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At least 217 records · Page 12

Big Data Mining for Assessing Calibration of Building Energy Models

Residential and commercial buildings in China, India, the United States (US), United Kingdom (UK), and Italy consume 39-45% of each nation's primary energy. Building energy models can be used to automatically optimize the return-on-investment for retrofits to improve a building’s energy efficiency. However, with an average of 3,000 building descriptors necessary to accurately simulate a single building, there is a market need to reduce the transaction cost for creating a more robust model for simulating every building in a city and accurately estimate savings prior to capital expenditures.We used two of the world’s fastest supercomputers, assembled unique datasets, and developed innovative algorithms for big data mining to assess different methods to create an accurate building energy model. The team has leveraged a total of eight high performance computing resources and 218 servers to analyze the best methods, metrics, and algorithms for creating an accurate building energy model beyond current industry standards necessary for private-sector financing. The project developed the world’s fastest buildings simulator, has completed over 8 million simulations totaling over 300TB, and mined this data with over 130,000 parallel artificial intelligence algorithms. This was used to quantify accuracy of AI-developed calibration algorithms with results that surpass industry standard guidelines and can identify individual building parameters to between 15% and 32% of their actual value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Formation of late-generation atmospheric compounds inhibited by rapid deposition

Reactive organic carbon species are important fuel for atmospheric chemical reactions, including the formation of secondary organic aerosol. However, in parallel to atmospheric oxidation processes, deposition can remove compounds from the atmosphere and impact downstream environments. To understand the impact of deposition on atmospheric oxidation, we present a framework for predicting and visualizing the fate of a molecule on the basis of the physicochemical properties of compounds (Henry’s law constant, vapour pressure and reaction rate constants), which are used to estimate timescales for oxidation and deposition. Further, by implementing our deposition rates in chemical models, we show that deposition substantially suppresses atmospheric reactivity and aerosol formation by removing early-generation products and preventing the formation of large fractions (up to 90%) of downstream, late-generation compounds. Deposition is frequently missing in the laboratory experiments and detailed chemical modelling, which probably biases our understanding of atmospheric composition.

54 ENVIRONMENTAL SCIENCES↗

Investigations on RELAP5-3D to RELAP5-3D coupling methodology by PVMEXEC

In the framework of a BEPU (Best Estimate Plus Uncertainty) approach within the licensing process of a nuclear power plant, the need to extend the resources of nuclear system thermal-hydraulics codes, such as RELAP5-3D, arises to allow more detailed simulations of the complex 3D reality of Nuclear Power Plants (NPPs), either under normal steady-state or during various accident scenarios. Currently, it is not possible to achieve the same degree of detail for a whole nuclear system when it is simulated with RELAP5-3D and this is due to the inherent limitations in the number of components and volumes to be used for the analysis. For this reason, it is of extreme interest the use of tools for codes coupling that enable the use of different codes for the simulation of different portions of a system in a unified analysis. In this paper the attention will be focused on the decomposition of the thermal-hydraulic domain of a system into subsystems to be simulated by different instances of the same code (e.g. RELAP5-3D) coupled together by means of PVMEXEC program and parallel virtual machine (PVM) technology. Explicit and semi-implicit solution algorithms were used for the analyses. Among the analyzed cases, the following will be discussed in detail with the aim to provide additional guidelines for the use of the PVMEXEC tool: (i) the Edward's pipe blowdown test, (ii) a simplified countercurrent heat exchanger, (iii) different hydraulics and heat structure coupling schemes for a shell-tube heat exchanger and (iv) a three-task coupled model of an adaptation of the Christensen subcooled boiling experiment. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Characterization of differences in calculated and actual measured skin doses to canine limbs during stereotactic radiosurgery using Gafchromic film

