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At least 253 records · Page 14

Breaking the curse of dimensionality: Solving configurational integrals for crystalline solids by tensor networks

Accurately evaluating configurational integrals for dense solids remains a central and difficult challenge in the statistical mechanics of condensed systems. Here, we present a tensor network approach that reformulates the high-dimensional configurational integral for identical-particle crystals into a sequence of computationally efficient summations. We represent the integrand as a high-dimensional tensor and apply tensor-train (TT) decomposition together with a custom TT-cross interpolation. This approach circumvents the need to explicitly construct the full tensor. We introduce tailored rank-1 and rank-2 schemes optimized for sharply peaked Boltzmann probability densities, typical for identical-particle crystals. When applied to the calculation of internal energy and pressure-temperature curves for crystalline Cu and Ar at high (GPa) pressures, as well as the alpha-to-beta phase transition diagram of Sn, our method accurately reproduces molecular dynamics simulation results using tight-binding, machine learning, hierarchical interacting particle–neural network, and modified embedded atom method potentials,all within seconds of computation time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In-Operando Evaluation of Solid Oxide Fuel Cell (SOFC) Cathodes for Enhanced Oxygen Reduction Reaction (ORR) Activity and Durability

Through this project we developed a new in-operando 18 O-isotope exchange technique, and determined the oxygen reduction reaction (ORR) kinetics and mechanisms in various solid oxide fuel cell (SOFC) cathodes under real operating conditions of applied voltage. We were able to measure and determine oxygen surface exchange coefficients of labeled oxygen with La 0.8 Sr 0.2 MnO 3 (LSM), La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 (LSCF) and other cathode material samples with varying compositions. We related the cell polarization conditions to the surface exchange process and surface exchange coefficient, and suggested a model to describe this relation. Our findings imply that LSCF keeps its higher exchange rate performance over LSM under real operating conditions. Changing the A-site cation ratio in LSM can enhance its performance, especially under cathodic polarizations larger than -400mV. Cathode powder composites of LSM and LSCF with YSZ and GDC show lower exchange coefficient values under applied polarization compared to the single constituent powder samples, probably due to limited contact between the powder particles. Using our model and basic electrochemical properties of the cathode materials we are able to successfully predict the exchange kinetic properties of SOFC cathode material under real operating conditions of applied voltage / current from surface exchange coefficients obtained in the absence of an applied bias.

36 MATERIALS SCIENCE↗

Application of a bayesian belief network model to reliability assessment of nuclear safety-related software - 207

As the instrumentation and control (I and C) systems in nuclear power plants (NPPs) have been replaced with digital-based systems, the need to incorporate software failures into NPP probabilistic risk assessments has arisen. In order to assess the probability of software failure on demand, a Bayesian belief network (BBN) model was developed which estimates the number of defects and the resulting probability of software failure on demand in nuclear safety-related software. To assess the feasibility of the BBN framework, the BBN model was applied to the prototype Integrated Digital Protection System-Reactor Protection System (IDiPS-RPS) to estimate the number of remaining faults and the software failure probability of a target software. The developmental- and V and V-activities carried out during the IDiPS-RPS development process were evaluated based on the well-defined checklist derived by the V and V team and were estimated based on expert elicitation. In addition, the attribute evaluations and the number of FPs of the target software is provided as the inputs for the BBN model. The application results showed the feasibility of using BBNs for quantifying software failure probabilities and several insights were gained from the applications of the BBN model. The proposed BBN framework can be applied to estimate the software failure probability for other safety-related NPP software and provide an insight on modeling the software development process that involves iterations between different development phases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Effects of scale of movement, detection probability, and true population density on common methods of estimating population density

Knowledge of population density is necessary for effective management and conservation of wildlife, yet rarely are estimators compared in their robustness to effects of ecological and observational processes, which can greatly influence accuracy and precision of density estimates. For this study, we simulate biological and observational processes using empirical data to assess effects of animal scale of movement, true population density, and probability of detection on common density estimators. We also apply common data collection and analytical techniques in the field and evaluate their ability to estimate density of a globally widespread species. We find that animal scale of movement had the greatest impact on accuracy of estimators, although all estimators suffered reduced performance when detection probability was low, and we provide recommendations as to when each field and analytical technique is most appropriately employed. The large influence of scale of movement on estimator accuracy emphasizes the importance of effective post-hoc calculation of area sampled or use of methods that implicitly account for spatial variation. In particular, scale of movement impacted estimators substantially, such that area covered and spacing of detectors (e.g. cameras, traps, etc.) must reflect movement characteristics of the focal species to reduce bias in estimates of movement and thus density.

