Physics Commons^™

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 …

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 …

Data-Driven Gradient Optimization For Field Emission Management In A Superconducting Radio-Frequency Linac, S. Goldenberg, K. Ahammed, A. Carpenter, J. Li, R. Suleiman, C. Tennant

Electrical & Computer Engineering Faculty Publications

Field emission can cause significant problems in superconducting radio-frequency linear accelerators (linacs). When cavity gradients are pushed higher, radiation levels within the linacs may rise exponentially, causing degradation of many nearby systems. This research aims to utilize machine learning with uncertainty quantification to predict radiation levels at multiple locations throughout the linacs and ultimately optimize cavity gradients to reduce field emission-induced radiation while maintaining the total linac energy gain necessary for the experimental physics program. The optimized solutions show over 40% reductions for both neutron and gamma radiation from the standard operational settings.

Polarized Photocathode R&D At Bnl And Spin Consideration For The Eic Preinjector, Jyoti Biswas, Erdong Wang, Omer Rahman, John Skaritka, Adam Masters, Sylvain Marsillac, Tai-De Li

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes are vital for producing polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector at the EIC requires a 7 nC bunch with at least 85% spin polarization from a GaAs-based superlattice cathode. The doping density of the very surface layer of the cathode needs to be optimized to extract a high bunch charge beam from the high-voltage DC gun. The polarization axis of the emitted beam is longitudinal, and it will be rotated to transverse direction using two Wien filters, each rotating the spin by 45 degrees. In this paper, we …

Time-Marching Quantum Algorithm For Simulation Of Nonlinear Lorenz Dynamics, Efstratios Koukoutsis, George Vahala, Min Soe, Kyriakos Hizanidis, Linda Vahala, Abhay K. Ram

Electrical & Computer Engineering Faculty Publications

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by developing an explicit quantum algorithm that implements the time evolution of a second-order time-discretized version of the Lorenz model. The Lorenz model is a celebrated system of nonlinear ordinary differential equations that has been extensively studied in the contexts of climate science, fluid dynamics, and chaos theory. Our algorithm possesses a recursive structure and requires only a linear number of copies of the initial state …

The Effect Of Electrode Geometry On Excited Species Production In Atmospheric Pressure Air-Hydrogen Streamer Discharge, Shirshak Kumar Dhali, Stuart Reyes

Electrical & Computer Engineering Faculty Publications

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the …

Quantum Efficiency, Electron Spin Polarization And Lifetime Study For Gaas Based Truncated Nanocone Array Photocathodes, Md. Aziz Ar Rahman, Greg Blume, Md Abdullah Mamun, Shukui Zhang, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

[First slide] Direct band-gap photocathode (Eg = 1.42 eV).

Valence band maximum (VBM) is doubly degenerate, Max. electron spin polarization (ESP) ~35-40%.

Strained-supperlattice (SSL) removed the VBM degeneracy, ESP ~85-90% with QE of ~1% at 780 nm.

Requires UHV: Lifetime ~200 C with ~200 μA beam current.

Ion-back bombardment degrades the lifetime.

Improvement in charge lifetime required for JLAB polarized positron source program: 1mA-10mA beam current for 2 weeks ~ 10³10⁴C.

Optimizing Superconducting Nb Film Cavities By Mitigating Medium-Field Q-Slope Through Annealing, B. Abdisatarov, G. Eremeev, H. E. Elsayed-Ali, D. Bafia, A. Murthy, Z. Sung, A. Netepenko, A. Romanenko, C. P.A. Carlos, G. J. Rosaz, S. Calatroni, S. Leith, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are of interest in applications in various superconducting devices, such as superconducting radiofrequency cavities for particle accelerators and superconducting qubits for quantum computing. In this study, we address the persistent medium-field Q-slope issue in Nb film cavities, which, despite their high-quality factor at low RF fields, exhibit a significant Q-slope at medium RF fields compared to bulk Nb cavities. Traditional heat treatments, effective in reducing surface resistance and mitigating the Q-slope in bulk Nb cavities, are challenging for Nb-coated copper cavities. To overcome this challenge, we employed DC bias high-power impulse magnetron sputtering to deposit …

