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Related papers: Data-driven low-fidelity models for multi-fidelity…

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Multi-fidelity simulation is a widely used strategy to reduce the computational cost of many-query numerical simulation tasks such as uncertainty quantification, design space exploration, and design optimization. The reduced basis approach…

Numerical Analysis · Mathematics 2025-09-17 Murray Cutforth , Tiffany Fan , Tony Zahtila , Alireza Doostan , Eric Darve

Many inverse problems in nuclear fusion and high-energy astrophysics research, such as the optimization of tokamak reactor geometries or the inference of black hole parameters from interferometric images, necessitate high-dimensional…

Machine Learning · Computer Science 2025-05-09 Jonathan Gorard , Ammar Hakim , Hong Qin , Kyle Parfrey , Shantenu Jha

A comprehensive gyrokinetic simulation model has been implemented in the global toroidal gyrokinetic code (GTC) and verified for studying low-frequency waves and turbulence in magnetic fusion plasmas by treating all kinetic-MHD processes on…

Channel modeling for satellite-to-underwater laser communication (StULC) links remains challenging due to long distances and the diversity of the channel constituents. The StULC channel is typically segmented into three isolated channels:…

Signal Processing · Electrical Eng. & Systems 2025-10-22 Zhixing Wang , Renzhi Yuan , Haifeng Yao , Chuang Yang , Mugen Peng

In regimes of low signal strengths and therefore a small signal-to-noise ratio, standard data analysis methods often fail to accurately estimate system properties. We present a method based on Monte Carlo simulations to effectively restore…

We describe results from particle-in-cell simulations of driven turbulence in collisionless, magnetized, relativistic pair plasma. This physical regime provides a simple setting for investigating the basic properties of kinetic turbulence…

High Energy Astrophysical Phenomena · Physics 2018-05-23 Vladimir Zhdankin , Dmitri A. Uzdensky , Gregory R. Werner , Mitchell C. Begelman

We present a multi-fidelity method for uncertainty quantification of parameter estimates in complex systems, leveraging generative models trained to sample the target conditional distribution. In the Bayesian inference setting, traditional…

Machine Learning · Computer Science 2025-04-03 Caroline Tatsuoka , Minglei Yang , Dongbin Xiu , Guannan Zhang

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available…

Condensed Matter · Physics 2009-10-31 W. M. C. Foulkes , Randolph Q. Hood , R. J. Needs

Random field Monte Carlo (MC) reliability analysis is a robust stochastic method to determine the probability of failure. This method, however, requires a large number of numerical simulations demanding high computational costs. This paper…

Machine Learning · Computer Science 2022-04-14 Mohammad Aminpour , Reza Alaie , Navid Kardani , Sara Moridpour , Majidreza Nazem

The vast separation dividing the characteristic times of energy confinement and turbulence in the core of toroidal plasmas makes first-principles prediction on long timescales extremely challenging. Here we report the demonstration of a…

Practical structural engineering problems often exhibit a significant degree of uncertainty in the material properties being used, the dimensions of the modeled structures, etc. In this paper, we consider a cantilever beam and a beam…

Computational Engineering, Finance, and Science · Computer Science 2018-09-03 Philippe Blondeel , Pieterjan Robbe , Cédric van hoorickx , Geert Lombaert , Stefan Vandewalle

In many plasma systems, introducing a small background shear flow is enough to stabilize the system linearly. The nonlinear dynamics are much less sensitive to sheared flows than the average linear growthrates, and very small amplitude…

Plasma Physics · Physics 2018-01-17 Chris C. T. Pringle , Ben F. McMillan , Bogdan Teaca

A method for the multifidelity Monte Carlo (MFMC) estimation of statistical quantities is proposed which is applicable to computational budgets of any size. Based on a sequence of optimization problems each with a globally minimizing…

Numerical Analysis · Mathematics 2022-11-15 Anthony Gruber , Max Gunzburger , Lili Ju , Zhu Wang

We study some aspects of a Monte Carlo method invented by Maggs and Rossetto for simulating systems of charged particles. It has the feature that the discretized electric field is updated locally when charges move. Results of simulations of…

Statistical Mechanics · Physics 2007-06-27 P. A. McClarty

Ice sheet simulations suffer from vast parametric uncertainties, such as the basal sliding boundary condition or geothermal heat flux. Quantifying the resulting uncertainties in predictions is of utmost importance to support judicious…

Geophysics · Physics 2024-12-10 Nicole Aretz , Max Gunzburger , Mathieu Morlighem , Karen Willcox

Complex nonlinear turbulent dynamical systems are ubiquitous in many areas. Recovering unobserved state variables is an important topic for the data assimilation of turbulent systems. In this article, an efficient continuous in time data…

Fluid Dynamics · Physics 2021-11-03 Nan Chen , Yuchen Li , Evelyn Lunasin

This paper presents a detailed study on the controlled experimental observation of drift wave instabilities in an inhomogeneous Six pole cusp magnetic field generated by an in-house developed Multi-pole line cusp magnetic field device (MPD)…

Plasma Physics · Physics 2021-12-08 A. D. Patel , M. Sharma , R. Ganesh , N. Ramasubramanian , P. K. Chattopadhyay

A case study in bifurcation and stability analysis is presented, in which reduced dynamical system modelling yields substantial new global and predictive information about the behaviour of a complex system. The first smooth pathway, free of…

Plasma Physics · Physics 2007-05-23 R. Ball

Fabrication process variations are a major source of yield degradation in the nano-scale design of integrated circuits (IC), microelectromechanical systems (MEMS) and photonic circuits. Stochastic spectral methods are a promising technique…

Computational Engineering, Finance, and Science · Computer Science 2016-11-08 Zheng Zhang , Tsui-Wei Weng , Luca Daniel

Weakly collisional space plasmas are rarely in local thermal equilibrium and often exhibit non-Maxwellian electron and ion velocity distributions that lead to the growth of microinstabilities, that is, enhanced electric and magnetic fields…

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