59 BASIC BIOLOGICAL SCIENCES↗

Unit-Sphere Multiaxial Stochastic-Strength Model Applied to Anisotropic and Composite Materials

Models that predict the failure probability of brittle materials under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This methodology has been extended to predict the multiaxial strength response of transversely isotropic brittle materials, including polymer matrix composites (PMCs), by considering (1) flaw-orientation anisotropy, whereby a preexisting microcrack has a higher likelihood of being oriented in one direction over another direction, and (2) critical strength, or K (sub Ic) orientation anisotropy, whereby the level of critical strength or fracture toughness for mode I crack propagation, K (sub Ic), changes with regard to the orientation of the microstructure. In this report, results from finite element analysis of a fiber-reinforced-matrix unit cell were used with the unit-sphere model to predict the biaxial strength response of a unidirectional PMC previously reported from the World-Wide Failure Exercise. Results for nuclear-grade graphite materials under biaxial loading are also shown for comparison. This effort was successful in predicting the multiaxial strength response for the chosen problems. Findings regarding stress-state interactions and failure modes also are provided.

Nemeth, Noel, N.↗

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗

Enforcing positivity in intrusive PC-UQ methods for reactive ODE systems

We explore the relation between the development of a non-negligible probability of negative states and the instability of numerical integration of the intrusive Galerkin ordinary differential equation system describing uncertain chemical ignition. To prevent this instability without resorting to either multi-element local polynomial chaos (PC) methods or increasing the order of the PC representation in time, we propose a procedure aimed at modifying the amplitude of the PC modes to bring the probability of negative state values below a user-defined threshold. This modification can be effectively described as a filtering procedure of the spectral PC coefficients, which is applied on-the-fly during the numerical integration when the current value of the probability of negative states exceeds the prescribed threshold. We demonstrate the filtering procedure using a simple model of an ignition process in a batch reactor. This is carried out by comparing different observables and error measures as obtained by non-intrusive Monte Carlo and Gauss-quadrature integration and the filtered intrusive procedure. The filtering procedure has been shown to effectively stabilize divergent intrusive solutions, and also to improve the accuracy of stable intrusive solutions which are close to the stability limits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Demonstration of Turnstiles as a Chaotic Ionization Mechanism in Rydberg Atoms

We present an experimental and theoretical study of the chaotic ionization of quasi-one-dimensional potassium Rydberg wave packets via a classical phase-space turnstile mechanism. Turnstiles form a general transport mechanism for numerous chaotic systems, and this study explicitly illuminates their relevance to atomic ionization. We create time-dependent Rydberg wave packets, subject them to alternating applied electric-field pulses, and measure the electron survival probability. Ionization depends not only on the initial electron energy, but also on the classical phase-space position of the electron with respect to the turnstile--that part of the electron packet inside the turnstile ionizes after the applied ionization sequence, while that part outside the turnstile does not. The survival data thus encode information on the shape and location of the turnstile, in good agreement with theoretical predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Effect of annealing on the laser induced damage of polished and CO{sub 2} laser-processed fused silica surfaces

We investigate the effect of different heat treatments on the laser-induced damage probabilities of fused silica samples. Isothermal annealing in a furnace is applied, with different temperatures in the range 700–1100 °C and 12 h annealing time, to super-polished fused silica samples. The surface flatness and laser damage probabilities at 3 ns, 351 nm are measured before and after the different annealing procedures. We have found a significant improvement of the initial laser damage probabilities of the silica surface after annealing at 1050 °C for 12 h. A similar study has been conducted on CO{sub 2} laser-processed sites on the surface of the samples. Before and after annealing, we have studied the morphology of the sites, the evolution of residual stress, and the laser-induced damage threshold measured at 351 nm, 3 ns. In this case, we observe that the laser damage resistance of the laser created craters can reach the damage level of the bare fused silica surface after the annealing process, with a complete stress relieve. The obtained results are then compared to the case of local annealing process by CO{sub 2} laser irradiation during 1 s, and we found similar improvements in both cases. The different results obtained in the study are compared to numerical simulations made with a thermo-mechanical model based on finite-element method that allows the simulation of the isothermal or the local annealing process, the evolution of stress and fictive temperature. The simulation results were found to be very consistent with experimental observations for the stresses evolution after annealing and estimation of the heat affected area during laser-processing based on the density dependence with fictive temperature. Following this work, the temperature for local annealing should reach 1330–1470 °C for an optimized reduction of damage probability and be below the threshold for material removal, whereas furnace annealing should be kept below the annealing point to avoid sample deformation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Arctic LDRD project: What happened?