Accurate calculation of absorbed dose to the skin, especially the superficial and radiosensitive basal cell layer, is difficult for many reasons including, but not limited to, the build-up effect of megavoltage photons, tangential beam effects, mixed energy scatter from support devices, and dose interpolation caused by a finite resolution calculation matrix. Stereotactic body radiotherapy (SBRT) has been developed as an alternative limb salvage treatment option at Colorado State University Veterinary Teaching Hospital for dogs with extremity bone tumors. Optimal dose delivery to the tumor during SBRT treatment can be limited by uncertainty in skin dose calculation. The aim of this study was to characterize the difference between measured and calculated radiation dose by the Varian Eclipse (Varian Medical Systems, Palo Alto, CA) AAA treatment planning algorithm (for 1-mm, 2-mm, and 5-mm calculation voxel dimensions) as a function of distance from the skin surface. The study used Gafchromic EBT film (International Specialty Products, Wayne, NJ), FilmQA analysis software, a limb phantom constructed from plastic water Trade-Mark-Sign (fluke Biomedical, Everett, WA) and a canine cadaver forelimb. The limb phantom was exposed to 6-MV treatments consisting of a single-beam, a pair of parallel opposed beams, and a 7-beam coplanar treatment plan. The canine forelimb was exposed to the 7-beam coplanar plan. Radiation dose to the forelimb skin at the surface and at depths of 1.65 mm and 1.35 mm below the skin surface were also measured with the Gafchromic film. The calculation algorithm estimated the dose well at depths beyond buildup for all calculation voxel sizes. The calculation algorithm underestimated the dose in portions of the buildup region of tissue for all comparisons, with the most significant differences observed in the 5-mm calculation voxel and the least difference in the 1-mm voxel. Results indicate a significant difference between measured and calculated data extending to average depths of 2.5 mm, 3.4 mm, and 10 mm for the 1-mm, 2-mm, and 5-mm dimension calculation matrices, respectively. These results emphasize the importance of selecting as small a treatment planning software calculation matrix dimension as is practically possible and of taking a conservative approach for skin treatment planning objectives. One suggested conservative approach is accomplished by defining the skin organ as the outermost 2-3 mm of the body such that the high dose tail of the skin organ dose-volume histogram curve represents dose on the deep side of the skin where the algorithm is more accurate.

61 RADIATION PROTECTION AND DOSIMETRY↗

Real time time-dependent density functional theory using higher order finite-element methods

We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real time using higher order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this end, we develop an a priori mesh adaption technique, based on the semidiscrete (discrete in space but continuous in time) error estimate on the time-dependent Kohn-Sham orbitals, to construct an efficient finite-element discretization. Subsequently, we obtain the full-discrete error estimate to guide our choice of the time step. We employ spectral finite elements along with special reduced order quadrature to render the overlap matrix diagonal, thereby simplifying the inversion of the overlap matrix that features in the evaluation of the discrete time-evolution operator. We use the second-order Magnus operator as the time-evolution operator, wherein the action of the discrete Magnus operator, expressed as exponential of a matrix, on the Kohn-Sham orbitals is obtained efficiently through an adaptive Lanczos iteration. We observe close to optimal rates of convergence of the dipole moment with respect to spatial and temporal discretization, for both pseudopotential and all-electron calculations. We demonstrate a staggering 100-fold reduction in the computational time afforded by higher order finite elements over linear finite elements, for both pseudopotential and all-electron calculations. Further, for similar level of accuracy, we obtain significant computational savings by our approach as compared to state-of-the-art finite-difference methods. Here, we also demonstrate the competence of higher order finite elements for all-electron benchmark systems. Lastly, we observe good parallel scalability of the proposed method on many hundreds of processors.

