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At least 37 records · Page 2

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗

Selective Recovery of Critical Minerals from Simulated Electronic Wastes Via Reaction‐Diffusion Coupling

Abstract Atom‐ and energy‐efficient chemical separations are urgently needed to meet the surging demand for critical materials that has strained supply chains and threatened environmental damage. In this study, we used reaction‐diffusion coupling to separate iron, neodymium, and dysprosium ions from model feedstocks of permanent magnets, which are typically found in electronic wastes. Feedstock solutions were placed in contact with a hydrogel loaded with potassium hydroxide and/or dibutyl phosphate, resulting in complex precipitation patterns as the various metal ions diffused into the reaction medium. Specifically, we observed the precipitation of up to 40 mM of iron from the feedstock, followed by the enrichment of 73 % dysprosium, and the extraction of >95 % neodymium product at a further distance from the solution‐gel interface. We designed a series of experiments and simulations to determine the relevant ion diffusivities, D Nd =5.4×10 −10 and D Dy =5.1×10 −10 m 2 /s, and precipitation rates, k Nd =1.0×10 −5 and k Dy =5.0×10 −3 m 9 mol −3 s −1 , which enabled a numerical model to be established for predicting the distribution of products in the reaction medium. Our proof‐of‐concept study validates reaction‐diffusion coupling as an effective and versatile approach for critical materials separations, without relying on ligands, membranes, resins, or other specialty chemicals.

Wang, Qingpu [Physical and Computational Sciences ↗

Production of alternate realizations of DESI fiber assignment for unbiased clustering measurement in data and simulations

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multiphysics Simulation of KRUSTY Warm Critical Experiments Using MOOSE Tools

A series of critical experiments were performed during the Kilopower Reactor Using Stirling TechnologY (KRUSTY) project, producing valuable and unique data for the validation of corresponding microreactor models. In this paper, the development of a high-fidelity multiphysics model of the KRUSTY microreactor within the MOOSE ecosystem is presented, with a focus on the microreactor configuration during the warm critical experiments. The model was established by coupling a deterministic neutronics model using the Griffin code, with a BISON thermomechanical model. The multiphysics model successfully simulated the KRUSTY 15 ¢ and 30 ¢ warm critical reactivity insertion experiments in satisfactory agreement with the experimental measurement data. In conclusion, the modeling results demonstrated the performance of MOOSE-based multiphysics tools in microreactor simulations, and spotlighted the useful applications of these tools in supporting microreactor design, qualification, and licensing activities.

KRUSTY↗

A radioisotope - enabled reactive transport model for deep vadose zone carbon

In mountainous regions, which constitute the principle source of recharge to major rivers and regional aquifers, infiltration occurs through fractured, partially saturated, weathered bedrock that acts as a boundary layer between saturated aquifers and surface soil. Commonly this deep vadose zone (DVZ) is many meters thick, and yet its role in regulating the generation, retention and mobility of reactive solutes, including nutrients, contaminants and weathering products, is largely unknown. In particular, many of the key reactions that drive the formation of the weathered DVZ and the quality of water moving through it are redox processes, regulated by the availability of organic carbon and oxygen below the soil layer. The role of the DVZ is thus also poorly constrained in the context of carbon stocks and mobility, particularly in lithologies that are naturally high in organic carbon, such as shales. The overarching hypothesis of this study is that upland regions developed in geologic settings with abundant petrogenic carbon store and actively cycle carbon in the weathered DVZ below the soil and above the water table at rates that are significant and currently unconstrained. In order to quantify this cycling, the current study combines novel instrumentation techniques allowing new direct sampling of DVZ systems with advanced numerical reactive transport simulations of carbon transport and transformation. Critically, these simulations will explicitly treat the three isotopes of carbon (the abundant 12C, the stable rare 13C and the radioactive 14C) in a unified framework, thus clearly parsing between the contributions of modern surface derived carbon and lithologic carbon sources in integrated measurements of fluid and gas phase fluxes. This novel model capability will be applied to test the role of DVZ carbon cycling as a regulator of water quality and geological weathering in two complementary field sites both located in organic carbon rich shale lithologies. The first is the Eel River Critical Zone Observatory (ERCZO) in Mendocino County, California, and the second is the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area (SFA) in the East River watershed, near Crested Butte, Colorado. At the ERCZO, a novel vadose zone monitoring system has been installed in a 20 m thick, partially saturated, weathered shale hillslope, and preliminary data already indicate substantial CO2 flux generated many meters below the soil surface. At the SFA field site, an instrumented hillslope transect indicates a more complex multi-dimensional fluid and solute transport regime, which will serve as a key test of the calibrated models. Collectively, this project will advance understanding of the cycling of carbon belowground and in relation to transport pathways across the poorly constrained DVZ characteristic of primary water recharge areas. The key product of this work will be enhanced isotope simulation capabilities that are robust and publicly available for application across a broad diversity of systems.

