Computing Sciences

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

In this work, we compare the rate of warming of summertime extreme temperatures (summer maximum value of daily maximum temperature; TXx) relative to the local mean (summer mean daily maximum temperature; TXm) over the Northern Hemisphere in observations and one set of large ensemble (LE) simulations. During the 1979–2021 historical period, observations and simulations show robust warming trends in both TXm and TXx almost everywhere in the Northern Hemisphere, except over the eastern U.S. where observations show a slight cooling trend in TXx, which may be a manifestation of internal variability. We find that the observed warming rate in TXx is significantly smaller than in TXm in North Africa, western North America, Siberia, and Eastern Asia, whereas the warming rate in TXx is significantly larger over the Eastern U.S., the U.K., and Northwestern Europe. This observed geographical pattern is successfully reproduced by the vast majority of the LE members over the historical period, and is persistent (although less intense) in future climate projections over the 2051–2100 period. We also find that these relative warming patterns are mostly driven by the local hydroclimate conditions. TXx warms slower than TXm in the hyper-arid, arid, semi-arid and moist regions, where trends in the partitioning of the turbulent surface fluxes between the latent and sensible heat flux are similar during regular and extreme hot days. In contrast, TXx warms faster than TXm in dry-subhumid regions where trends in the partitioning of the surface fluxes are significantly different between regular and extreme hot days, with a larger role of sensible heat flux during the extreme hot days.

Abstract: A real-time capable core ICRF heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.

Traditional models of lanthanide electronic structure suggest that bonding is predominantly ionic, and that covalent orbital mixing is not an important factor in determining magnetic properties. Here, 4f orbital mixing and its impact on the magnetic susceptibility of Cp'₃Eu (Cp' = C₅H₄SiMe₃) was analyzed experimentally using magnetometry and X-ray absorption spectroscopy (XAS) methods at the C K-, Eu M_5,4-, and L₃-edges. Pre-edge features in the experimental and TDDFT-calculated C K-edge XAS spectra provided unequivocal evidence of C 2p and Eu 4f orbital mixing in the π-antibonding orbital of a' symmetry. The charge-transfer configurations resulting from 4f orbital mixing were identified spectroscopically by using Eu M_5,4-edge and L₃-edge XAS. Modeling of variable-temperature magnetic susceptibility data showed excellent agreement with the XAS results and indicated that increased magnetic susceptibility of Cp'₃Eu is due to removal of the degeneracy of the ⁷F₁ excited state due to mixing between the ligand and Eu 4f orbitals.

Abstract: Correlation coefficients and linear regression values computed from group averages can differ from correlation coefficients and linear regression values computed using individual scores. This observation known as the ecological fallacy often assumes that all the individual scores are available from a population. In many situations, one must use a sample from the larger population. In such cases, the computed correlation coefficient and linear regression values will depend on the sample that is chosen and the underlying sampling distribution. The sampling distribution of correlation coefficients and linear regression values for group averages will be identical to the sampling distribution for individuals for normally distributed variables for random samples drawn from infinitely large continuous distributions. However, data that is acquired in practice is often acquired when sampling without replacement from a finite population. Our objective is to demonstrate through Monte Carlo simulations that the sampling distributions for correlation and linear regression will also be similar for individuals and group averages when sampling without replacement from normally distributed variables. These simulations suggest that when a random sample from a population is selected, the correlation coefficients and linear regression values computed from individual scores will not be more accurate in estimating the entire population values compared to samples when group averages are used as long as the sample size is the same.

In this paper we present a novel method for solving the shallow-shelf equations in the presence of grounding lines. The shallow-self equations are a two-dimensional system of nonlinear elliptic PDEs with variable coefficients that are discontinuous across the grounding line, which we treat as a sharp interface between grounded and floating ice. The grounding line is “reconstructed” from ice thickness and basal topography data to provide necessary geometric information for our cut-cell, finite volume discretization. Our discretization enforces jump conditions across the grounding line and achieves high-order accuracy using stencils constructed with a weighted least-squares method. We demonstrate second and fourth order convergence of the velocity field, driving stress, and reconstructed geometric information.

Antiferromagnets have attracted significant attention in the field of magnonics, as promising candidates for ultralow-energy carriers for information transfer for future computing. The role of crystalline orientation distribution on magnon transport has received very little attention. In multiferroics such as BiFeO3 the coupling between antiferromagnetic and polar order imposes yet another boundary condition on spin transport. Thus, understanding the fundamentals of spin transport in such systems requires a single domain, a single crystal. We show that through Lanthanum (La) substitution, a single ferroelectric domain can be engineered with a stable, single-variant spin cycloid, controllable by an electric field. The spin transport in such a single domain displays a strong anisotropy, arising from the underlying spin cycloid lattice. Our work shows a pathway to understanding the fundamental origins of magnon transport in such a single domain multiferroic.

This document specifies an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.

This article presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types. Our proposed new hybrid models (named hybridM) merge the Monte Carlo Tree Search structure (MCTS) for categorical variables with Gaussian Processes (GP) for continuous ones. hybridM leverages the upper confidence bound tree search (UCTS) for MCTS strategy, showcasing the tree architecture’s integration into Bayesian optimization. Our innovations, including dynamic online kernel selection in the surrogate modeling phase and a unique UCTS search strategy, position our hybrid models as an advancement in mixed-variable surrogate models. Numerical experiments underscore the superiority of hybrid models, highlighting their potential in Bayesian optimization. Supplementary materials for this article are available online.