36 MATERIALS SCIENCE↗

Improvements to Nuclear Data and Its Uncertainties by Theoretical Modeling

This project addresses three important gaps in existing evaluated nuclear data libraries that represent a significant hindrance against highly advanced modeling and simulation capabilities for the Advanced Fuel Cycle Initiative (AFCI). This project will: Develop advanced theoretical tools to compute prompt fission neutrons and gamma-ray characteristics well beyond average spectra and multiplicity, and produce new evaluated files of U and Pu isotopes, along with some minor actinides; Perform state-of-the-art fission cross-section modeling and calculations using global and microscopic model input parameters, leading to truly predictive fission cross-sections capabilities. Consistent calculations for a suite of Pu isotopes will be performed; Implement innovative data assimilation tools, which will reflect the nuclear data evaluation process much more accurately, and lead to a new generation of uncertainty quantification files. New covariance matrices will be obtained for Pu isotopes and compared to existing ones. The deployment of a fleet of safe and efficient advanced reactors that minimize radiotoxic waste and are proliferation-resistant is a clear and ambitious goal of AFCI. While in the past the design, construction and operation of a reactor were supported through empirical trials, this new phase in nuclear energy production is expected to rely heavily on advanced modeling and simulation capabilities. To be truly successful, a program for advanced simulations of innovative reactors will have to develop advanced multi-physics capabilities, to be run on massively parallel super- computers, and to incorporate adequate and precise underlying physics. And all these areas have to be developed simultaneously to achieve those ambitious goals. Of particular interest are reliable fission cross-section uncertainty estimates (including important correlations) and evaluations of prompt fission neutrons and gamma-ray spectra and uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Effects of Galactic Irradiation on Thermal and Electronic Transport in Tungsten

The impact of irradiation on the thermal and electronic properties of materials is a persistent puzzle, particularly defect formation at the atomic and nanoscales. This work examines the nanoscale effects of low-energy irradiation on tungsten (W), focusing on defect-induced modifications to thermal and electronic transport. Using the site-projected thermal conductivity (SPTC) method [A. Gautam et al. PSS-RRL, 2400306, 2024], bulk and twin-grain boundary W with vacancy defects based on the Norgett–Robinson–Torrens displacements per atom model is analyzed. SPTC provides a detailed prediction of postcascade spatial thermal conductivity distribution. Electronic conductivity activity is estimated using the “N 2 method” [K. Nepal et al. Carbon, 119711, 2025] to explore the consequences of vacancies and grain boundaries, highlighting the defect-dependent nature of charge transport behavior. These findings offer high-resolution insights into irradiation-driven transport phenomena, with implications for space-exposed materials and nanoscale thermal/electronic management.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microstructure and CPO evolution of dynamically recrystallized olivine during complex deformation conditions: a full-field numerical modeling approach

The rheological properties of mantle rocks are strongly dependent on their crystallographic preferred orientation (CPO). Olivine CPO, defined by the orientation of seismically fast [100] axes parallel to flow direction, is also thought to be a dominant contributor to seismic anisotropy in the Earth's upper mantle. However, the amount of deformation needed to overprint a new CPO on a pre-existing fabric and the impact of the inherited CPOs on the transient microstructure evolution, remain unknown. This study employs a full-field numerical approach (VPFFT-ELLE) to explore the dynamic recrystallization and microstructural evolution of olivine polycrystalline aggregates under complex deformation conditions. We test four combinations of successive pure shear and simple shear boundary conditions. Findings indicate that inherited CPOs influence subsequent deformation in a manner dependent on the kinematic relationship between successive stages. In all cases, a minor strain increment (ε ∼0.3–0.6) is sufficient to erase the previous microstructure and CPO. However, when deformation conditions change dramatically (e.g., stretching direction changes orthogonally), the intensity of the new CPO developed is significantly lower and strain distribution are specially altered. During a transient strain stage, pre-existing microstructures undergo extensive reworking, especially when deformation conditions are changed dramatically, such as switching from simple shear to a pure shear condition with a parallel shortening direction relative to the stretching direction. We estimate the significance of these results in interpreting observations of seismic velocity anisotropy, concluding that P-wave seismic anisotropy is significantly and positively correlated with the evolution of olivine CPO with deformation history. This research underscores the transient nature of microstructural rearrangement in olivine aggregates and the necessity for caution in interpreting seismic anisotropy in regions with complex deformation histories, as inherited CPOs can influence current fabric development and induce deviation to the present deformation conditions.

