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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Sagnik Mondal Sameh Abdulah Hatem Ltaief Ying Sun Marc G. Genton David E. Keyes Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Kingdom of Saudi Arabia Statistics Program King Abdullah University of Science and Technology Extreme Computing Research Center King Abdullah University of Science and Technology

Maximum likelihood estimation is an essential tool in the procedure to impute missing data in climate/weather applications. By defining a particular statistical model, the maximum likelihood estimation can be used to understand the underlying structure of given geospatial data. The Gaussian random field has been widely used to describe geospatial data, as one of the most popular models under the hood of maximum likelihood estimation. Computation of Gaussian log-likelihood demands operations on a dense symmetric positive definite matrix, often parameterized by the Matérn correlation function. This computation of the log-likelihood requires $\mathcal{O}(n^{2})$ storage and $\mathcal{O}(n^{3})$ operations, which can be a huge task considering that the number of geographical locations, $n$ , now commonly reaches into the millions. However, despite its appealing theoretical properties, the assumptions of Gaussianity may be unrealistic since real data often show signs of skewness or have some extreme values. Herein, we consider the Tukey ${g-}$ and $-h$ (TGH) random field as an example of a non-Gaussian random field that shows more robustness in modeling geospatial data by including two more parameters to incorporate skewness and heavy tail features in the model. This work provides the first HPC implementation of the TGH random field's inference on parallel hardware architectures. Using task-based programming models associated with dynamic runtime systems, our implementation leverages the high concurrency of current parallel systems. This permits to run the exact log-likelihood evaluation of the Tukey g-and-h (TGH) random fields for a decent number of geospatial locations. To tackle large-scale problems, we provide additionally an implementation of the given model using two different low-rank approximations. We compress the aforementioned positive-definite symmetric matrix for computing the log-likelihood and rely on the Tile Low-Rank (TLR) and the Hierarchical Off-Diagon

关键词： Maximum likelihood estimation Symmetric matrices Runtime Computational modeling Linear algebra Tail Predictive models

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Surface Dyakonov-Cherenkov radiation

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eLight 2022年第1期2卷 24-31页

作者： Hao Hu Xiao Lin Liang Jie Wong Qianru Yang Dongjue Liu Baile Zhang Yu Luo School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical InstrumentationZJU‑Hangzhou Global Science and Technology Innovation CenterCollege of Information Science and Electronic EngineeringZhejiang UniversityHangzhou 310027China International Joint Innovation Center ZJU‑UIUC InstituteZhejiang UniversityHaining 314400China Division of Physics and Applied Physics School of Physical and Mathematical SciencesNanyang Technological University21 Nanyang LinkSingapore 637371Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University21 Nanyang LinkSingapore 637371Singapore UMI 3288 CINTRA CNRS/NTU/THALESNanyang Technological University50 Nanyang DriveSingapore 637553Singapore.

Recent advances in engineered material technologies(e.g.,photonic crystals,metamaterials,plasmonics,etc.)provide valuable tools to control Cherenkov *** all these approaches,however,the particle velocity is a key parameter to affect Cherenkov radiation in the designed material,while the influence of the particle trajectory is generally ***,we report on surface Dyakonov-Cherenkov radiation,*** emission of directional Dyakonov surface waves from a swift charged particle moving atop a birefringent *** new type of Cherenkov radiation is highly susceptible to both the particle velocity and trajectory,*** observe a sharp radiation enhancement when the particle trajectory falls in the vicinity of a particular ***,close to the Cherenkov threshold,such a radiation enhancement can be orders of magnitude higher than that obtained in traditional Cherenkov *** distinct properties allow us to determine simultaneously the magnitude and direction of particle velocities on a compact *** surface Dyakonov-Cherenkov radiation studied in this work not only adds a new degree of freedom for particle identification,but also provides an all-dielectric route to construct compact Cherenkov detectors with enhanced sensitivity.

