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DOE OSTI2021

Materials challenges and opportunities for quantum computing hardware

Combatting noise on the platform The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general, many-particle quantum states are highly sensitive to noise, which inevitably causes errors in quantum algorithms. Some noise sources are inherent to the current materials platforms. de Leon et al. review some of the materials challenges for five platforms for quantum computers and propose directions for their solution. Science , this issue p. eabb2823

Science & Technology - Other Topics↗

DOE OSTI2019

Low-Overhead In Situ Visualization Using Halo Replay

In situ visualization and analysis is of increasing importance as the compute and I/O gap further widens with the advance to exascale capable computing. Yet, in situ methods impose resource constraints leading to the difficult task of balancing simulation code performance and the quality of analysis. Applications with tightly-coupled in situ visualization often achieve performance through spatial and temporal downsampling, a tradeoff which risks not capturing transient phenomena at sufficient fidelity. Determining a priori visualization parameters such as sampling rate is difficult without time and resource intensive experimentation. We present a method for reducing resource contention between in situ visualization and stencil codes on heterogeneous systems. This method permits full resolution replay through recording halos and the communication-free reconstruction of interior values uncoupled from the main simulation. We apply this method in the computational fluid dynamics (CFD) code HARVEY [1] on the Summit supercomputer. We demonstrate minimal-overhead, in situ visualization relative to simulation alone, and compare the Halo Replay performance to tightly-coupled in situ approaches.

Ames, Jeff↗

DOE OSTI2013

Final Technical Report for "High Energy Physics at The University of Iowa"

Particle Physics explores the very fundamental building blocks of our universe: the nature of forces, of space and time. By exploring very energetic collisions of sub-nuclear particles with sophisticated detectors at the colliding beam accelerators (as well as others), experimental particle physicists have established the current theory known as the Standard Model (SM), one of the several theoretical postulates to explain our everyday world. It explains all phenomena known up to a very small fraction of a second after the Big Bang to a high precision; the Higgs boson, discovered recently, was the last of the particle predicted by the SM. However, many other phenomena, like existence of dark energy, dark matter, absence of anti-matter, the parameters in the SM, neutrino masses etc. are not explained by the SM. So, in order to find out what lies beyond the SM, i.e., what conditions at the earliest fractions of the first second of the universe gave rise to the SM, we constructed the Large Hadron Collider (LHC) at CERN after the Tevatron collider at Fermi National Accelerator Laboratory. Each of these projects helped us push the boundary further with new insights as we explore a yet higher energy regime. The experiments are extremely complex, and as we push the boundaries of our existing knowledge, it also requires pushing the boundaries of our technical knowhow. So, not only do we pursue humankind’s most basic intellectual pursuit of knowledge, we help develop technology that benefits today’s highly technical society. Our trained Ph.D. students become experts at fast computing, manipulation of large data volumes and databases, developing cloud computing, fast electronics, advanced detector developments, and complex interfaces in several of these areas. Many of the Particle physics Ph.D.s build their careers at various technology and computing facilities, even financial institutions use some of their skills of simulation and statistical prowess. Additionally, last but not least, today’s discoveries make for tomorrow’s practical uses of an improved life style, case in point, internet technology, fiber optics, and many such things. At The University of Iowa we are involved in the LHC experiments, ATLAS and CMS, building equipment, with calibration and maintenance, supporting the infrastructure in hardware, software and analysis as well as participating in various aspects of data analyses. Our theory group works on fundamentals of field theories and on exploration of non-accelerator high energy neutrinos and possible dark matter searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗

DOE OSTI2013

miniSMAC2D

In the drive to make exascale computing a reality, significant effort is being invested in efficiently implementing and improving current numerical algorithms on various vendors' newest testbeds acquired by DOE's Advanced Simulation and Computing program. Porting large-scale applications to these testbeds is prohibitive in labor and time. Instead, it is more advantageous to run small-scale programs that capture the essence of the large-scale application and that can be more easily modified, improved, and distributed to other collaborators focused on hardware/software co-design. These small-scale applications are called miniapps are are being developed under the aegis of the Mantevo project.