36 MATERIALS SCIENCE↗

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39 Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ignition probability of polymer-bonded explosives accounting for multiple sources of material stochasticity

Accounting for the combined effect of multiple sources of stochasticity in material attributes, we develop an approach that computationally predicts the probability of ignition of polymer-bonded explosives (PBXs) under impact loading. The probabilistic nature of the specific ignition processes is assumed to arise from two sources of stochasticity. The first source involves random variations in material microstructural morphology; the second source involves random fluctuations in grain-binder interfacial bonding strength. The effect of the first source of stochasticity is analyzed with multiple sets of statistically similar microstructures and constant interfacial bonding strength. Subsequently, each of the microstructures in the multiple sets is assigned multiple instantiations of randomly varying grain-binder interfacial strengths to analyze the effect of the second source of stochasticity. Critical hotspot size-temperature states reaching the threshold for ignition are calculated through finite element simulations that explicitly account for microstructure and bulk and interfacial dissipation to quantify the time to criticality (t{sub c}) of individual samples, allowing the probability distribution of the time to criticality that results from each source of stochastic variation for a material to be analyzed. Two probability superposition models are considered to combine the effects of the multiple sources of stochasticity. The first is a parallel and series combination model, and the second is a nested probability function model. Results show that the nested Weibull distribution provides an accurate description of the combined ignition probability. The approach developed here represents a general framework for analyzing the stochasticity in the material behavior that arises out of multiple types of uncertainty associated with the structure, design, synthesis and processing of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Measurement-induced deterministic and probabilistic entanglement with strong and weak interactions

A scheme is proposed to transform spatial coherence of a single particle into entanglement. Two quantum systems can be entangled by having them interact in parallel with an ancillary particle in a Mach–Zehnder interferometer, then making a suitable post-selection of the particle followed by a conditional feedforward on one of the systems to be entangled. For a strong interaction between each system and the ancilla, the process works deterministically. For a weaker interaction only the probability of success is reduced, but the output continues to be a maximally entangled state. It is demonstrated that the process is optimal when the two interactions are symmetric, systems with continuous variables are considered, and the effects of the environment are taken into account. - Highlights: • Presents a scheme for deterministic entanglement based on feedforward, if a strong interaction is available. • Presents a scheme for probabilistic entanglement, if only a weak interaction is available. • Specifies the importance of an equal interaction strength in both arms. • Includes the effects of the environment and of the internal degrees of freedom of the ancilla.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Study of the second magnetization peak and the pinning behaviour in Ba(Fe 0.935 Co 0.065 ) 2 As 2 pnictide superconductor

Isothermal magnetic field dependence of magnetization and magnetic relaxation measurements were performed for the $H\parallel {\rm{c}}$ axis on a single crystal of Ba(Fe 0.935 Co 0.065 ) 2 As 2 pnictide superconductor having T c = 21.7 K. The second magnetization peak (SMP) for each isothermal M(H) was observed in a wide temperature range from T c to the lowest temperature of measurement (2 K). The magnetic field dependence of relaxation rate R(H), showed a peak (H spt) between H on (onset of SMP in M(H)) and H p (peak field of SMP in M(H)), which is likely to be related to a vortex-lattice structural phase transition, as suggested in the literature for a similar sample. In addition, the magnetic relaxation measured for magnetic fields near H spt showed some noise, which might be the signature of the structural phase transition of the vortex lattice. Analysis of the magnetic relaxation data using Maley's criterion and the collective pinning theory suggested that the SMP in the sample was due to the collective (elastic) to plastic creep crossover, which was also accompanied by a rhombic to square vortex lattice phase transition. The analysis of the pinning force density suggested a single dominating pinning mechanism in the sample, which did not showing the usual $\delta {l}$ and $\delta {T}_{{\rm{c}}}$ nature of pinning. Furthermore, the critical current density (J c ), estimated using the Bean critical state model, was found to be 5 × 10 5 A cm - 2 at 2 K in the zero magnetic field limit. Surprisingly, the maximum of the pinning force density was not responsible for the maximum value of the critical current density in the sample.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhanced Raman scattering from aromatic dithiols electrosprayed into plasmonic nanojunctions

