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Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conceptual design of HTS magnets for fusion nuclear science facility

Second-generation high temperature superconductors (HTS) are available for producing >20 T at the magnet bore compared to 13–16 T for lower temperature superconducting (LTS) toroidal field magnets proposed in recent fusion energy systems studies (FESS) of Fusion Nuclear Science Facility (FNSF). HTS may enable higher fusion power density and smaller device size. High current density cables of multi-layered REBCO tapes have achieved >10 kA at 4–20 K operation in short sample tests for fusion. High current density cables are required for engineering design of FNSF to allow space for interior plasma components. High current density HTS magnets are particularly attractive in reducing the size of a fusion device, beneficial for compact tokamaks, due to their space constraints. Successful HTS magnet development may enable the design of smaller and cheaper fusion pilot plants with a mission of demonstrating net electricity. It may also offer significant cost and performance advantages in non-fusion applicants such as nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI). Furthermore, we developed HTS magnet design concepts for a compact FNSF radial build in order to define the coil size, winding pack mechanical loading and engineering requirements. Partnering with vendors in the US, PPPL is also testing high current cable prototypes aiming at enabling low cost cable technology toward 100 A/mm 2 engineering current density over the winding pack desired in high field model coil development for compact fusion pilot plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Establishment of a Nationwide Plasma Science and Fusion Energy Certification and Apprenticeship Programs

Here we propose the establishment of a national Plasma Science and Fusion Energy training program that will combine professional development certification courses with hands-on apprenticeship opportunities. The program should be developed by a collaboration of stakeholders (academia, national laboratories, and industry) and should offer pathways for students from community colleges (CCs), minority-serving institutions (MSIs), high school graduates, and veterans. We argue that certification courses offer fast and flexible discipline-specific education that can be rapidly translated into marketable skills through hands-on apprenticeship opportunities. Furthermore, we first list major findings and recommendations related to the fusion workforce and discuss how to address them through the establishment of the proposed training program. We then highlight the appropriateness of this format for engagement with CCs, MSIs, high schools, and veteran employment services. In the final section, we provide a strategy for the establishment of the program, along with a tentative timeline and projected costs.

Certification↗

Edge and scrape-off layer modeling for a Fusion Nuclear Science Facility with tungsten walls; a summary report for 2019-21

This report summarizes model development and simulations for the edge/scrape-off layer (SOL) region of a Fusion Nuclear Science Facility (FNSF) as part of the DOE Fusion Energy Systems Studies project. An overview of the FNSF device is given in Ref. 1. Our earlier related modeling of FNSF in the 2015-16 timeframe is reported in Ref. 2, and similar work on the ARIES ACT-1 tokamak device is described in Ref. 3. During 2017-18, we contributed to the analysis of a liquid lithium wall for FNSF [4].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum computing for fusion energy science applications

This is a review of recent research exploring and extending present-day quantum computing capabilities for fusion energy science applications. We begin with a brief tutorial on both ideal and open quantum dynamics, universal quantum computation, and quantum algorithms. Then, we explore the topic of using quantum computers to simulate both linear and nonlinear dynamics in greater detail. Because quantum computers can only efficiently perform linear operations on the quantum state, it is challenging to perform nonlinear operations that are generically required to describe the nonlinear differential equations of interest. In this work, we extend previous results on embedding nonlinear systems within linear systems by explicitly deriving the connection between the Koopman evolution operator, the Perron–Frobenius evolution operator, and the Koopman–von Neumann evolution (KvN) operator. We also explicitly derive the connection between the Koopman and Carleman approaches to embedding. Extension of the KvN framework to the complex-analytic setting relevant to Carleman embedding, and the proof that different choices of complex analytic reproducing kernel Hilbert spaces depend on the choice of Hilbert space metric are covered in the appendixes. Finally, we conclude with a review of recent quantum hardware implementations of algorithms on present-day quantum hardware platforms that may one day be accelerated through Hamiltonian simulation. We discuss the simulation of toy models of wave–particle interactions through the simulation of quantum maps and of wave–wave interactions important in nonlinear plasma dynamics.