Barnette, DanielW.↗

DOE OSTI2012

Thermochimica User Manual – v1.0

A new software library called Thermochimica has been developed that determines a unique combination of phases and their compositions at thermochemical equilibrium. The development of Thermochimica in this research is aimed at direct integration in multi-physics codes and to address several concerns with using commercially available software, including: licensing entanglements associated with code distribution, access to the source code, convenient incorporation into other codes with quality assurance considerations, and computational performance. In particular, significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. The overall goal of this undertaking is to provide an open source computational tool to enhance the predictive capability of multiphysics codes without significantly impeding computational performance. The purpose of this document is to describe the design of Thermochimica and the basic use of the software library. A brief background to computational thermodynamics and the conditions for thermodynamic equilibrium is given in §2, details of the code development is discussed in §3, details of building and compiling Thermochimica is given in §4, specific programming details for each subroutine in the library is given in the Appendix. The open license for Thermochimica is provided with the source code. As is always the case, software quality assurance (SQA) is an extremely important subject in software development. The importance of this warrants an independent document dedicated to SQA, which has been developed in parallel to this document. The subject of thermodynamic model validation is also of extreme importance in scientific computing and must be given careful attention. To be clear, this document is concerned with the development and use of a general thermodynamic solver and the validation of any models should be included in the discussion of the development of a thermodynamic model that is specific to a particular system.

36 MATERIALS SCIENCE↗

DOE OSTI2023

The advanced characterization, post-irradiation examination, and materials informatics for the development of ultra high-burnup annular U-10Zr metallic fuel

U-Zr metallic fuel is a promising fuel candidate for Gen Ⅳ fast spectrum reactors. Previous experimental irradiation campaigns showed that the sodium thermal bonded U-10Zr fuel design can achieve a burnup of 10% fissions per initial heavy metal atom (FIMA). Advanced metallic fuel designs are pushing the burnup limit to 20% or even 30% FIMA. To achieve the higher burnup and eliminate the pyrophoric sodium, a prototypical annular fuel has been designed, fabricated, clad with HT-9 in the Materials and Fuels Complex, and irradiated in the Advanced Test Reactors of Idaho National Laboratory (INL) to a peak burnup of 3.3% FIMA. During irradiation, the mechanical contact between fuel and cladding acts as a thermal bond. The irradiation lasted for 132 days in the reactor. Recently, the archived fresh and irradiated fuel samples were characterized using advanced characterization capabilities in the Irradiated Materials Characterization Laboratory (IMCL) of INL. This article summarizes the results of advanced characterization and computer vision-based materials informatics to reveal the irradiation effects on U-Zr metallic fuel. Future work will focus on further implementation of advanced characterization and statistical data mining to improve the fidelity of fuel performance modeling and support U-Zr metallic fuel qualification for fast spectrum reactors.

Yao, Tiankai↗

DOE OSTI2013

miniSMAC2D

Barnette, Daniel W.↗

DOE OSTI2026

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗

DOE OSTI2026

Future Generation High Performance Computing Center (FG-HPCC): RFI Technical Considerations

Lawrence Livermore National Security, LLC (LLNS) is interested in receiving information about technologies that could be available in the 2029-2030 timeframe that may serve to enable the vision for a Future Generation High Performance Computing (HPC) Center (FG-HPCC) described in this document. The future HPC Center vision has been conceived to meet the future mission needs of the Advanced Simulation and Computing (ASC) Program within the National Nuclear Security Administration (NNSA). LLNS envisions a center composed not of many independent clusters, but of heterogeneous elements accessible to users as a single system. The capabilities will be integrated to create a scalable, flexible, yet tightly coupled computing center capable of integrated HPC, AI, and cloud-like workloads.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