We describe surface enhanced Raman spectroscopy (SERS) experiments in which molecular coverage is systematically varied from 3.8 x 105 to 3.8 x 102 to 0.38 molecules/μm2 using electrospray deposition of ethanolic 4,4’-dimercaptostilbene (DMS) solutions. The plasmonic SERS substrate used herein consists of a well-characterized 2-dimensional (2D) array of silver nanospheres [see El-Khoury et al., J. Chem. Phys., 2014, 141, 214308], previously shown to feature uniform topography and plasmonic response, as well as intense SERS activity. When compared to their ensemble averaged analogues, the spatially and temporally averaged spectra of a single molecule exhibit several unique features including: (i) distinct relative intensities of the observable Raman-active vibrational states, (ii) more pronounced SERS backgrounds, and (iii) broader Raman lines indicative of faster vibrational dephasing. The first observation may be understood on the basis of an intuitive physical picture in which removal of averaging over multiple molecules exposes the tensorial nature of Raman scattering. When an oriented single molecule gives rise to the recorded SERS spectra, the relative orientation of the molecule with respect to vector components of the local electric field determines the relative intensities of the observable vibrational states. Using a single molecule SERS framework described herein, we derive a unique molecular orientation in which a single DMS molecule is isolated at a nanojunction formed between two silver nanospheres in the 2D array. The DMS molecule is found lying nearly flat with respect to the metal surface. The derived orientation of a single molecule at a plasmonic nanojunction is consistent with observations (ii) and (iii). In particular, a careful inspection of the temporal spectral variations along the recorded single molecule SERS time sequences reveals that the time-averaged SERS backgrounds arise from individual molecular events, marked by broadened SERS signatures. We assign the broadened spectra along the SERS time sequence – which sum up to a SERS background in the averaged spectra – to instances in which the π-framework of the DMS molecule is parallel to the metal surface. This also accounts for Raman line broadening as a result of fast vibrational dephasing and driven by molecular reorientation at a plasmonic nanojunction. Furthermore, we report on the orientation dependence of single molecule SERS enhancement factors. We find that in the case of a single DMS molecule isolated at a plasmonic nanojunction, molecular orientation may affect the derived single molecule SERS enhancement factor by up to 5 orders of magnitude. Taking both chemical effects as well as molecular orientation into account, we were able to estimate a single molecule enhancement factor of ~1010 in our measurements.

Environmental Molecular Sciences Laboratory↗

Induced magnetic anisotropy in Si-free nanocrystalline soft magnetic materials: A transmission x-ray diffraction study

In order to better understand the origin of field-induced anisotropy (K{sub u}) in Si-free nanocrystalline soft magnetic alloys, the lattice spacing of the bcc-Fe phase in nanocrystalline Fe{sub 94−x}Nb{sub 6}B{sub x} (x = 10, 12, 14) alloys annealed under an applied magnetic field has been investigated by X-ray diffraction in transmission geometry (t-XRD) with the diffraction vector parallel and perpendicular to the field direction. The saturation magnetostriction (λ{sub s}) of nanocrystalline Fe{sub 94−x}Nb{sub 6}B{sub x} was found to increase linearly with the volume fraction of the residual amorphous phase and is well described by taking into account the volume-weighted average of two local λ{sub s} values for the bcc-Fe nanocrystallites (−5 ± 2 ppm) and the residual amorphous matrix (+8 ± 2 ppm). The lattice distortion required to produce the measured K{sub u} values (∼100 J/m{sup 3}) was estimated via the inverse magnetostrictive effect using the measured λ{sub s} values and was compared to the lattice spacing estimations made by t-XRD. The lattice strain required to produce K{sub u} under the magnetoelastic model was not observed by the t-XRD experiments and so the findings of this study suggest that the origin of magnetic field induced K{sub u} cannot be explained through the magnetoelastic effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

Final Report for Project "Framework Application for Core-Edge Transport Simulations (FACETS)"