Joseph, I. (ORCID:0000000255400840)↗

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗

Steady state thermo-mechanics and material property definition framework for analyzing DCLL blanket in the fusion nuclear science facility

In this work, a thermo-mechanics model that relies on creating the material property definition framework (MPDF) and multiphysics coupling of the heat transfer and the solid mechanics modules is developed to determine the structural integrity of the recently designed dual cooled lead lithium (DCLL) inboard blanket (IB) for the Fusion Nuclear Science Facility under steady state loads. The MPDF is called to supply fusion relevant neutron irradiation and temperature induced changes in material properties during multiphysics finite element runs, and PbLi temperature profiles are used to approximate Magnetohydrodynamics effect and the nuclear volumetric heating on the PbLi. Neutron irradiation and temperature induced reduction of the yield and ultimate strengths of F82H steel at the first wall (FW) are quantified for one year. A blanket in an assembly with gaps between blanket sectors and another blanket in an assembly with no gaps between blanket sectors, both exposed to radiation damage that lasted for one year are analyzed. Analysis using the elastic ITER structural design criteria for in-vessel components (ITER SDC-IC) design rules and a linear isotropic-hardening-type elastoplastic material model are used where most appropriate. The IB blanket with gaps between blanket sectors will withstand the steady state combined thermal and coolant loads for one year operational period but will fail if no gaps are allowed between blanket sectors. It is recommended that a gap of about 7.62 mm should be provided between IB blanket sectors during assembly which would close up during service, stop neutron streaming, reduce stresses and reduce bending of the FW into the scrape-off layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Earth Science Data Fusion with Event Building Approach

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

Lukashin, C.↗

Analysis and design of fast flow liquid Li divertor for fusion nuclear science facility (FNSF) using coupled plasma boundary and LM MHD/heat transfer codes *

The SOLPS-ITER code is utilized to analyze the boundary plasma associated with a fast-flow lithium (Li) divertor configuration in the fusion nuclear science facility (FNSF) tokamak and identify operational regimes with acceptable divertor and core conditions. Plasma transport from the SOLPS-ITER code has been coupled with a liquid metal (LM) MHD/heat transfer code to model a Li open-surface divertor design and assess its impact on the scrape-off-layer (SOL) and core plasma performance. Simulations with only Neon (Ne) impurity seeding have been conducted to evaluate its impact on meeting FNSF design demands for the divertor and upstream plasma parameters. Simulation results indicate that Ne seeding significantly mitigates divertor heat flux but potentially reduces both upstream electron and main ion density due to fuel dilution. The combined application of Ne seeding and deuterium (D 2 ) puffing is required to satisfy the FNSF design requirements on upstream density ($n^{OMP}_{e,sep}$~1× 10 20 m -3 ) and divertor energy flux ($q^{Odiv}_{\bot,max}$<10 MW m -2 ). D 2 puffing plays a role in counteracting upstream density drops and augmenting energy and momentum losses through atomic and molecular processes. The inlet Li flow velocity is systematically varied across a wide range to identify acceptable flows and corresponding LM surface temperatures. This comprehensive analysis identifies the acceptable Li flow parameters, LM surface temperature, and emitted Li fluxes necessary to meet the major design constraints. The emitted Li fluxes exhibit minimal impact on the main plasma at surface temperatures up to approximately ~525 °C, corresponding emitted Li fluxes of up to φ Li ~2X10 23 atoms s -1 . Uncertainties in the Li emission processes from the surface are also investigated, primarily influencing Li loss in the lower surface temperature range (<525 °C), with simulation results indicating a minor impact on the divertor and upstream plasma. Conversely, evaporation predominantly drives the Li loss processes at higher surface temperature ranges (>525 °C), contaminating both the divertor and upstream plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Introduction to Special Issue on the Early History of Nuclear Fusion