关键词： Cherenkov radiation Dyakonov surface wave Particle detector

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On the particle approximation of lagged Feynman–Kac formulae

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Stochastic Processes and their Applications 2025年 188卷

作者： Awadelkarim, Elsiddig Caffarel, Michel Del Moral, Pierre Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia University of Toulouse CNRS-Lab. de Chimie et Physique Quantiques Toulouse31062 France Centre de Recherche Inria Bordeaux Sud-Ouest Talence33405 France School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

In this paper we examine the numerical approximation of the limiting invariant measure associated with Feynman–Kac formulae. These are expressed in a discrete time formulation and are associated with a Markov chain and a potential function. The typical application considered here is the computation of eigenvalues associated with non-negative operators as found, for example, in physics or particle simulation of rare-events. We focus on a novel lagged approximation of this invariant measure, based upon the introduction of a ratio of time-averaged Feynman–Kac marginals associated with a positive operator iterated l∈N times;a lagged Feynman–Kac formula. This estimator and its approximation using Diffusion Monte Carlo (DMC) are commonly used in the physics literature. In short, DMC is an iterative algorithm involving N∈N particles or walkers simulated in parallel, that undergo sampling and resampling operations. In this work, it is shown that for the DMC approximation of the lagged Feynman–Kac formula, one has an almost sure characterization of the L1-error as the time parameter (iteration) goes to infinity and this is at most of O(exp{−κl}/N), for κ>0. In addition a non-asymptotic in time, and time uniform L1−bound is proved which is O(l/N). We also prove a novel central limit theorem to give a characterization of the exact asymptotic in time variance. This analysis demonstrates that the strategy used in physics, namely, to run DMC with N and l small and, for long time enough, is mathematically justified. Our results also suggest how one should choose N and l in practice. We emphasize that these results are not restricted to physical applications;they have broad relevance to the general problem of particle simulation of the Feynman–Kac formula, which is utilized in a great variety of scientific and engineering fields. © 2025 Elsevier B.V.

关键词： Iterative methods

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Measurement of peripheral nerve magnetostimulation thresholds of a head solenoid coil between 200 Hz and 88.1 kHz

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IEEE Journal of Translational engineering in Health and Medicine 2025年 13卷 275-285页

作者： Barksdale, Alex C. Ferris, Natalie G. Mattingly, Eli Sliwiak, Monika Guerin, Bastien Wald, Lawrence L. Davids, Mathias Klein, Valerie MIT Department of Electrical Engineering and Computer Science CambridgeMA United States Martinos Center for Biomedical Imaging CharlestownMA United States Harvard University Harvard Graduate Program in Biophysics CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology BostonMA United States Harvard Medical School BostonMA United States

Objective: Magnetic fields switching at kilohertz frequencies induce electric fields in the body, which can cause peripheral nerve stimulation (PNS). Although magnetostimulation has been extensively studied below 10 kHz, the behavior of PNS at higher frequencies remains poorly understood. This study aims to investigate PNS thresholds at frequencies up to 88.1 kHz and to explore deviations from the widely accepted hyperbolic strength-duration curve (SDC). Methods and procedures: PNS thresholds were measured in the head of 8 human volunteers using a solenoidal coil at 16 distinct frequencies, ranging from 200 Hz to 88.1 kHz. A hyperbolic SDC was used as a reference to compare the frequency-dependent behavior of PNS thresholds. Results: Contrary to the predictions of the hyperbolic SDC, PNS thresholds did not decrease monotonically with frequency. Instead, thresholds reached a minimum near 25 kHz, after which they increased by an average of 39% from 25 kHz to 88.1 kHz across subjects. This pattern indicates a significant deviation from previously observed behavior at lower frequencies. Conclusion: Our results suggest that PNS thresholds exhibit a non-monotonic frequency dependence at higher frequencies, diverging from the traditional hyperbolic SDC. These findings offer critical data for refining neurodynamic models and provide insights for setting PNS safety limits in applications like MRI gradient coils and magnetic particle imaging (MPI). Further investigation is needed to understand the biological mechanisms driving these deviations beyond 25 kHz. Clinical impact: These findings call for further basic research into biological mechanisms underlying high frequency PNS threshold trends, and supports refinement of safety guidelines for MRI and MPI systems for clinical implementation. © 2013 IEEE.

