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NASA NTRS2018

Design Principles for Smallsat SARs

Synthetic Aperture Radar (SAR) is by now a mature remote sensing technique to obtain spatially-resolved radar measurements of terrain. Currently, SAR image data are readily available from an ever-expanding multitude of SAR satellites in Earth orbit. Many spaceborne SAR systems currently in use or planned for the near-term are multifunctional: their designs tend to maximize the menu of image modes available to the end user. They also follow fairly conventional design principles, laid down decades ago, that lead almost inevitably to large antennas and even larger spacecraft. This raises the question: how does one go about designing a SAR system that fits in a Smallsat (<200 kg) form factor? The design principles for Smallsat SARs outlined in this paper have been developed over a twenty-year period in architecting Earth-orbiting SARs such as NASA/JPL’s NISAR and ESA’s Biomass mission, as well as planetary SAR mission concepts. Example mission concepts following this approach will be presented at the end of the paper. These include an S-Band Smallsat geodetic constellation to measure surface deformation, as called for by the 2018 National Academy Decadal Survey for Earth Observation from Space. Another example is a Ka-band cubesat-sized system designed to detect changes on Earth’s surface.

Freeman, Anthony↗

DOE OSTI2026

Acquisitive root exploration strategies help maintain higher peak sap flux rates during summer drought, but more root biomass does not

Roots are responsible for soil water uptake, yet little is known about how variation in fine-root traits relates to whole-tree water movement, particularly during periods of drought. By combining a 3-yr dataset monitoring sap flow rates with measures of fine-root biomass, length, and morphology across 10 tree species, we addressed hypotheses concerning the role of fine-root system size and morphology in determining tree responses to summer drought as well as potential changes in their relative importance under more severe droughts. Greater fine-root biomass and length did not enable trees to maintain high rates of sap flow during drought, whereas the morphological traits, specific root length and specific root area, were linked to sustained sap flow rates during drought. We found that all species, irrespective of root traits, progressively reduced their sap flow under more extreme drought conditions, although more acquisitive root morphology was still associated with smaller reductions. Our results run counter to long-standing assumptions that larger root systems are better able to access soil water and maintain photosynthetic activity during drought. Instead, we find evidence that root morphology at least partially determines the capacity for water uptake and movement as soil moisture declines.

drought↗

NASA NTRS2004

Chondrites and the Protoplanetary Disk, Part 2

Contents include the following: On the Dynamical Evolution of a Nebula and Its Effect on Dust Coagulation and the Formation of Centimeter-sized Particles. The Mineralogy and Grain Properties of the Disk Surfaces in Three Herbig Ae/Be Stars. Astrophysical Observations of Disk Evolution Around Solar Mass Stars. The Systematic Petrology of Chondrites: A Consistent Approach to Assist Classification and Interpretation. Understanding Our Origins: Formation of Sun-like Stars in H II Region Environments. Chondrule Crystallization Experiments. Formation of SiO2-rich Chondrules by Fractional Condensation. Refractory Forsterites from Murchison (CM2) and Yamato 81020 (CO3.0) Chondrites: Cathodoluminescence, Chemical Compositions and Oxygen Isotopes. Apparent I-Xe Cooling Rates of Chondrules Compared with Silicates from the Colomera Iron Meteorite. Chondrule Formation in Planetesimal Bow Shocks: Physical Processes in the Near Vicinity of the Planetesimal. Genetic Relationships Between Chondrules, Rims and Matrix. Chondrite Fractionation was Cosmochemical; Chondrule Fractionation was Geochemical. Chondrule Formation and Accretion of Chondrite Parent Bodies: Environmental Constraints. Amoeboid Olivine Aggregates from the Semarkona LL3.0 Chondrite. The Evolution of Solids in Proto-Planetary Disks. New Nickel Vapor Pressure Measurements: Possible Implications for Nebular Condensates. Chemical, Mineralogical and Isotopic Properties of Chondrules: Clues to Their Origin. Maximal Size of Chondrules in Shock-Wave Heating Model: Stripping of Liquid Surface in Hypersonic Rarefied Gas Flow. The Nature and Origin of Interplanetary Dust: High Temperature Components. Refractory Relic Components in Chondrules from Ordinary Chondrites. Constraints on the Origin of Chondrules and CAIs from Short-lived and Long-lived Radionuclides. The Genetic Relationship Between Refractory Inclusions and Chondrules. Contemporaneous Chondrule Formation Between Ordinary and Carbonaceous Chondrites. Chondrules and Isolated Grains in the Fountain Hills Bencubbinite. Implications of Chondrule Formation in a Gas of Solar Composition. Implications of Meteoritic Cl-36 Abundance for the Origin of Short-lived Radionuclides in the Early Solar System. Size Sorting and the Chondrule Size Spectrum. Comparative Study of Refractory Inclusions from Different Groups of Chondrites. In Situ Investigation of Mg Isotope Distributions in an Allende CAI by Combined LA-ICPMS and SIMS Analyses Photochemical Speciation of Oxygen Isotopes in the Solar Nebula.

