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We construct finite-dimensional approximations of solution spaces of divergence form operators with $L^\infty$-coefficients. Our method does not rely on concepts of ergodicity or scale-separation, but on the property that the solution space…

Numerical Analysis · Mathematics 2011-08-05 Houman Owhadi , Lei Zhang

In many areas of engineering, nonlinear numerical analysis is playing an increasingly important role in supporting the design and monitoring of structures. Whilst increasing computer resources have made such formerly prohibitive analyses…

Numerical Analysis · Mathematics 2020-07-02 Thomas Simpson , Nikolaos Dervilis , Eleni Chatzi

Elliptic Partial Differential Equations (PDEs) play a central role in computing the equilibrium conditions of physical problems (heat, gravitation, electrostatics, etc.). Efficient solutions to elliptic PDEs are also relevant to computer…

Graphics · Computer Science 2026-02-13 Zhiyuan Zhang , Amir Vaxman , Stefanos-Aldo Papanicolopulos , Kartic Subr

We propose a new discretization method for PDEs on moving domains in the setting of unfitted finite element methods, which is provably higher-order accurate in space and time. In the considered setting, the physical domain that evolves…

Numerical Analysis · Mathematics 2022-02-18 Yimin Lou , Christoph Lehrenfeld

In this work, we develop and analyze a higher-order finite element method for the multidimensional fragmentation equation. To the best of our knowledge, this is the first study to establish a rigorous, conforming finite element framework…

Numerical Analysis · Mathematics 2026-04-10 Arushi , Naresh Kumar

Parameter estimation in inverse problems involving partial differential equations (PDEs) underpins modeling across scientific disciplines, especially when parameters vary in space or time. Physics-informed Machine Learning (PhiML)…

Machine Learning · Computer Science 2025-05-20 Ananyae Kumar Bhartari , Vinayak Vinayak , Vivek B Shenoy

Algorithms, data structures, coding techniques, and other methods that reduce bit-flips are being sought to best utilize hardware where flipping bits is the dominating cost. Write efficient memories were introduced by Ahlswede and Zhang as…

Data Structures and Algorithms · Computer Science 2019-08-16 Matthew Gray

We construct high order symmetric volume-preserving methods for the relativistic dynamics of a charged particle by the splitting technique with processing. Via expanding the phase space to include time $t$, we give a more general…

Computational Physics · Physics 2016-10-12 Yang He , Yajuan Sun , Ruili Zhang , Yulei Wang , Jian Liu , Hong Qin

Radial basis function generated finite difference (RBF-FD) methods for PDEs require a set of interpolation points which conform to the computational domain $\Omega$. One of the requirements leading to approximation robustness is to place…

Numerical Analysis · Mathematics 2021-04-07 Igor Tominec , Eva Breznik

Numerical methods such as the Finite Element Method (FEM) have been successfully adapted to utilize the computational power of GPU accelerators. However, much of the effort around applying FEM to GPU's has been focused on high-order FEM due…

The multiscale hybrid-mixed (MHM) method consists of a multi-level strategy to approximate the solution of boundary value problems with heterogeneous coefficients. In this context, we propose a family of low-order finite elements for the…

Numerical Analysis · Mathematics 2024-03-26 Antônio Tadeu Azevedo Gomes , Weslley da Silva Pereira , Frédéric Valentin

We present an algorithm for $hp$-adaptive collocation-based mesh-free numerical analysis of partial differential equations. Our solution procedure follows a well-established iterative solve-estimate-mark-refine paradigm. The solve phase…

Numerical Analysis · Mathematics 2023-01-25 Mitja Jančič , Gregor Kosec

We propose an adaptive iteratively linearized finite element method (AILFEM) in the context of strongly monotone nonlinear operators in Hilbert spaces. The approach combines adaptive mesh-refinement with an energy-contractive linearization…

Numerical Analysis · Mathematics 2025-03-18 Ani Miraçi , Dirk Praetorius , Julian Streitberger

In the present work, we investigate the computational efficiency afforded by higher-order finite-element discretization of the saddle-point formulation of orbital-free density functional theory. We first investigate the robustness of viable…

Computational Physics · Physics 2015-05-30 Phani Motamarri , Mrinal Iyer , Jaroslaw Knap , Vikram Gavini

Computational analysis with the finite element method requires geometrically accurate meshes. It is well known that high-order meshes can accurately capture curved surfaces with fewer degrees of freedom in comparison to low-order meshes.…

Mathematical Software · Computer Science 2024-01-30 Ketan Mittal , Veselin A. Dobrev , Patrick Knupp , Tzanio Kolev , Franck Ledoux , Claire Roche , Vladimir Z. Tomov

We present a one-dimensional high-order moving-mesh finite element method for moving boundary problems where the boundary velocity depends implicitly on the solution in the interior of the domain. The method employs a conservative arbitrary…

Numerical Analysis · Mathematics 2025-09-05 Matthew E Hubbard , Thomas J Radley

Predicting the binding affinity between small molecules and target macromolecules while combining both speed and accuracy, is a cornerstone of modern computational drug discovery which is critical for accelerating therapeutic development.…

In this work, we propose a novel adaptive stochastic gradient-free (ASGF) approach for solving high-dimensional nonconvex optimization problems based on function evaluations. We employ a directional Gaussian smoothing of the target function…

Optimization and Control · Mathematics 2022-01-19 Anton Dereventsov , Clayton G. Webster , Joseph D. Daws

We propose highly accurate finite-difference schemes for simulating wave propagation problems described by linear second-order hyperbolic equations. The schemes are based on the summation by parts (SBP) approach modified for applications…

Numerical Analysis · Mathematics 2014-02-04 Leonid Dovgilovich , Ivan Sofronov

We generalise the non-affine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic…

Disordered Systems and Neural Networks · Physics 2020-07-27 Ivan Kriuchevskyi , Vladimir V. Palyulin , Rico Milkus , Robert M. Elder , Timothy W. Sirk , Alessio Zaccone
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