2025 Workshop on Envisioning Frontiers in AI and Computing for Biological Research: Position Papers

This workshop aims to identify key research directions for transforming biology using artificial intelligence (AI), machine learning (ML) and computational methods to facilitate the discovery of new behaviors, mechanisms, and designs of biological processes relevant to DOE missions, underpinning a broader U.S. bioeconomy. By developing novel AI/ML technologies to analyze and interpret complex biological data, researchers can organize and simulate biological processes at various scales as well as advance predictive understanding and manipulation of biological systems. This integration of computation, experimentation, and next-generation experimental technologies can lead to discoveries in new biological behaviors and mechanisms relevant to DOE missions. The focus is on how advanced computational and mathematical methods can impact this mission by exploring digital twins, foundation models, automated laboratory experiments, modeling of complex living systems, and data-driven approaches for the biodesign of plants and microbial systems. While data management is important, it is not the primary focus of this workshop, which will assess the current state, trends, and AI/ML challenges at the interface between biology and computational science to identify opportunities for high-impact research at their intersection. The goal is to define research needs and opportunities that align with biological sciences, computational sciences, and applied mathematics research.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Resolving the biophysics of axon transmembrane polarization in a single closed-form description

When a depolarizing event occurs across a cell membrane there is a remarkable change in its electrical properties. A complete depolarization event produces a considerably rapid increase in voltage that propagates longitudinally along the axon and is accompanied by changes in axial conductance. A dynamically changing magnetic field is associated with the passage of the action potential down the axon. Over 75 years of research has gone into the quantification of this phenomenon. To date, no unified model exist that resolves transmembrane polarization in a closed-form description. Here, a simple but formative description of propagated signaling phenomena in the membrane of an axon is presented in closed-form. The focus is on using both biophysics and mathematical methods for elucidating the fundamental mechanisms governing transmembrane polarization. The results presented demonstrate how to resolve electromagnetic and thermodynamic factors that govern transmembrane potential. Computational results are supported by well-established quantitative descriptions of propagated signaling phenomena in the membrane of an axon. The findings demonstrate how intracellular conductance, the thermodynamics of magnetization, and current modulation function together in generating an action potential in a unified closed-form description. The work presented in this paper provides compelling evidence that three basic factors contribute to the propagated signaling in the membrane of an axon. It is anticipated this work will compel those in biophysics, physical biology, and in the computational neurosciences to probe deeper into the classical and quantum features of membrane magnetization and signaling. It is hoped that subsequent investigations of this sort will be advanced by the computational features of this model without having to resort to numerical methods of analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗

DOE OSTI2016

Simulation and Optimizing Groundwater Investigations, Conceptual Design Analysis, Model Calibration and Remedial Design Using Parallel Numerical Methods: Theory and Application - 16578

Optimization of environmental restoration efforts at complex groundwater sites involves the development of a conceptual and often numerical flow and transport models. Typically, a limited number of simulations are done to assess the impact of parameter uncertainty, to evaluate remedial alternatives and develop a remedy, or to modify an existing remedy. A limited number of simulations are performed because each simulation can take upwards of several hours per simulation and until now the ability to conduct the 100's to 1000's of simulations needed to derive an optimal remedy was beyond the reach of the everyday practitioner. HGL has developed and implemented new parallel simulation and optimization methods in their software and has successfully deployed applications on high performance Cloud-based computing platforms. This advancement removes the impediment of burdensome and unpredictable runtime requirements these types of projects have typically exhibited using heuristic trial-and-error or even automated serial computation approaches. A parallel numerical solver has been added to the subsurface flow and transport simulator MODFLOW-SURFACT{sup TM} and has demonstrated reductions in solution time by as much as a factor of 9.8. This is accomplished by distributing the numerical computations of every time step over multiple processors. The integrated parallel simulation and optimization method uses the breadth and depth search approach; iteratively producing sets of tens or 100's of candidate solutions that are evaluated concurrently instead sequentially (i.e. one model evaluation at a time). Solutions within 80-100% of the globally optimal solution are regularly found expending only 5-10% of the usual computational effort using this new parallel optimization method (reducing computation effort by 10 to 20 times). Distributing optimal search runs across multiple processors additionally reduces calendar time to solutions. Practitioners evaluating multiple conceptual site models, model calibration by auto-calibration methods and remedial design by heuristics can enjoy significant reductions in model solution time by using the parallel numerical matrix solver in the physics-based simulator. Combining investigation and design analysis with breadth and depth parallel optimization methods, projects at the fringe of practical optimization, along with projects that were beyond the reach of formal optimization methods are now wholly feasible and tractable optimization problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Exemplar for simulation challenges: Large-deformation micromechanics of Sylgard 184/glass microballoon syntactic foams.