Source record↗

NASA NTRS1988

The evoluation of young stellar object disks and their environment

By carrying out direct imaging and spectroscopic observations of young, pre-main sequence stars in nearby molecular clouds researchers have begun: to define the frequency with which disks of approximately solar system size and mass form around young stars, and to understand the timescale for disk evolution; to characterize the early radiation (ultraviolet and keV particle) environment of circumstellar disks through study of evolution of stellar winds, wind/disk interactions and the UV and optical emission characteristics of young stars; and to understand the evolution of the solid and gaseous constituents of disks through observations of absorption features in circumstellar gas, broad emission features produced by organic compounds on grain surfaces, and absorption features (e.g., ice) produced in grain mantles. These programs offer the possibilty of relating results from astrophysical studies of the environment to newly-formed stars to the record of planet formation preserved in the solar system. Researchers completed a spectroscopic survey of 30 T Tauri stars with ages ranging from approximately 2 x 10 to the 5th power to 3 x 10 to the 7th power years. From analysis of (OI) and (SII) emission lines, it was concluded that all but two of the stars in our sample are surrounded by optically opaque disks of dimension approximately 50 AU. The two remaining objects show evidence consistent with partial disk clearing (at an age approximately 3 x 10 to the 6th power year). R and I band CFHT observations yielded detections of disks of dimension approximately 100 AU surrounding 5 additional T Tauri stars.

Strom, Stephen E.↗

NASA NTRS2013

A Tool for the Automated Design and Evaluation of Habitat Interior Layouts

The objective of space habitat design is to minimize mass and system size while providing adequate space for all necessary equipment and a functional layout that supports crew health and productivity. Unfortunately, development and evaluation of interior layouts is often ignored during conceptual design because of the subjectivity and long times required using current evaluation methods (e.g., human-in-the-loop mockup tests and in-depth CAD evaluations). Early, more objective assessment could prevent expensive design changes that may increase vehicle mass and compromise functionality. This paper describes a new interior design evaluation method to enable early, structured consideration of habitat interior layouts. This interior layout evaluation method features a comprehensive list of quantifiable habitat layout evaluation criteria, automatic methods to measure these criteria from a geometry model, and application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In addition to a detailed description of this method, a C++/OpenGL software tool which has been developed to implement this method is also discussed. This tool leverages geometry modeling coupled with collision detection techniques to identify favorable layouts subject to multiple constraints and objectives (e.g., minimize mass, maximize contiguous habitable volume, maximize task performance, and minimize crew safety risks). Finally, a few habitat layout evaluation examples are described to demonstrate the effectiveness of this method and tool to influence habitat design.