关键词： Neuroimaging

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Layer-dependent optically induced spin polarization in InSe

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physical Review B 2023年第11期107卷 115304-115304页

作者： Jovan Nelson Teodor K. Stanev Dmitry Lebedev Trevor LaMountain J. Tyler Gish Hongfei Zeng Hyeondeok Shin Olle Heinonen Kenji Watanabe Takashi Taniguchi Mark C. Hersam Nathaniel P. Stern Applied Physics Program Northwestern University Evanston Illinois 60208 USA Department of Physics and Astronomy Northwestern University Evanston Illinois 60208 USA Department of Material Science and Engineering Northwestern University Evanston Illinois 60208 USA Computational Science Division Argonne National Laboratory Lemont Illinois 60439 USA Material Science Division Argonne National Laboratory Lemont Illinois 60439 USA Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Department of Chemistry Northwestern University Evanston Illinois 60208 USA Department of Electrical Engineering and Computer Science Northwestern University Evanston Illinois 60208 USA

Optical control of spin in semiconductors has been pioneered using nanostructures of III-V and II-VI semiconductors, but the emergence of two-dimensional van der Waals materials offers an alternative low-dimensional platform for spintronic phenomena. Indium selenide (InSe), a group-III monochalcogenide van der Waals material, has shown promise for optoelectronics due to its high electron mobility, tunable direct band gap, and quantum transport. In addition to these confirmed properties, there are predictions of spin-dependent optical selection rules, suggesting the potential for all-optical excitation and control of spin in a two-dimensional layered material. Despite these predictions, layer-dependent optical spin phenomena in InSe have yet to be explored. Here, we present measurements of layer-dependent optical spin dynamics in few-layer and bulk InSe. Polarized photoluminescence reveals layer-dependent optical orientation of spin, thereby demonstrating the optical selection rules in few-layer InSe. Spin dynamics are also studied in many-layer InSe using time-resolved Kerr rotation spectroscopy. By applying out-of-plane and in-plane static magnetic fields for polarized emission measurements and Kerr measurements, respectively, the g factor for InSe was extracted. Further investigations are done by calculating precession values using a k·p model, which is supported by ab initio density functional theory. Comparison of predicted precession rates with experimental measurements highlights the importance of excitonic effects in InSe for understanding spin dynamics. Optical orientation of spin is an important prerequisite for optospintronic phenomena and devices, and these first demonstrations of layer-dependent optical excitation of spins in InSe lay the foundation for combining layer-dependent spin properties with advantageous electronic properties found in this material.

关键词： Magneto-optics Spin dynamics Chalcogenides Layered semiconductors Van der Waals systems Density functional theory Kerr effect Photoluminescence k dot p method

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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Distributionally Robust Variational Quantum Algorithms with Shifted Noise

arXiv

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arXiv 2023年

作者： He, Zichang Peng, Bo Alexeev, Yuri Zhang, Zheng Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory RichlandWA99352 United States Computational Science Division Argonne National Laboratory LemontIL60439 United States

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is that quantum noise is highly unstable and thus it is likely to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by shifted noise from the parameter optimization perspective. Copyright © 2023, The Authors. All rights reserved.

关键词： Probability density function

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On the Particle Approximation of Lagged Feynman-Kac Formulae

arXiv

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arXiv 2024年

作者： Awadelkarim, Elsiddig Caffarel, Michel Moral, Pierre Del Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia University of Toulouse CNRS-Lab. de Chimie et Physique Quantiques Toulouse31062 France Centre de Recherche Inria Bordeaux Sud-Ouest Talence33405 France School of Data Science The Chinese University Hong Kong Shenzhen China

In this paper we examine the numerical approximation of the limiting invariant measure associated with Feynman-Kac formulae. These are expressed in a discrete time formulation and are associated with a Markov chain and a potential function. The typical application considered here is the computation of eigenvalues associated with non-negative operators as found, for example, in physics or particle simulation of rare-events. We focus on a novel lagged approximation of this invariant measure, based upon the introduction of a ratio of time-averaged Feynman-Kac marginals associated with a positive operator iterated l ∈ N times;a lagged Feynman-Kac formula. This estimator and its approximation using Diffusion Monte Carlo (DMC) have been extensively employed in the physics literature. In short, DMC is an iterative algorithm involving N ∈ N particles or walkers simulated in parallel, that undergo sampling and resampling operations. In this work, it is shown that for the DMC approximation of the lagged Feynman-Kac formula, one has an almost sure characterization of the L1-error as the time parameter (iteration) goes to infinity and this is at most of O(exp{−κl}/N), for_ κ > 0. In addition a non-asymptotic in time, and time uniform L1−bound is proved which is O(l/√N). We also prove a novel central limit theorem to give a characterization of the exact asymptotic in time variance. This analysis demonstrates that the strategy used in physics, namely, to run DMC with N and l small and, for long time enough, is mathematically justified. Our results also suggest how one should choose N and l in practice. We emphasize that these results are not restricted to physical applications;they have broad relevance to the general problem of particle simulation of the Feynman-Kac formula, which is utilized in a great variety of scientific and engineering fields. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

