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Many modern data sets are sampled with error from complex high-dimensional surfaces. Methods such as tensor product splines or Gaussian processes are effective/well suited for characterizing a surface in two or three dimensions but may…

Machine Learning · Statistics 2017-06-16 Matthew W. Wheeler

Inverse problems constrained by partial differential equations (PDEs) play a critical role in model development and calibration. In many applications, there are multiple uncertain parameters in a model that must be estimated. However, high…

Numerical Analysis · Mathematics 2022-10-27 Joseph Hart , Bart van Bloemen Waanders

The goal of this paper is to solve the global sensitivity analysis for a particular control problem. More precisely, the boundary control problem of an open-water channel is considered, where the boundary conditions are defined by the…

Analysis of PDEs · Mathematics 2014-12-10 Alexandre Janon , Maëlle Nodet , Christophe Prieur , Clémentine Prieur

The term "Active Plasma Resonance Spectroscopy" (APRS) denotes a class of related techniques which utilize, for diagnostic purposes, the natural ability of plasmas to resonate on or near the electron plasma frequency $\omega_{\rm pe}$: A…

Plasma Physics · Physics 2015-06-16 Jens Oberrath , Ralf Peter Brinkmann

A newly developed sensitivity-driven approach is employed to study the role of energetic particles in suppressing turbulence-inducing micro-instabilities for a set of realistic JET-like cases with NBI deuterium and ICRH $^3$He fast ions.…

Plasma Physics · Physics 2021-05-26 Ionut-Gabriel Farcas , Alessandro Di Siena , Frank Jenko

Landslide run-out modeling involves various uncertainties originating from model input data. It is therefore desirable to assess the model's sensitivity. A global sensitivity analysis that is capable of exploring the entire input space and…

Fluid Dynamics · Physics 2021-08-17 Hu Zhao , Florian Amann , Julia Kowalski

We present results of a 2D3V kinetic Vlasov simulation of the Weibel instability. The kinetic Vlasov simulation allows us to investigate the velocity distribution of dilute plasmas, in which the effect of collisions between particles is…

High Energy Astrophysical Phenomena · Physics 2011-02-11 Akihiro Suzuki , Toshikazu Shigeyama

Two-stream (TS) and Bump-On-Tail (BOT) electron distributions can induce instabilities in collisionless plasmas, which is closely related to phenomena in space and fusion plasmas. Collisions can lead to unexpected plasma behavior,…

Plasma Physics · Physics 2024-07-18 Y. W. Hou , M. Y. Yu , J. F. Wang , C. Y. Liu , M. X. Chen , B. Wu

A problem of considerable importance within the field of uncertainty quantification (UQ) is the development of efficient methods for the construction of accurate surrogate models. Such efforts are particularly important to applications…

Computational Physics · Physics 2019-03-01 Rohit Tripathy , Ilias Bilionis

Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC)…

Plasma Physics · Physics 2025-06-11 S. R. Totorica , K. V. Lezhnin , W. Fox

Motivated by risk assessment of coastal flooding, we consider time-consuming simulators with a spatial output. The aim is to perform sensitivity analysis (SA), quantifying the influence of input parameters on the output. There are three…

We develop nonparametric Bayesian modelling approaches for Poisson processes, using weighted combinations of structured beta densities to represent the point process intensity function. For a regular spatial domain, such as the unit square,…

Methodology · Statistics 2021-06-10 Chunyi Zhao , Athanasios Kottas

Plasma dynamics is a multi-scale problem that involves many spatial and temporal scales. Turbulence connects the disparate scales in this system through a cascade that is established by nonlinear interactions. Most astrophysical plasma…

Plasma Physics · Physics 2019-01-30 C. A. González , T. Parashar , D. Gomez , W. H. Matthaeus , P. Dmitruk

Plasma supports collective modes and particle-wave interactions that leads to complex behavior in inertial fusion energy applications. While plasma can sometimes be modeled as a charged fluid, a kinetic description is useful towards the…

Plasma Physics · Physics 2022-11-28 Archis S. Joglekar , Alexander G. R. Thomas

Recent advances in local models for point processes have highlighted the need for flexible methodologies to account for the spatial heterogeneity of external covariates influencing process intensity. In this work, we introduce tessellated…

Methodology · Statistics 2025-04-11 Nicoletta D'Angelo

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

This work aims at identifying and quantifying uncertainties related to elastic and viscoelastic parameters, which characterize the arterial wall behavior, in one-dimensional modeling of the human arterial hemodynamics. The chosen uncertain…

Fluid Dynamics · Physics 2021-02-12 Giulia Bertaglia , Valerio Caleffi , Lorenzo Pareschi , Alessandro Valiani

Magnetic fields pervade the entire Universe and affect the formation and evolution of astrophysical systems from cosmological to planetary scales. The generation and dynamical amplification of extragalactic magnetic fields through cosmic…

Cosmology and Nongalactic Astrophysics · Physics 2016-04-27 F. Rincon , F. Califano , A. A. Schekochihin , F. Valentini

We study the robustness of system estimation to parametric perturbations in system dynamics and initial conditions. We define the problem of sensitivity-based parametric uncertainty quantification in dynamical system estimation. The main…

Systems and Control · Electrical Eng. & Systems 2025-09-09 Ayush Pandey

Graph neural networks are often used to model interacting dynamical systems since they gracefully scale to systems with a varying and high number of agents. While there has been much progress made for deterministic interacting systems,…

Machine Learning · Computer Science 2023-05-04 Andreas Look , Melih Kandemir , Barbara Rakitsch , Jan Peters
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