Simon, Matthew A.↗

DOE OSTI2024

Luther-Emery liquid and dominant singlet superconductivity in the hole-doped Haldane spin-1 chain

We investigate the pairing tendencies in the hole-doped Haldane spin-1 chain. To allow for doping, we extend the original spin chain Hamiltonian into a fermionic model involving a two-orbital Hubbard chain at intermediate or strong repulsive interaction strengths U and for degenerate orbitals. At half filling and large U, the ferromagnetic Hund's coupling, J H , generates effective spin-1 moments, with antiferromagnetic correlations between sites. Using large-scale density matrix renormalization group calculations, we accurately study the system's behavior under light hole-doping. For U = 1.6 in units of the noninteracting bandwidth and for J H /U ≳ 0.275, we find that singlet pairing dominates the long-distance physics, establishing this system as a promising platform for repulsively mediated superconductivity. We provide concrete examples of materials that could realize the physics described here. We also provide evidence that the system approaches a Luther-Emery liquid state at large system sizes, reminiscent of the behavior of doped one-orbital two-leg ladders at weak coupling, which also have superconducting tendencies. The numerically calculated central charge approaches one in the thermodynamic limit, indicating a single gapless mode as is expected for the Luther-Emery state. Exponents characterizing the power-law decays of singlet pair-pair and charge density-density correlations are determined, and found to approximately satisfy the Luther-Emery identity.

1-dimensional systems↗

NASA NTRS2002

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Precipitation Processes

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and incoming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a cloud-resolving model, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. Dr. Joanne Simpson played a central role in GCE modeling developments and applications. She was the lead author or co-author on more than forty GCE modeling papers. In this paper, a brief discussion and review of the application of the GCE model to (1) cloud interactions and mergers, (2) convective and stratiform interaction, (3) mechanisms of cloud-radiation interaction, (4) latent heating profiles and TRMM, and (5) responses of cloud systems to large-scale processes are provided. Comparisons between the GCE model's results, other cloud-resolving model results and observations are also examined.

Tao, Wei-Kuo↗

DOE OSTI2026

Principles and Options for Designing Battery Energy Storage Zoning Ordinances

Deployment of battery energy storage (BESS) systems, both standalone and as part of hybrid systems paired with generation, has rapidly increased in the United States in recent years as utilities and communities have deployed storage to improve electric grid reliability and act as a cost-effective alternative to larger grid infrastructure. The modular nature of BESS technologies means systems may be built near other existing land uses, creating the potential for conflicts with neighboring landowners that can be managed and mitigated through zoning and permitting requirements established by local jurisdictions. While many cities and counties have adopted ordinances specific to BESS into their local zoning codes, these ordinances vary significantly in their requirements and level of detail. Meanwhile, many other jurisdictions, including those home to proposed or existing BESS projects, lack any specific language related to BESS in their zoning codes. Local planning and zoning officials have limited capacity and may lack the familiarity with BESS technologies needed to develop ordinances or otherwise make reasonable zoning decisions that balance safety, community impacts, and other goals. The resulting uncertainty at the local zoning level has led developers to withdraw projects in some areas and has spurred moratoria or bans on energy storage projects in others. This report intends to provide practical resources for practitioners interested in reasonable and effective local regulation of battery energy storage. It does not present a model zoning ordinance, but rather is intended to complement model ordinances developed by others by providing additional context and analysis regarding the structure of energy storage zoning ordinances and the decision points for local officials. Zoning ordinances at the city, town, and county level across the U.S. were surveyed alongside two template model ordinances to identify common elements and options for regulating the zoning and siting of BESS. Common elements identified and analyzed include definitions and general requirements, including cutoffs or tiers used to apply regulations to different system sizes and the permitted zones where jurisdictions allow BESS to be sited; visual, noise, and aesthetic requirements, including property line setbacks, fencing and visual screening, noise, and lighting requirements; and safety and planning requirements, such as site plans, decommissioning plans or funds, and requirements for access by emergency services. The report also summarizes some of the more unique regulations, including those that place additional restrictions on BESS at the local level.

