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A brief history of the impurity theories in semiconductors is provided. A bound exciton model is proposed for both donor- and acceptor- like impurities and point defects, which offers a unified understanding for "shallow" and "deep"…

Materials Science · Physics 2020-06-02 Yong Zhang

When modelling discontinuities (interfaces) using the finite element method, the standard approach is to use a conforming finite-element mesh in which the mesh matches the interfaces. However, this approach can prove cumbersome if the…

Computational Engineering, Finance, and Science · Computer Science 2024-06-06 Jedrzej Dobrzanski , Kajetan Wojtacki , Stanislaw Stupkiewicz

We develop an interpolation-based modeling framework for parameter-dependent partial differential equations arising in control, inverse problems, and uncertainty quantification. The solution is discretized in the physical domain using…

Numerical Analysis · Mathematics 2026-04-20 Erik Burman , Mats G. Larson , Karl Larsson , Jonatan Vallin

We present a deep learning approach to extract physical parameters (e.g., mobility, Schottky contact barrier height, defect profiles) of two-dimensional (2D) transistors from electrical measurements, enabling automated parameter extraction…

The extension of piezoresistance coefficient extraction method was proposed, for protection from errors in estimation of the thickness of the test structure membrane. This new approach requires finding models of elements of matrix of…

Mesoscale and Nanoscale Physics · Physics 2016-01-11 Zenon Gniazdowski , Bogdan Latecki , Pawel Kowalski

Electrical impedance tomography is an imaging modality for extracting information on the interior structure of a physical body from boundary measurements of current and voltage. This work studies a new robust way of modeling the contact…

Numerical Analysis · Mathematics 2022-07-06 J. Dardé , N. Hyvönen , T. Kuutela , T. Valkonen

We investigate solution methods for large-scale inverse problems governed by partial differential equations (PDEs) via Bayesian inference. The Bayesian framework provides a statistical setting to infer uncertain parameters from noisy…

Applications · Statistics 2023-02-08 Mina Karimi , Mehrdad Massoudi , Kaushik Dayal , Matteo Pozzi

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

The oversampling multiscale finite element method (MsFEM) is one of the most popular methods for simulating composite materials and flows in porous media which may have many scales. But the method may be inapplicable or inefficient in some…

Numerical Analysis · Mathematics 2012-11-16 Weibing Deng , Haijun Wu

All 21-cm signal experiments rely on electronic receivers that affect the data via both multiplicative and additive biases through the receiver's gain and noise temperature. While experiments attempt to remove these biases, the residuals of…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-14 Keith Tauscher , David Rapetti , Bang D. Nhan , Alec Handy , Neil Bassett , Joshua Hibbard , David Bordenave , Richard F. Bradley , Jack O. Burns

We present a novel framework for Finite Element Particle-in-Cell methods based on the discretization of the underlying Hamiltonian structure of the Vlasov-Maxwell system. We derive a semi-discrete Poisson bracket, which retains the defining…

Numerical Analysis · Mathematics 2017-10-05 Michael Kraus , Katharina Kormann , Philip J. Morrison , Eric Sonnendrücker

For a singularly perturbed elliptic model problem with two small parameters, we analyze finite element methods of any order on a Bakhvalov-type mesh. For convergence analysis, we construct a new interpolation by using the characteristics of…

Numerical Analysis · Mathematics 2020-11-26 Jin Zhang , Yanhui Lv

The ab-initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of…

A mixed finite element method (MFEM), using dual-parametric piecewise bi-quadratic and affine (DP-Q2-P1) finite element approximations for the deformation and the pressure like Lagrange multiplier respectively, is developed and analyzed for…

Analysis of PDEs · Mathematics 2019-04-30 Weijie Huang , Zhiping Li

A new particle-based sampling and approximate inference method, based on electrostatics and Newton mechanics principles, is introduced with theoretical ground, algorithm design and experimental validation. This method simulates an…

Artificial Intelligence · Computer Science 2024-07-01 Yongchao Huang

Strongly interacting electrons in clean two-dimensional devices are theorized to exhibit many distinct transport regimes, such as ballistic, hydrodynamic, or diffusive. Realistic samples often lie in crossover regimes between these…

Mesoscale and Nanoscale Physics · Physics 2026-05-14 Jack H. Farrell , Andrew Lucas

We construct a finite element method (FEM) for the infinity Laplacian. Solutions of this problem may be singular, which has prompted us to conduct an a posteriori analysis of the method deriving residual based estimators to drive an…

Numerical Analysis · Mathematics 2017-05-17 Omar Lakkis , Tristan Pryer

We propose an accurate and energy-stable parametric finite element method for solving the sharp-interface continuum model of solid-state dewetting in three-dimensional space. The model describes the motion of the film\slash vapor interface…

Numerical Analysis · Mathematics 2023-07-04 Weizhu Bao , Quan Zhao

A simple and efficient interface-fitted mesh generation algorithm is developed in this paper. This algorithm can produce a local anisotropic fitting mixed mesh which consists of both triangles and quadrilaterals near the interface. A new…

Numerical Analysis · Mathematics 2020-05-13 Jun Hu , Hua Wang

In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational…

Numerical Analysis · Mathematics 2021-10-12 Christian Beck , Sebastian Becker , Patrick Cheridito , Arnulf Jentzen , Ariel Neufeld