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Cross-system biological image quality enhancement based on the generative adversarial network as a foundation for establishing a multi-institute microscopy cooperative network

arXiv

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arXiv 2024年

作者： Panek, Dominik Rząca, Carina Szczypior, Maksymilian Sorysz, Joanna Misztal, Krzysztof Baster, Zbigniew Rajfur, Zenon Doctoral School of Exact and Natural Sciences Jagiellonian University ul. Lojasiewicza 11 Kraków30-348 Poland Department of Molecular and Interfacial Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate Program in Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate program in Biomedical Engineering Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Al. A. Mickiewicza 30 Building B-1 Kraków30-059 Poland Division of Computational Mathematics Faculty of Mathematics and Computer Science Jagiellonian University 6 Lojasiewicza St. Kraków Poland

High-quality fluorescence imaging of biological systems is limited by processes like photobleaching and phototoxicity, and also in many cases, by limited access to the latest generations of microscopes. Moreover, low temporal resolution can lead to a motion blur effect in living systems. Our work presents a deep learning (DL) generative-adversarial approach to the problem of obtaining high-quality (HQ) images based on their low-quality (LQ) equivalents. We propose a generative-adversarial network (GAN) for contrast transfer between two different separate microscopy systems: a confocal microscope (producing HQ images) and a wide-field fluorescence microscope (producing LQ images). Our model proves that such transfer is possible, allowing us to receive HQ-generated images characterized by low mean squared error (MSE) values, high structural similarity index (SSIM), and high peak signal-to-noise ratio (PSNR) values. For our best model in the case of comparing HQ-generated images and HQ-ground truth images, the median values of the metrics are 6·10-4, 0.9413, and 31.87, for MSE, SSIM, and PSNR, respectively. In contrast, in the case of comparison between LQ and HQ ground truth median values of the metrics are equal to 0.0071, 0.8304, and 21.48 for MSE, SSIM, and PSNR respectively. Therefore, we observe a significant increase ranging from 14% to 49% for SSIM and PSNR respectively. These results, together with other single-system cross-modality studies, provide proof of concept for further implementation of a cross-system biological image quality enhancement. © 2024, CC BY-SA.

关键词： Fluorescence imaging

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Properties of Donor Qubits in ZnO Formed by Indium-Ion Implantation

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physical Review Applied 2023年第5期19卷 054090-054090页

作者： Xingyi Wang Christian Zimmermann Michael Titze Vasileios Niaouris Ethan R. Hansen Samuel H. D’Ambrosia Lasse Vines Edward S. Bielejec Kai-Mei C. Fu Department of Electrical Engineering University of Washington Seattle Washington 98195 USA Department of Physics University of Washington Seattle Washington 98195 USA Sandia National Laboratories Albuquerque New Mexico 87123 United States Department of Physics and Centre for Materials Science and Nanotechnology University of Oslo Blindern N-0316 Oslo Norway Physical Sciences Division Pacific Northwest National Laboratory Richland Washington 99352 USA

Neutral shallow donors (D0) in ZnO have emerged as a promising candidate for solid-state spin qubits. Here we report on the formation of D0 in ZnO via implantation of In and subsequent annealing. The implanted In donors exhibit optical and spin properties on par with those of in situ–doped donors. The inhomogeneous linewidth of the donor-bound-exciton transition is less than 10 GHz, comparable to the optical linewidth of in situ In. Longitudinal spin relaxation times (T1) exceed reported values for in situ Ga donors, indicating that residual In-implantation damage does not degrade T1. Two-laser Raman spectroscopy of the donor spin reveals the hyperfine interaction of the donor electron with the spin-9/2 In nuclei. This work is an important step toward the deterministic formation of In-donor qubits in ZnO with optical access to a long-lived nuclear-spin memory.

关键词： Defects Quantum control Quantum information with solid state qubits Quantum memories Doped semiconductors Annealing Ion implantation Optically detected magnetic resonance

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