25 ENERGY STORAGE↗

DOE OSTI2024

Power Electronics Manufacturing Improvements for Heavy-Duty Fuel Cell Vehicles

The Marel Power Solutions project, funded by the U.S. Department of Energy under Award DE-SC0023801, focused on advancing manufacturing techniques for power electronics in heavy-duty fuel cell vehicles. The research aimed to enhance system efficiency, reduce costs, and support broader adoption of hydrogen fuel cell technology. Key areas of investigation included power topology, thermal modeling, system architecture, and accessibility through software tools. Key Accomplishments: 1. Power Topology: - Developed an interleaved boost converter with optimized phase count, leveraging Marel’s proprietary Power Stacks. - Achieved reduced parasitic inductance and resistance, enabling high efficiency in DC-DC converters. 2. Thermal Modeling: - Integrated innovative cooling systems into compact Silicon Carbide (SiC) modules. - Simulations demonstrated the ability to dissipate significant heat (up to 7.5 kW), ensuring device reliability under heavy loads. 3. System Architecture: - Utilized simulation tools to analyze the impact of various fuel cell and vehicle parameters on efficiency. - Highlighted the role of smaller, modular improvements, such as enhanced DC-DC converters, in achieving system-wide gains. 4. Accessibility: - Evaluated and implemented MATLAB/Simulink code generation tools for real-world hardware applications. - Demonstrated the potential for rapid prototyping of custom power systems with reduced development costs. Impact and Benefits: - Efficiency and Cost Reduction: Marel’s cooling technology enhances SiC die performance, reducing the number of dies required and overall system size. - Scalability and Flexibility: The innovations support tailored solutions for diverse applications, from mass transit to mining vehicles. - Sustainability: The research promotes the integration of electrification technologies, helping meet rising energy demands sustainably. Conclusion: The project’s outcomes advance the state of power electronics for hydrogen fuel cell vehicles, enabling more efficient, compact, and cost-effective solutions. These developments lay a foundation for future innovation, contributing to the broader adoption of clean energy technologies in transportation and other industries.

08 HYDROGEN↗

DOE OSTI2026

Classification of dynamical Lie algebras generated by spin interactions on undirected graphs

Dynamical Lie algebras (DLAs) are a versatile tool for various topics that span from the expressibility-trainability of variational quantum algorithms (VQAs), to simulation of many body Hamiltonians. Quantum gates and most of the Hamiltonians of interest consist of local interactions; therefore, the analysis of all possible DLAs generated by 1- and 2-local operators is crucial for quantum simulation and VQAs on current hardware. Previously in [R. Wiersema et al ., npj Quantum Inf. 10 , 110 (2024)], we analyzed the DLAs on linear, circular and all-to-all topologies, and obtained results about their dimensions and algebraic structure. Here, in this work, we extend our analysis into any possible hardware topology and provide a classification of all DLAs generated by Pauli strings on any undirected interaction graph. Our results indicate that the DLAs depend solely on whether the connectivity or interaction graph is bipartite or not. In addition, we find that the non-trivial polynomially scaling DLAs appear only on 1D line or circle topologies, and all other DLAs have dimensions scaling exponentially with the system size. Together with the current VQA literature, our results imply that either the majority of VQAs are non-trainable, or we are yet to understand the role of DLAs on the trainability of VQAs.