This presentation overviews results from the 2019 LDRD Reserve project “Diagnosing near-future changes in Arctic sea ice and ocean conditions” and a follow-up 2020 CSES Rapid Response project “Multi- Model Risk Assessment for Arctic Navigability.” We analyzed Arctic simulations from 4 CMIP6 model ensembles (E3SM, CESM-CAM, CESM-WACCM and CESM-DPLE), comparing them with observations. We then applied a machine-learning approach using copulas to produce joint probabilities of adverse conditions along potential shipping transit routes through the Arctic. Here we compare and contrast the different models and examine the utility of the copula approach applied to these data sets.

58 GEOSCIENCES↗

AN EFFICIENT AUTOMATED VALIDATION PROCEDURE FOR EXOPLANET TRANSIT CANDIDATES

Surveys searching for transiting exoplanets have found many more candidates than they have been able to confirm as true planets. This situation is especially acute with the Kepler survey, which has found over 2300 candidates but has to date confirmed only a small fraction of them as planets. I present here a general procedure that can quickly be applied to any planet candidate to calculate its false positive probability. This procedure takes into account the period, depth, duration, and shape of the signal; the colors of the target star; arbitrary spectroscopic or imaging follow-up observations; and informed assumptions about the populations and distributions of field stars and multiple-star properties. Applying these methods to a sample of known Kepler planets, I demonstrate that many signals can be validated with very limited follow-up observations: in most cases with only a spectrum and an adaptive optics image. Additionally, I demonstrate that this procedure can reliably identify false positive signals. Because of the computational efficiency of this analysis, it is feasible to apply it to all Kepler planet candidates in the near future, and it will streamline the follow-up efforts for Kepler and other current and future transit surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Typological representation of the offshore oceanographic environment along the Alaskan North Slope

Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III® and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ~50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (H s ) and peak period (T p ). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

54 ENVIRONMENTAL SCIENCES↗

Finite element formulation of fluctuating hydrodynamics for fluids filled with rigid particles using boundary fitted meshes

In this paper, we present a finite element implementation of fluctuating hydrodynamics with a moving boundary fitted mesh for treating the suspended particles. The thermal fluctuations are incorporated into the continuum equations using the Landau and Lifshitz approach [1]. The proposed implementation fulfills the fluctuation–dissipation theorem exactly at the discrete level. Since we restrict the equations to the creeping flow case, this takes the form of a relation between the diffusion coefficient matrix and friction matrix both at the particle and nodal level of the finite elements. Brownian motion of arbitrarily shaped particles in complex confinements can be considered within the present formulation. A multi-step time integration scheme is developed to correctly capture the drift term required in the stochastic differential equation (SDE) describing the evolution of the positions of the particles. The proposed approach is validated by simulating the Brownian motion of a sphere between two parallel plates and the motion of a spherical particle in a cylindrical cavity. The time integration algorithm and the fluctuating hydrodynamics implementation are then applied to study the diffusion and the equilibrium probability distribution of a confined circle under an external harmonic potential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Age gradients in the stellar populations of massive star forming regions based on a new stellar chronometer

A major impediment to understanding star formation in massive star-forming regions (MSFRs) is the absence of a reliable stellar chronometer to unravel their complex star formation histories. We present a new estimation of stellar ages using a new method that employs near-infrared (NIR) and X-ray photometry, Age {sub JX} . Stellar masses are derived from X-ray luminosities using the L{sub X} -M relation from the Taurus cloud. J-band luminosities are compared to mass-dependent pre-main-sequence (PMS) evolutionary models to estimate ages. Age {sub JX} is sensitive to a wide range of evolutionary stages, from disk-bearing stars embedded in a cloud to widely dispersed older PMS stars. The Massive Young Star-Forming Complex Study in Infrared and X-ray (MYStIX) project characterizes 20 OB-dominated MSFRs using X-ray, mid-infrared, and NIR catalogs. The Age {sub JX} method has been applied to 5525 out of 31,784 MYStIX Probable Complex Members. We provide a homogeneous set of median ages for over 100 subclusters in 15 MSFRs; median subcluster ages range between 0.5 Myr and 5 Myr. The important science result is the discovery of age gradients across MYStIX regions. The wide MSFR age distribution appears as spatially segregated structures with different ages. The Age {sub JX} ages are youngest in obscured locations in molecular clouds, intermediate in revealed stellar clusters, and oldest in distributed populations. The NIR color index J – H, a surrogate measure of extinction, can serve as an approximate age predictor for young embedded clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