Streamer Discharge Modeling For Plasma-Assisted Combustion, Stuart Reyes, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

Some of the popular and successful atmospheric pressure fuel/air plasma-assisted combustion methods use repetitive ns pulsed discharges and dielectric-barrier discharges. The transient phase in such discharges is dominated by transport under strong space charge from ionization fronts, which is best characterized by the streamer model. The role of the nonthermal plasma in such discharges is to produce radicals, which accelerates the chemical conversion reaction leading to temperature rise and ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to develop a predictive model. We examine the important characteristics of streamers that influence combustion and develop some …

Detecting Anomalous Srf Cavity Behavior With Unsupervised Learning, Hal Ferguson, Jiang Li, Adam Carpenter, Chris Tennant, Dillon Thomas, Dennis Turner

Electrical & Computer Engineering Faculty Publications

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a …

Direct Measurement Of Microwave Loss In Nb Films For Superconducting Qubits, B. Abdisatarov, D. Bafia, A. Murthy, G. Eremeev, H. E. Elsayed-Ali, J. Lee, A. Netepenko, C. P. A. Carlos, S. Leith, G. J. Rosaz, A. Romanenko, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are a key component in modern two-dimensional superconducting qubits, yet their contribution to the total qubit decay rate is not fully understood. The presence of different layers of materials and interfaces makes it difficult to identify the dominant loss channels in present two-dimensional qubit designs. In this paper, we present the study that directly correlates measurements of RF losses in such films to material parameters by investigating a high-power impulse magnetron sputtered (HiPIMS) film atop a three-dimensional niobium superconducting radio frequency (SRF) resonator. By using a 3D SRF structure, we are able to isolate the niobium film loss …

Quest For An Optimal Spin-Polarized Electron Source For The Electron-Ion Collider, J. Biswas, E. Wang, O. Rahman, J. Sharitka, K. Kisslinger, Adam Masters, S. Marsillac, T. Lee

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes play a crucial role as the primary source of polarized electrons in various accelerator facilities, including the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson National Laboratory and the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. To increase the quantum efficiency (QE) of GaAs/GaAsP superlattice photocathodes, a Distributed Bragg Reflector (DBR) is grown underneath using metal-organic chemical vapor deposition (MOCVD). There are several challenges associated with DBR photocathodes: the resonance peak may not align with the emission threshold of around 780 nm, non-uniform doping density in the top 5 nm may significantly impact QE and spin polarization, …

Thermal Diffusivity And Acoustic Properties Of Nb Thin Films Studied By Time-Domain Thermoreflectance, Md. Obidul Islam, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

The thermal diffusion and acoustic properties of Nb impacts the thermal management of devices incorporating Nb thin films such as superconducting radiofrequency (SRF) cavities and superconducting high-speed electronic devices. The diffusion and acoustic properties of 200-800 nm thick Nb films deposited on Cu substrates were investigated using time-domain thermoreflectance (TDTR). The films were examined by X-ray diffraction, scanning electron microscopy, and atomic force microscopy. The grain size and thermal diffusivity increase with film thickness. The thermal diffusivity increased from 0.100± 0.002 cm²s^-1 to 0.237± 0.002 cm²s^-1 with the increase in film thickness from 200 …

Parametrization Of Fluid Models For Electrical Breakdown Of Nitrogen At Atmospheric Pressure, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

In the transient phase of an atmospheric pressure discharge, the avalanche turns into a streamer discharge with time. Hydrodynamic fluid models are frequently used to describe the formation and propagation of streamers, where charge particle transport is dominated by the creation of space charge. The required electron transport data and rate coefficients for the fluid model are parameterized using the local mean energy approximation (LMEA) and the local field approximation (LFA). In atmospheric pressure applications, the excited species produced in the electrical discharge determine the subsequent conversion chemistry. We performed the fluid model simulation of streamers in nitrogen gas at …

Transfer Learning For Field Emission Mitigation In Cebaf Srf Cavities, K. Ahammed, J. Li, A. Carpenter, C. Tennant, R. Suleiman

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) operates hundreds of superconducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed invasive gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio-frequency (RF) gradients changes or due …