58 GEOSCIENCES↗

Landau-Forbidden Quantum Criticality in Rydberg Quantum Simulators

The Landau-Ginzburg-Wilson theory of phase transitions precludes a continuous transition between two phases that spontaneously break distinct symmetries. However, quantum mechanical effects can intertwine the symmetries, giving rise to an exotic phenomenon called deconfined quantum criticality (DQC). Here, in this Letter, we study the ground state phase diagram of a one-dimensional array of individually trapped neutral atoms interacting strongly via Rydberg states, and demonstrate through extensive numerical simulations that it hosts a variety of symmetry-breaking phases and their transitions including DQC. We show how an enlarged, emergent continuous symmetry arises at the DQCs, which can be experimentally observed in the joint distribution of two distinct order parameters, obtained within measurement snapshots in the standard computational basis. Our findings highlight quantum simulators of Rydberg atoms not only as promising platforms to experimentally realize such exotic phenomena, but also as unique ones allowing access to physical properties not obtainable in traditional experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

AI Denoising to Accelerate Detector Simulation

Detector simulation is critical to experimental HEP; however this simulation (commonly done through toolkits such as Geant4) is computationally intensive. Performance can be improved somewhat through technical optimization, but more is needed. Using machine learning (ML) to accelerate simulation is a promising field, however efforts to use generative adversarial networks (GANs) or optimized autoencoders have faced issues. Using convolutional neural networks (CNNs) for denoising has been successful in non-HEP applications such as image processing. This poster investigates the efficacy of using CNNs to denoise Geant4 simulations. This could increase the accuracy of simulations performed under settings designed to increase computational efficiency.

Franklin, Lena↗

Validation of New MCNP6.3 Features for Critical and Subcritical Benchmark Simulations [Slides]

A separate MCNP6.3 V&V document reports on all the default calculations for all test suites was introduced. Here, we look at new optional features of the MCNP6.3 code. Then, Fission-matrix-based options with Convergence and population testing and Automated acceleration of the fission source and Doppler Broadening Resonance Correction and HDF5 Particle Track Output (PTRAC) and Validation benchmarks: criticality, Rossi-α, and subcritical multiplication. All the new MCNP6.3 options give statistically equivalent results and should be considered for default usage in criticality and subcritical multiplication calculation work. Discussed are two separate papers at the upcoming 2023 International Conference on Nuclear Criticality Safety (ICNC 2023) that give more details on the results presented here.

97 MATHEMATICS AND COMPUTING↗

SCALE HTR-PROTEUS Benchmark Model

This dataset contains input and result files of computational simulations of HTR-PROTEUS benchmark with the latest version of SCALE code system. The simulations cover criticality control rod worth calculations as well as sensitivity analysis and uncertainty quantification. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Large-Area Lasing in Nanoscale Complex Media: The Critical Role of Local Dielectric Environment