This introductory paper to the special issue of Fusion Science and Technology commemorates early research on fusion conducted at Los Alamos (the singular entity denoted Los Alamos Laboratory/Los Alamos Scientific Laboratory/Los Alamos National Laboratory at different times is designated “Los Alamos” in this paper) in support of the eventual H-bomb program. We survey the historical origins of the thermonuclear program, what was known of fusion reactions at the outbreak of the war, and the remarkable breakthroughs involving particularly the prospect of deuterium-tritium (DT) reactions conducted during the war, and we summarize the papers in this volume. Much of the nuclear fusion technical history presented herein has not been previously reported. Papers describe aspects of fusion science during these days, on shock hydrodynamics and on electron-radiation coupling, and on nuclear physics including the discoveries of resonances in both the DT cross section and in the lithium tritium-breeding cross section. Three papers follow our colleague Mark Paris’s finding Arthur Ruhlig’s 1938 paper on the first observation of DT fusion: one on how it influenced subsequent Manhattan Project research, another on a modern calculation of that historic experiment, and a third that has repeated the experiment using modern experimental capabilities. Other papers discuss how the first H-bomb test, Ivy Mike, led to the discovery of the new elements einsteinium and fermium and how the DT fusion processes played a key role in our universe’s development after the Big Bang. We also present a paper that analyzes the pioneering Cambridge University 1934 experiment by Marcus Oliphant, Paul Harteck, and Ernest Rutherford where deuterium-deuterium fusion was first observed and that describes how Ernest Lawrence missed identifying fusion in 1933. Finally, we present a summary of early concepts for controlled fusion energy that grew out of wartime discussions at Los Alamos. The papers show how J. Robert Oppenheimer played a leading technical role in the early developments of the H-bomb, before his later opposition—our first paper in this issue addresses the U.S. Department of Energy’s 2022 vacation of the earlier 1954 decision to revoke his security clearance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science Addendum

Activation detectors developed at LLNL for measuring real-time neutron fluence from fusion sources are used in the broader fusion community. The recommended fluence operating range of this diagnostic is 5x10 2 – 1x10 6 n/cm2. The upper limit on this fluence range is set by the dead time caused by data transfer between the detector and data acquisition computer. Delaying the start of counting is a possible strategy to operate these detectors in higher fluences.

42 ENGINEERING↗

Leading magnetic fusion energy science into the big-and-fast data lane

To crack the code of unlimited clean energy from magnetic fusion, researchers collaborate among numerous facilities that are scattered around the globe. Probing hot fusion plasmas with sophisticated diagnostics, they routinely generate fast streams of high-dimensional time-series data. We present the adaptation of a production code-base for a plasma diagnostic to the big-and-fast data lane. The new code-base is used to stream measurements, made in Korea, into a Top-15 computing facility in the US for remote analysis. We discuss software and design choices made for this new HPC-enabled scientific workflow.

Kube, Ralph↗

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

Artificial Intelligence (cs.AI)↗

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

Optical design and efficiency measurement of an extreme ultraviolet high-resolution spectrometer for unresolved transition array research

Understanding the structures of the unresolved transition array (UTA) observed in extreme ultraviolet (EUV) spectra from many-electron atoms is crucial for various applications, including fusion science and nanolithography. Here, to measure the fine structure of the UTA from tungsten and tin at around 5 and 13.5 nm at the Tokyo electron beam ion trap, we developed a high-resolution EUV spectrometer. The designed spectrometer achieves a resolving power of λ/dλ > 5000 at 5 and 13.5 nm. The fabricated large-area grating was experimentally examined at beamline BL5B of the UVSOR synchrotron facility to evaluate the diffraction efficiencies and their variation across the ruled area. The measured diffraction efficiencies are 0.65% ± 0.07% at 5 nm (second order) and 7.9% ± 0.2% at 13.5 nm (first order). The variation in the diffraction efficiency across the ruled area is 2.2%, 13.6%, and 10.0% in zeroth, first, and second order diffractions, respectively. The discrepancies in diffraction efficiencies between the experiments and the calculations were 5.2%, 29%, and 35% for the zeroth, first, and second diffraction orders, respectively.

47 OTHER INSTRUMENTATION↗

Fusion Energy Sciences Network Requirements Review: Mild-cycle Update

The US Department of Energy (DOE) Office of Science (SC) world-class research infrastructure provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