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The dynamic behavior of jointed assemblies exhibiting friction nonlinearities features amplitude-dependent dissipation and stiffness. To develop numerical simulations for predictive and design purposes, macro-scale High Fidelity Models…

Computational Engineering, Finance, and Science · Computer Science 2022-04-27 Ahmed Amr Morsy , Mariella Kast , Paolo Tiso

In this paper, a new iterative two-level algorithm is presented for solving the finite element discretization for nonsymmetric or indefinite elliptic problems. The iterative two-level algorithm uses the same coarse space as the traditional…

Numerical Analysis · Mathematics 2023-01-05 Ming Tang , Xiaoqing Xing , Ying Yang , Liuqiang Zhong

This paper studies a low-communication algorithm for solving elliptic partial differential equations (PDE's) on high-performance machines, the nested iteration with range decomposition algorithm (NIRD). Previous work has shown that NIRD…

Numerical Analysis · Mathematics 2019-06-26 Wayne Mitchell , Tom Manteuffel

We propose a Hermite spectral method for the inelastic Boltzmann equation, which makes two-dimensional periodic problem computation affordable by the hardware nowadays. The new algorithm is based on a Hermite expansion, where the expansion…

Numerical Analysis · Mathematics 2023-08-15 Ruo Li , Yixiao Lu , Yanli Wang

Image modeling and simulation are critical to extending the limits of leading edge lithography technologies used for IC making. Simultaneous source mask optimization (SMO) has become an important objective in the field of computational…

Bilevel optimization aims to optimize an outer objective function that depends on the solution to an inner optimization problem. It is routinely used in Machine Learning, notably for hyperparameter tuning. The conventional method to compute…

Machine Learning · Computer Science 2024-02-27 Zhenzhang Ye , Gabriel Peyré , Daniel Cremers , Pierre Ablin

When equipped with efficient optimization algorithms, the over-parameterized neural networks have demonstrated high level of performance even though the loss function is non-convex and non-smooth. While many works have been focusing on…

Machine Learning · Computer Science 2021-03-11 Zhiqi Bu , Shiyun Xu , Kan Chen

Nonparametric models are versatile, albeit computationally expensive, tool for modeling mixture models. In this paper, we introduce spectral methods for the two most popular nonparametric models: the Indian Buffet Process (IBP) and the…

Machine Learning · Computer Science 2017-04-04 Hsiao-Yu Fish Tung , Chao-Yuan Wu , Manzil Zaheer , Alexander J. Smola

Non-Hermitian (NH) quantum systems have emerged as a powerful framework for describing open quantum systems, non-equilibrium dynamics, and engineered quantum optical materials. However, solving the ground-state properties of NH systems is…

Quantum Physics · Physics 2025-12-17 Lavoisier Wah , Remmy Zen , Flore K. Kunst

Meshfree radial basis function (RBF) methods are popular tools used to numerically solve partial differential equations (PDEs). They take advantage of being flexible with respect to geometry, easy to implement in higher dimensions, and can…

Numerical Analysis · Mathematics 2018-03-29 G. Garmanjani , R. Cavoretto , M. Esmaeilbeigi

A novel smooth immersed boundary method (IBM) based on a direct-forcing formulation is proposed to simulate incompressible dense particle-laden flows. This IBM relies on a regularization of the transfer function between the Eulerian grid…

Computational Physics · Physics 2023-04-24 Victor Chéron , Fabien Evrard , Berend van Wachem

Derivative boundary conditions introduce challenges for mesh-free discretizations of PDEs on surfaces, especially when the domain is represented by randomly sampled point clouds. The recently developed two-step tangent-space RBF-generated…

Numerical Analysis · Mathematics 2026-03-31 Peng Chen , Shixiao Willing Jiang , Rongji Li , Qile Yan

This work introduces an adaptive mesh refinement technique for hierarchical hybrid grids with the goal to reach scalability and maintain excellent performance on massively parallel computer systems. On the block structured hierarchical…

Numerical Analysis · Mathematics 2025-08-11 Benjamin Mann , Ulrich Rüde

With advances in scientific computing, computer experiments are increasingly used for optimizing complex systems. However, for modern applications, e.g., the optimization of nuclear physics detectors, each experiment run can require…

Machine Learning · Statistics 2025-08-08 Hwanwoo Kim , Simon Mak , Ann-Kathrin Schuetz , Alan Poon

This article considers the extension of two-grid $hp$-version discontinuous Galerkin finite element methods for the numerical approximation of second-order quasilinear elliptic boundary value problems of monotone type to the case when…

Numerical Analysis · Mathematics 2021-12-10 Scott Congreve , Paul Houston

In this paper, we develop a new reduced basis (RB) method, named as Single Eigenvalue Acceleration Method (SEAM), for second-order parabolic equations with homogeneous Dirichlet boundary conditions. The high-fidelity numerical method adopts…

Numerical Analysis · Mathematics 2023-02-16 Qijia Zhai , Qingguo Hong , Xiaoping Xie

This work introduces a new approach for accelerating the numerical analysis of time-domain partial differential equations (PDEs) governing complex physical systems. The methodology is based on a combination of a classical reduced-order…

Machine Learning · Computer Science 2024-06-06 Victor Matray , Faisal Amlani , Frédéric Feyel , David Néron

This article proposes new strategies for solving two-point Fractional order Nonlinear Boundary Value Problems(FN-BVPs) with Robin Boundary Conditions(RBCs). In the new numerical schemes, a two-point FNBVP is transformed into a system of…

Numerical Analysis · Mathematics 2020-10-06 Junseo Lee , Bongsoo Jang , Hyunju Kim

This paper is concerned with the fundamental problem of estimating chirp parameters from a mixture of linear chirp signals. Unlike most previous methods, which solve the problem by discretizing the parameter space and then estimating the…

Signal Processing · Electrical Eng. & Systems 2025-03-20 Dehui Yang , Feng Xi

This paper proposes a projection-based implicit modeling method (PIMM) for functionally graded lattice optimization, which does not require any homogenization techniques. In this method, a parametric projection function is proposed to link…

Computational Physics · Physics 2020-08-18 Hao Deng , Albert C. To