Scattering using real-time path integrals

Background: Path integrals are a powerful tool for solving problems in quantum theory that are not amenable to a treatment by perturbation theory. Most path integral computations require an analytic continuation to imaginary time. While imaginary time treatments of scattering are possible, imaginary time is not a natural framework for treating scattering problems. More importantly, quantum algorithms for calculating path integrals require real-time evolution. Purpose: Here, we test a recently introduced method for performing direct calculations of scattering observables using real-time path integrals in order to understand the challenges facing real-time path integral calculations of scattering observables. Method: The computations are based on a new interpretation of the path integral as the expectation value of a potential functional on cylinder sets of continuous paths with respect to a complex probability distribution. The method can in principle be applied to arbitrary short-range potentials. Results: The method is applied to compute matrix elements of Møller wave operators applied to narrow wave packets. These are used to calculate half-shell sharp-momentum transition matrix elements for one-dimensional potential scattering. The calculations for half-shell transition operator matrix elements converge to the numerical solution of the Lippmann-Schwinger equation. Conclusions: This work presents a proof in principle that scattering observables can be computed using real-time Feynman path integrals. While the computational method is not efficient, it can be improved. It provides a laboratory for studying quantum computational algorithms that are applicable to scattering problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preparation of excited states for nuclear dynamics on a quantum computer

We study two different methods to prepare excited states on a quantum computer, a key initial step to study dynamics within linear response theory. The first method uses unitary evolution for a short time T = O(√1 - F) to approximate the action of an excitation operator Ô with fidelity F and success probability P ≈ 1 – F. The second method probabilistically applies the excitation operator using the Linear Combination of Unitaries (LCU) algorithm. We benchmark these techniques on emulated and real quantum devices, using a toy model for thermal neutron-proton capture. Despite its larger memory footprint, the LCU-based method is efficient even on current generation noisy devices and can be implemented at a lower gate cost than a naive analysis would suggest. Here, these findings show that quantum techniques designed to achieve good asymptotic scaling on fault tolerant quantum devices might also provide practical benefits on devices with limited connectivity and gate fidelity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantum Time-Space Tradeoffs for Matrix Problems

We consider the time and space required for quantum computers to solve a wide variety of problems involving matrices, many of which have only been analyzed classically in prior work. Our main results show that for a range of linear algebra problems—including matrix-vector product, matrix inversion, matrix multiplication and powering—existing classical time-space tradeoffs, several of which are tight for every space bound, also apply to quantum algorithms with at most a constant factor loss. For example, for almost all fixed matrices 𝐴, including the discrete Fourier transform matrix, we prove that quantum circuits with at most 𝑇 input queries and 𝑆 qubits of memory require 𝑇 = Ω⁢(𝑛 2 /𝑆) to compute matrix-vector product 𝐴⁢𝑥 for 𝑥 ∈{0,1 𝑛 . We similarly prove that matrix multiplication for 𝑛 ×𝑛 binary matrices requires 𝑇 = Ω⁢(𝑛 3 /$\sqrt{𝑆}$). Because many of our lower bounds are matched by deterministic algorithms with the same time and space complexity, our results show that quantum computers cannot provide any asymptotic advantage for these problems with any space bound. We obtain matching lower bounds for the stronger notion of quantum cumulative memory complexity—the sum of the space per layer of a circuit. We also consider Boolean (i.e., AND-OR) matrix multiplication and matrix-vector products, improving the previous quantum time-space tradeoff lower bounds for 𝑛 × 𝑛 Boolean matrix multiplication to 𝑇 = Ω⁢(𝑛 2.5 /𝑆 1/4 ) from 𝑇 = Ω⁢(𝑛 2.5 /𝑆 1/2 ). Our improved lower bound for Boolean matrix multiplication is based on a new coloring argument that extracts more from the strong direct product theorem that was the basis for prior work. To obtain our tight lower bounds for linear algebra problems, we require much stronger bounds than strong direct product theorems. We obtain these bounds by adding a new bucketing method to the quantum recording-query technique of Zhandry that lets us apply classical arguments to upper bound the success probability of quantum circuits.

lower bounds↗