate entire collider events, including all particle species with complete kinematic information. We quantify how well the model learns event-wide constraints such as the conservation of momentum and discrete quantum numbers. We …

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Hybrid Quantum Simulations With Qubits And Qumodes On Trapped-Ion Platforms, Jack Y. Araz, Matt Grau, Jake Montgomery, Felix Ringer Jan 2025

Hybrid Quantum Simulations With Qubits And Qumodes On Trapped-Ion Platforms, Jack Y. Araz, Matt Grau, Jake Montgomery, Felix Ringer

Physics Faculty Publications

We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms. Trapped-ion systems have demonstrated record one- and two-qubit gate fidelities and long qubit coherence times, while qumodes, which can be represented by the collective vibrational modes of the ion chain, have remained relatively unexplored for their use in computing. Using numerical simulations, we show that high-fidelity hybrid gates and measurement operations can be achieved for existing trapped-ion quantum platforms. As an exemplary application, we consider quantum simulations of the Jaynes-Cummings-Hubbard model, which is given by a one-dimensional chain of interacting …

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Eic 197 Mhz Crab Cavity Hom Damping And Tolerence Analysis, Z. Li, B. Xiao, S. U. De Silva, Q. Wu, J. R. Delayen, R. Rimmer Jan 2025

Eic 197 Mhz Crab Cavity Hom Damping And Tolerence Analysis, Z. Li, B. Xiao, S. U. De Silva, Q. Wu, J. R. Delayen, R. Rimmer

Physics Faculty Publications

Crab cavities, operating at 197 MHz and 394 MHz respectively, will be used to compensate the loss of luminosity due to a 25 mrad crossing angle at the interaction point in the Electron Ion Collider (EIC). Both cavities are of the RF Dipole (RFD) type. To meet the stringent impedance requirements for beam stability and quality, the cavity design must incorporate strong Higher Order Mode (HOM) damping. A special type of HOM coupler has been developed (for both horizontal and vertical HOMs), which consisting of a waveguide stub that couples to the cavity and a waveguide-to-coaxial transition that extracts the …

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Design Of A Shipping Fixture For A Compact Cryomodule Hermetic Assembly, J. Lewis, G. Ciovati, N. Huque, J. Armstrong, K. Harding Jan 2025

Design Of A Shipping Fixture For A Compact Cryomodule Hermetic Assembly, J. Lewis, G. Ciovati, N. Huque, J. Armstrong, K. Harding

Physics Faculty Publications

Two conduction-cooled 915 MHz superconducting radio frequency hermetic assemblies must be safely transported from the Jefferson Lab in Newport News, VA to General Atomics in San Diego, CA for performance testing in a custom horizontal test cryostat. One hermetic assembly consists of a 2-cell 915 MHz cavity, a coaxial fundamental power coupler, and the warm-to-cold transition beam tubes. The second hermetic assembly consists of a 2-cell 915 MHz cavity only. The assemblies will be transported on a flatbed air-ride trailer over the approximate 4000 km distance. Design requirements included adequate attenuation of 4g vertical axis, 5g beamline axis, and 1.5g …

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Effect Of Activation Temperature On Quantum Efficiency And Lifetime Of Nea Truncated Nanocone Array Gaas Photocathode, Md. Aziz Arroyo Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali Jan 2025

Effect Of Activation Temperature On Quantum Efficiency And Lifetime Of Nea Truncated Nanocone Array Gaas Photocathode, Md. Aziz Arroyo Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali

Physics Faculty Publications

This study investigates the quantum efficiency (QE) and operational lifetime of a negative electron affinity GaAs truncated nanocone array (TNCA) photocathode benchmarked against a conventional flat GaAs photocathode under varying activation temperatures. The TNCA structure demonstrated a QE of up to 13.6% at 590 nm with room temperature (RT) activation—approximately 1.5 times higher than its flat counterpart. This enhancement is due to Mie resonance effects within the nanostructure, as confirmed by finite-difference time-domain simulations. Moreover, the TNCA photocathode exhibits significantly extended charge lifetime, with enhancement factors of ∼6.1 and ∼19.8 under RT and 50 °C activations, respectively. These gains are …

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Modeling Strain And Quantum Confinement In Gaas/GaXIn1-XP Superlattices For Spin-Polarized Electron Sources, A. Kachwala, G. Blume, S. Marsillac, J. Grames, M. Grau Jan 2025

Modeling Strain And Quantum Confinement In Gaas/GaXIn1-XP Superlattices For Spin-Polarized Electron Sources, A. Kachwala, G. Blume, S. Marsillac, J. Grames, M. Grau