Algebraic structures↗

NASA NTRS2005

Development of Particulates and Aerosols Research

During the past year several accomplishments were made for both the Particulate Matter Characterization and Measurement System, (PMCMS) and PAGEMS projects. The PAGEMS focus is to measure particulate emissions as a function of combustor parameters such as inlet temperature, inlet pressure and fuel air ratio. These measurements are used to evaluate combustor performance in hopes of correlating particulate emissions with engine conditions. These measurements have taken place at in-house NASA combustor facilities and off-site facilities. Ths work is unique because particulate measurements at high- pressure conditions are not commonly made. Some calibration of the PAGEMS instrumentation was done as well as minor modifications to the PAGEMS plumbing setup. These led to measurement improvements. The instrumentation and measurement process for PAGEMS was assessed and new instruments such as a thermodenuder, thermal mass flow meters and a cyclone separator were purchased to improve the PAGEMS instrumentation and measurement process. A worksheet was created to simulate varying inlet conditions to the DMA. This worksheet allows the user to assess the error in the measurements when certain conditions exist. Two technical papers were written with the PAGEMS team for the EXCAVATE field project. A paper was also reviewed for an in house publication. Also data was processed and analyzed for another field project (PAX) and will be part of a third PAGEMS paper. Accomplishments were also made with the PMCMS project. The calibration of the radial differential mobility analyzer, (RDMA) in the particle sizing system in the PMCMS was completed and provided satisfactory results. The voltages used for the RDMA depending on the particle of interest were corrected. The measurement capability of the PMCMS was increased by replacing the MetOne CPC with a TSI CPC. Lastly, assistance was provided to three college summer students with calibration of their particulate equipment and Monica Rivera shared her understanding of the aerosol technology with them. She also provided input for their end of the summer presentations. And attended the Aviation and Particle Emissions workshop. This workshop brought together experts in the aircraft particulate emissions field. As a result Ms. Rivera made two significant contacts with academia (UMR) and government (WPAFB) which could lead to future collaboration. She also attended the Aerosol and Particle Measurement Class held at the University of Minnesota. This class refreshed her particulate knowledge and introduced her to new aerosol applications and technology. Furthermore at the class contacts were made with private industry (TSI) and government (WPAFB). Ms. Rivera also enhanced her education by taking an in-house class on aircraft design and operation.

DeWitt, Kenneth↗

DOE OSTI2025

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗

NASA NTRS1980

Automated holographic drop-size analyzer

System analyzes drop-size distribution in liquid-droplet-spray combustion fields. Holographic camera takes "stop-motion" hologram of combustion volume; it is then viewed by vidicon camera connected to digital data-processing system that identifies particles or droplets, determining their size and count, and displays histogram of drop-size distribution in holographic field.

Feinstein, S. P.↗

DOE OSTI2024

Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators

Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗

DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗

DOE OSTI2025

Application of machine learning interatomic potentials in heterogeneous catalysis

Heterogeneous catalysts are crucial in modern societies as they promote sustainability by enabling lower-energy pathways for various chemical reactions. While Density Functional Theory (DFT) computations can provide critical insights into how heterogeneous catalysts operate at the atomic level, they are limited by computational costs and unfavorable scaling with system size. Recently, machine learning interatomic potentials (MLIPs) have emerged as a promising alternative to DFT, offering near-DFT accuracy at significantly reduced cost. Here, in this perspective, we discuss the application of MLIPs in heterogeneous catalyst modeling as a surrogate for DFT. We detail how MLIPs have been applied in thermal catalysis to probe active sites, enable studying complex metallic and nanoporous catalysts, and investigate the reconstruction of catalytic surfaces. We review the use of MLIPs in electrocatalysis and photocatalysis, emphasizing their capabilities in studying transition metal oxide surfaces and solid–liquid interfaces. We also discuss the current limitations of MLIPs, particularly their challenges with transferability and description of non-local interactions. Finally, we conclude by identifying promising and underexplored domains in which MLIPs can further advance our understanding of heterogeneous catalysts.

Catalytic surfaces↗

DOE OSTI2026

Sampling two-dimensional isometric tensor network states

Sampling a quantum system’s underlying probability distributions is an important computational task, e.g., for quantum advantage experiments and quantum Monte Carlo algorithms. Tensor networks are an invaluable tool for efficiently representing states of large quantum systems with limited entanglement. Algorithms for sampling one-dimensional (1D) tensor networks are well-established and utilized in several 1D tensor network methods. In this paper we introduce two novel sampling algorithms for two-dimensional (2D) isometric tensor network states (isoTNS) that generalize existing 1D tensor network sampling algorithms. Our first proposed algorithm performs independent sampling and yields a single configuration together with its associated probability. The second algorithm employs a greedy search strategy to identify high-probability configurations and their corresponding probabilities. Numerical results demonstrate the effectiveness of these algorithms across quantum states with varying entanglement and system size.

Dumitrescu, Eugene [ORNL] (ORCID:0000000158519567)↗