Sylgard® 184/Glass Microballoon (GMB) potting material is currently used in many NW systems. Analysts need a macroscale constitutive model that can predict material behavior under complex loading and damage evolution. To address this need, ongoing modeling and experimental efforts have focused on study of damage evolution in these materials. Micromechanical finite element simulations that resolve individual GMB and matrix components promote discovery and better understanding of the material behavior. With these simulations, we can study the role of the GMB volume fraction, time-dependent damage, behavior under confined vs. unconfined compression, and the effects of partial damage. These simulations are challenging and push the boundaries of capability even with the high performance computing tools available at Sandia. We summarize the major challenges and the current state of this modeling effort, as an exemplar of micromechanical modeling needs that can motivate advances in future computing efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Keeping Classified Information Secret in the World of Quantum Computing

Quantum computing is a technology that promises to revolutionize computing by speeding up key computing tasks in are as such as machine learning and solving otherwise intractable problems.Some influential American policymakers, scholars, and analysts are extremely concerned about the effects quantum computing will have on national security. Similar to the way space technology was viewed in the context of the US-Soviet rivalry during the Cold War, scientific advancement in quantum computing is seen as a race with significant national security consequences, particularly in the emerging US-China rivalry.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Results of an In-Field Validation Exercise in Support of Wide-Area Environmental Sampling

The National Nuclear Security Administration’s (NNSA) Office of Nonproliferation and Arms Control (NA-24) is evaluating Wide-Area Environmental Sampling (WAES) as an additional safeguards verification tool for the International Atomic Energy Agency to detect undeclared nuclear activities. The NNSA is evaluating strategies for conducting a generic WAES campaign, the cost of a WAES campaign, and the effect of technological advancements that have occurred since the last major WAES review in 1999. Until now, the NNSA effort has focused on tabletop exercises (TTXs) in which high-performance computing allows for advanced modeling and simulation efforts to be applied to the WAES question. Although the modeling and simulations used in the TTXs are extremely valuable, field campaigns are still needed to validate the assumptions that underpin the models and the modeling process itself. During a 7 week period beginning in May 2023 and ending in June 2023, which included 4 weeks of active field collections, a multilaboratory team conducted its first in-field validation exercise. Prior to the in-field exercise, abbreviated TTXs were conducted to estimate the performance of all collection systems to be used during the field test. These TTXs guided the selection of materials to be released and the placement of the collection system. Based on these determinations, materials were procured to use in the field test, and an injection/release system was designed, built, and installed at the test facility. Background samples were collected during weeks one and four, and environmental collections against active releases were conducted during weeks two and three. The goals of this validation exercise included a demonstration of (1) the ability to provide controlled releases of particulates of surrogate materials, (2) the fielding and operation of collection systems (including deposition and active air collectors), and (3) the flexibility to revise equipment and campaign plans in the field. This paper presents the results and preliminary conclusions for this initial validation test. Based on these results, subsequent field campaigns are anticipated and will include the addition of other released materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