Accelerating Cavity Fault Prediction Using Deep Learning At Jefferson Laboratory, Md M. Rahman, A. Carpenter, K. Iftekharuddin, C. Tennant

Electrical & Computer Engineering Faculty Publications

Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive …

Quantum Efficiency And Lifetime Study For Negative Electron Affinity Gaas Nanopillar Array Photocathode, Md Aziz Ar Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

Recent studies showed significant improvement in quantum efficiency (QE) by negative electron affinity (NEA) GaAs nanopillar array (NPA) photocathodes over their flat surface peers, particularly at 500 ─ 800 nm waveband. However, the underlying physics is yet to be well understood for further improvement in its performance. In this report, NEA GaAs NPA photocathodes with different dimensions were studied. The diameter of the nanopillars varied from 200 ─ 360 nm, the height varied from 230 ─ 1000 nm and the periodicity varied from 470 ─ 630 nm. The QE and photocathode lifetime were measured. Mie-resonance enhancement was observed at tunable …

The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe

Electrical & Computer Engineering Faculty Publications

The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n₁ to another of index n₂is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …

Long-Range Aceo Phenomena In Microfluidic Channel, Diganta Dutta, Keifer Smith, Xavier Palmer

Electrical & Computer Engineering Faculty Publications

Microfluidic devices are increasingly utilized in numerous industries, including that of medicine, for their abilities to pump and mix fluid at a microscale. Within these devices, microchannels paired with microelectrodes enable the mixing and transportation of ionized fluid. The ionization process charges the microchannel and manipulates the fluid with an electric field. Although complex in operation at the microscale, microchannels within microfluidic devices are easy to produce and economical. This paper uses simulations to convey helpful insights into the analysis of electrokinetic microfluidic device phenomena. The simulations in this paper use the Navier–Stokes and Poisson Nernst–Planck equations solved using COMSOL …

High Figure Of Merit Spin Polarized Electron Sources Grown Via Mocvd, Benjamin Belfore, Adam Masters, Deewakar Poudel, Greg Blume, Stephen Polly, Erdong Wang, Seth M. Hubbard, Marcy Stutzman, Joseph M. Grames, Matt Poelker, Matt Grau, Sylvain Marsillac

Electrical & Computer Engineering Faculty Publications

Spin polarized photocathodes are key to the future operation of electron accelerators such as the ones at Thomas Jefferson National Accelerator Facility and Brookhaven National Laboratory. Currently, these photocathodes come in short supply due to limited production by molecular beam epitaxy. By developing a process to implement similar structures using metal organic chemical vapor deposition, the availability of these devices can be increased. In this paper, we detail the implementation of recent photocathode advancements via metal organic chemical vapor deposition process and show an improvement in both polarization and quantum efficiency of our devices compared to those fabricated via molecular …

Design And Commissioning Of An E-Beam Irradiation Beamline At The Upgraded Injector Test Facility At Jefferson Lab, Xi Li, Helmut Baumgart, Charles Bott, Gianluigi Ciovati, Shaun Gregory, Fay Hannon, Mike Mccaughan, Robert Pearce, Matthew Poelker, Hannes Vennekate, Shaoheng Wang

Electrical & Computer Engineering Faculty Publications

The Upgraded Injector Test Facility (UITF) at Jefferson Lab is a continuous-wave superconducting linear accelerator capable of providing an electron beam with energy up to 10 MeV. A beamline for electron-beam irradiation has been designed, installed and successfully commissioned at this facility, aimed at the degradation study of 1,4-dioxane and per- and polyfluoroalkyl substances (PFAS) in wastewater treatment. A solenoid with a peak axial magnetic field of up to 0.28 T and a set of raster coils were used to obtain a Gaussian beam profile with a transverse standard deviation of ∼15.0 mm at the target location. Monte-Carlo simulations using …

Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi

Electrical & Computer Engineering Faculty Publications

Plasma medicine refers to the application of nonequilibrium plasmas at approximately body temperature, for therapeutic purposes. Nonequilibrium plasmas are weakly ionized gases which contain charged and neutral species and electric fields, and emit radiation, particularly in the visible and ultraviolet range. Medically-relevant cold atmospheric pressure plasma (CAP) sources and devices are usually dielectric barrier discharges and nonequilibrium atmospheric pressure plasma jets. Plasma diagnostic methods and modelling approaches are used to characterize the densities and fluxes of active plasma species and their interaction with surrounding matter. In addition to the direct application of plasma onto living tissue, the treatment of liquids …

Srf Cavity Fault Classification And Prediction At Jefferson Lab, Chris Tennant, Adam Carpenter, Lasitha Vidyaratne, Md. Monibor Rahman, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Over the last few years several machine learning projects at Jefferson Lab have had a common focus to optimize operation of superconducting RF (SRF) cavities in the Continuous Electron Beam Accelerator Facility (CEBAF). In this talk we highlight work to identify and classify types of faults from C100-type cavities and then to extend those capabilities to provide real-time fault prediction. Early prediction may enable mitigation strategies to prevent some types of faults. In our approach we apply a two-step fault prediction pipeline. In the first step, a model distinguishes between faulty and normal signals. In the second step, signals flagged …

Grand Challenges In Low Temperature Plasmas, Xinpei Lu, Peter J. Bruggeman, Stephan Reuter, George Naidis, Annemie Bogaerts, Mounir Laroussi, Michael Keidar, Eric Robert, Jean-Michel Pouvesle, Dawei Liu, Kostya (Ken) Ostrikov

Electrical & Computer Engineering Faculty Publications

Low temperature plasmas (LTPs) enable to create a highly reactive environment at near ambient temperatures due to the energetic electrons with typical kinetic energies in the range of 1 to 10 eV (1 eV = 11600K), which are being used in applications ranging from plasma etching of electronic chips and additive manufacturing to plasma-assisted combustion. LTPs are at the core of many advanced technologies. Without LTPs, many of the conveniences of modern society would simply not exist. New applications of LTPs are continuously being proposed. Researchers are facing many grand challenges before these new applications can be translated to practice. …

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina

Electrical & Computer Engineering Faculty Publications

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …

Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski

Electrical & Computer Engineering Faculty Publications

This special feature issue covers the intersection of topical areas in artificial intelligence (AI)/machine learning (ML) and optics. The papers broadly span the current state-of-the-art advances in areas including image recognition, signal and image processing, machine inspection/vision and automotive as well as areas of traditional optical sensing, interferometry and imaging.

Beamline For E-Beam Processing At Uitf, G. Ciovati, C. Bott, S. Gregory, F. Hannon, Xi Li, M. Mccaughan, R. Pearce, M. Poelker, H. Vennekate

Electrical & Computer Engineering Faculty Publications

No abstract provided.

Work-In-Progress: Rapid Development Of Advanced Virtual Labs For In-Person And Online Education, Yiyang Li, Yuzhong Shen, Charles Sukenik, Brian Sanders, Pauline Delacruz, Justin Mason

Electrical & Computer Engineering Faculty Publications

During the closure of K-12 schools and universities thanks to the COVID-19 pandemic, many educators turned to web conferencing tools such as Zoom and WebEx to deliver online lectures. For courses with labs, some teachers provide recorded videos of real labs. Watching recorded lab videos is a passive experience, as the procedures and point of view are fixed, and students do not have any control of the lab and thus miss the opportunity to explore different options, including making mistakes that is important part of the learning process. One approach that holds great potential to enhance laboratory experience for online …

Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.)

Electrical & Computer Engineering Faculty Publications

Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply …

Particle Identification And Tracking In Real Time Using Machine Learning On Fpga, F. Barbosa, L. Belfore, C. Dickover, C. Fanelli, S. Furletov, Y. Furletova, L. Jokhovets, D. Lawrence, D. Romanov

Electrical & Computer Engineering Faculty Publications

This project is a multi-disciplinary endeavour between Physics, Electrical Engineering, and Computer Engineering. The purpose is to develop and implement an FPGA(*) based Machine Learning algorithm for real-time particle identification, filtering, and data reduction. This is important research that can be applied to streaming readout systems being developed now at JLab and other facilities. Real-time data processing is a frontier field in experimental physics, especially in HEP. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented ML elements for real-time …