Controlling how electromagnetic waves interact with complex media is critical for applications in imaging and focusing. Such lightwave interactions with complex media can lead to dramatic optical effects like lasing. While much work in random lasing focus on understanding how gain and scattering co-operatively generate lasing, little work has focused on how to manipulate the lasing threshold without modifying the structural disorder. Here, a simple, mostly unexplored, strategy is demonstrated that employs atomic layer deposition (ALD) to tune the local near-field environment while preserving the underpinning disorder—controlling lasing in a nanoscale complex medium on a large scale (>cm 2 ). The nanoscale complex medium is a quasi-2D system of coupled zinc oxide nanospheres with overall thickness deep in the sub-wavelength regime (≈λ/4). Near-ultraviolet femtosecond spectroscopy probes the broadband response of the gain nanomaterial, details how ALD process fundamentally modifies the fast-picosecond and slow-nanosecond carrier dynamics, and informs on the relevant timescales critical for lasing. Full-field electromagnetic simulations provide critical insights about how near-field dielectric environment modifies the nanostructure's scattering cross-section, which ultimately results in enhanced lasing. Importantly, these results highlight a simple path to control how electromagnetic waves interact in a complex medium, a key step toward large-scale implementation of complex lasers.

36 MATERIALS SCIENCE↗

Measuring Critical Fuel Properties for Simulations to Accelerate Fuel Qualification

NREL's sustainable aviation fuel (SAF) research in the area of fuel properties and end use is focused on accelerating SAF development and deployment. This will be achieved by close collaboration with BETO program researchers on fuel property measurement and development of structure-property relationships. Additionally, fuel properties measured at often extreme engine operating conditions will be measured, and will be used as inputs to exascale ready simulations of aviation combustion turbines to reveal impacts of properties on turbine operation. This research will potentially lead to a widening of the allowable fuel property range for SAF, expanding SAF production process options and production volumes.

ADVANCED PROPULSION SYSTEMS↗

Critical Assemblies: Dragon Burst Assembly and Solution Assemblies

This work reviews the historical literature associated with the Dragon experiment and water boiler reactors operated at Los Alamos during the Manhattan Project. Frisch’s invited talk given at the American Nuclear Society’s Fast Burst Reactor Conference held at the University of New Mexico in Albuquerque, New Mexico, in 1969 is quoted. From the literature review, basic models for the Dragon experiment and for a water boiler–type assembly (aqueous homogeneous reactor) were created that can be used for conducting multiphysics simulations for criticality excursion studies. This methodology utilizes the coupled neutronic-hydrodynamic method to perform a time-dependent dynamic simulation of a criticality excursion. MCNP® was utilized to calculate important nuclear kinetic parameters that were incorporated into the models. Simulation results compare reasonably well with historic data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Critical design load case fatigue and ultimate failure simulation for a 10-m H-type vertical-axis wind turbine

While previous studies investigating critical VAWT design load cases have focused on large and relatively flexible Darrieus designs, the bulk of current commercial products seeking certification fall in the relatively small, stiff, and H-type configuration, such as the XFlow Energy Corporation turbine that this study compares against. Understanding the critical design load case impacts for both fatigue and ultimate failure for this size and type of VAWT are imperative for certification. The abil

Brownstein, Ian↗

Long-Range Dispersion Governs the Behavior of Near-Critical Fluids: Universal Scaling and Implications for Accurate Molecular Simulation

Computer simulations of near-critical and supercritical fluids often deviate from experimental results, a discrepancy commonly attributed to force-field resolutions and inaccuracies. We demonstrate that these errors primarily stem from using finite cutoff schemes for dispersion interactions, which become effectively long-range as the correlation length grows near the critical point. By employing the smooth particle-mesh Ewald method to account for full long-range dispersion, we show that coarse-grained models can also achieve high quantitative accuracy for n-undecane and propylbenzene. This approach enables the precise determination of density fluctuations and correlation lengths, which exhibit universal critical scaling and depend on the molecular size and shape. Our findings resolve a longstanding debate in molecular simulations of near-critical fluids, establishing that capturing long-wavelength fluctuations is essential for bridging the gap between the microscopic behavior and macroscopic critical phenomena.

Chen, Guang↗

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