Physics Faculty Publications

In this study, we systematically design and simulate a series of GaAs-based superlattice configurations aimed at enhancing heavy-hole–light-hole band splitting while simultaneously optimizing band alignment to reduce the conduction band barrier, thereby facilitating efficient electron transport. These combined effects are crucial for achieving high electron spin polarization and high quantum efficiency, the two key performance metrics of next-generation spin-polarized electron sources. We investigated three types of superlattice architectures: (1) compressively strained GaAs wells on GaInP barriers, yielding a maximum band splitting of 140 meV, (2) lattice-matched GaAs/GaInP structures, resulting in the maximum band splitting of 75 meV, and (3) tensile …

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Investigation Of New Superconducting Materials For The Next Generation High-Performance Rf Superconducting Cavities For Particle Accelerators, Alex Gurevich, Jean Delayen, Chang-Beom Eom, Gianluigi Ciovati Jan 2025

Investigation Of New Superconducting Materials For The Next Generation High-Performance Rf Superconducting Cavities For Particle Accelerators, Alex Gurevich, Jean Delayen, Chang-Beom Eom, Gianluigi Ciovati

Physics Faculty Publications

In this DOE-funded project DE-SC0010081-020 Old Dominion University (ODU) in collaboration with University of Wisconsin (UW) and Jefferson Laboratory have investigated both experimentally and theoretically electromagnetic response and losses in multilayered superconducting structures made of new SRF materials which can push the field and Q performance limits of accelerating cavities.

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A Plan To Revitalize The Domestic Superconducting Radio-Frequency Industry, G. Ciovati, M. Schuchman, W. Donaldson, A. Murokh, M. Naughton, D. Osha, D. Packard, J. Rathke, A. Todd Jan 2025

A Plan To Revitalize The Domestic Superconducting Radio-Frequency Industry, G. Ciovati, M. Schuchman, W. Donaldson, A. Murokh, M. Naughton, D. Osha, D. Packard, J. Rathke, A. Todd

Physics Faculty Publications

Superconducting radio-frequency (SRF) cavities are essential building blocks of modern particle accelerators for scientific research, and they offer unique capabilities that could be transformative for commercial applications. Growth of the domestic SRF industry in North America has faced several challenges over the past decades, as most of the international demand for cavities was supplied by European vendors. This contribution provides a brief review of the domestic industrial vendor space, an outlook of the global demand for SRF cavities and an outline of the challenges leading to this supply chain deficiency. One of the main challenges towards establishing a robust domestic …

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State Preparation Of Lattice Field Theories Using Quantum Optimal Control, Jack Y. Araz, Siddhanth Bhowmick, Matt Grau, Thomas J. Mcentire, Felix Ringer Jan 2025

State Preparation Of Lattice Field Theories Using Quantum Optimal Control, Jack Y. Araz, Siddhanth Bhowmick, Matt Grau, Thomas J. Mcentire, Felix Ringer

Physics Faculty Publications

We explore the application of quantum optimal control (QOC) techniques to state preparation of lattice field theories on quantum computers. As a first example, we focus on the Schwinger model, quantum electrodynamics in 1 + 1 dimensions. We demonstrate that QOC can significantly speed up the ground state preparation compared to gate-based methods, even for models with long-range interactions. Using classical simulations, we explore the dependence on the interqubit coupling strength and the device connectivity, and we study the optimization in the presence of noise. While our simulations indicate potential speedups, the results strongly depend on the device specifications. In …

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Preparation Of Mocvd-Grown Photocathodes Containing A Strained Gaas/Gaasp Superlattice, G. Blume, A. Masters, J. Grames, M. Stutzman, M. Grau, S. Marsillac Jan 2025

Preparation Of Mocvd-Grown Photocathodes Containing A Strained Gaas/Gaasp Superlattice, G. Blume, A. Masters, J. Grames, M. Stutzman, M. Grau, S. Marsillac

Physics Faculty Publications

In this work, we investigate heat cleaning options for high-polarization GaAs/GaAsP strained-superlattice (SSL) photocathodes with a distributed Bragg reflector (DBR) that were grown using metalorganic chemical vapor deposition (MOCVD). This was done using a microMott polarimeter at Jefferson Lab to optimize both quantum efficiency and polarization. The fabrication process for MOCVD-grown photocathodes does not allow for the inclusion of an arsenic cap, contrary to what is done when fabricating photocathodes using molecular-beam epitaxy (MBE). Without proper preparation, the performance of MOCVD-grown photocathodes can be limited due to surface contamination. Here, we varied both duration and temperature of the heat cleaning …

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