This is the final report for the Colorado State University Component of the FACETS Project. FACETS was focused on the development of a multiphysics, parallel framework application that could provide the capability to enable whole-device fusion reactor modeling and, in the process, the development of the modeling infrastructure and computational understanding needed for ITER. It was intended that FACETS be highly flexible, through the use of modern computational methods, including component technology and object oriented design, to facilitate switching from one model to another for a given aspect of the physics, and making it possible to use simplified models for rapid turnaround or high-fidelity models that will take advantage of the largest supercomputer hardware. FACETS was designed in a heterogeneous parallel context, where different parts of the application can take advantage through parallelism based on task farming, domain decomposition, and/or pipelining as needed and applicable. As with all fusion simulations, an integral part of the FACETS project was treatment of the coupling of different physical processes at different scales interacting closely. A primary example for the FACETS project is the coupling of existing core and edge simulations, with the transport and wall interactions described by reduced models. However, core and edge simulations themselves involve significant coupling of different processes with large scale differences. Numerical treatment of coupling is impacted by a number of factors including, scale differences, form of information transferred between processes, implementation of solvers for different codes, and high performance computing concerns. Operator decomposition involving the computation of the individual processes individually using appropriate simulation codes and then linking/synchronizing the component simulations at regular points in space and time, is the defacto approach to high performance simulation of multiphysics, multiscale systems. Various forms of operator decomposition are used in nearly all fusion simulations. However, operator decomposition generally has a complex effect on accuracy and stability of numerical simulations. Yet, these effects can be difficult to detect. The Colorado State University component of the FACETS team led by P.I.D. Estep was focused on analyzing the effects of operator decomposition on fusion simulations. The approach was based on a posteriori error analysis employing adjoint problems, computable residuals, and variational analysis to produce accurate computational error estimates for quantities of interest. Computable residuals are used to quantify the effects of various discretization choices. The generalized Greens function satisfying the adjoint problem quantities the effects of stability. Technical issues to be addressed included: (1) defining appropriate adjoint operators for operator decomposition discretizations; (2) determining the appropriate residuals for the multifaceted aspects involved with multiphysics discretizations; (3) producing the estimates within the computational framework of existing fusion codes; (4) carrying out the analysis for discretizations used in fusion simulations; and (5) devising efficient approaches to mitigating the effects of discretization. This report provides a summary of the accomplished research and a detailed description of personnel, activities, outcomes and achievements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules

Abstract Materials simulations involving strongly correlated electrons pose fundamental challenges to state‐of‐the‐art electronic structure methods but are hypothesized to be the ideal use case for quantum computing algorithms. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real‐world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near‐term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using the VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies using it have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near‐term feasibility of modeling a molecule with d‐orbitals on real quantum hardware. We demonstrate that the inclusion of d‐orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE + UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Kelvin–Helmholtz instability under stabilizing parallel magnetic field in nonhomogeneous compressible MHD flows

We study the Kelvin–Helmholtz instability (KHI) for the general case of a compressible, nonhomogeneous, magnetized plasma flow. The study is limited to a vortex sheet interface with an imposed parallel magnetic field. We introduce a new formalism based on a convective Mach number M c , a convective Alfvénic Mach number M Ac , and a total convective Mach number that combines the two. We derive an analytic expression of the KHI growth rate for a homogeneous flow (i.e., zero Atwood number, A=0) that converges toward both the expression for unmagnetized compressible flow and Chandrasekhar's expression for magnetized incompressible flow. Otherwise, the dispersion relation is solved numerically and allows deriving general stability diagrams of magnetized KHI for the triplet (A, M c , β −plasma) parameters. We show these parameters uniquely define all configurations for a parallel magnetic field. We also construct diagrams with respect to the convective Alfvénic Mach number, the β − plasma parameter, or the magnetic field showing which magnetic field strength is required for stabilizing a given shear flow. The theoretical growth rates are compared with 18 simulations made with the GAMERA code, currently used for 3D magnetospheric simulations. Finally, we apply our results to the analysis of a past KHI experiment performed at the OMEGA laser facility, showing linear theory succeeds to provide accurate estimates of the growth rate at early times. We further discuss how our results can inform future experiments in the high-Mach magnetized regime at the National Ignition Facility. Possible limitations of the study due to resistive, mixing, or turbulence effects are discussed.

compressible flows↗