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A numerical scheme is presented for approximating fractional order Poisson problems in two and three dimensions. The scheme is based on reformulating the original problem posed over $\Omega$ on the extruded domain…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa

The study of parametric differential equations plays a crucial role in weather forecasting and epidemiological modeling. These phenomena are better represented using fractional derivatives due to their inherent memory or hereditary effects.…

Numerical Analysis · Mathematics 2025-03-31 S M Sivalingam , V Govindaraj , A. S. Hendy

In this work, we consider an extension to parabolic problems of the variational multiscale method with spectral approximation of the sub-scales. We first discretize in time using a finite difference scheme and second, apply the…

Numerical Analysis · Mathematics 2018-01-25 Tomás Chacón Rebollo , Soledad Fernández-García

A collection of codes (in MATLAB & Fortran 77), and examples, for solving reaction-diffusion equations in one and two space dimensions is presented. In areas of the mathematical community spectral methods are used to remove the stiffness…

Numerical Analysis · Mathematics 2018-10-18 Richard V. Craster , Roberto Sassi

We introduce a novel spectral element method based on the ultraspherical spectral method and the hierarchical Poincar\'{e}-Steklov scheme for solving second-order linear partial differential equations on polygonal domains with unstructured…

Numerical Analysis · Mathematics 2021-05-19 Daniel Fortunato , Nicholas Hale , Alex Townsend

In this paper, a new deep-learning architecture for solving the non-linear Falkner-Skan equation is proposed. Using Legendre and Chebyshev neural blocks, this approach shows how orthogonal polynomials can be used in neural networks to…

Machine Learning · Computer Science 2023-08-08 Alireza Afzal Aghaei , Kourosh Parand , Ali Nikkhah , Shakila Jaberi

We have recently presented the multichannel Dyson equation as an alternative to the standard single-channel Dyson equation. While the latter involves a single many-body Green's function, the former uses a multichannel Green's function in…

Strongly Correlated Electrons · Physics 2025-07-17 Stefano Paggi , J. Arjan Berger , Pina Romaniello

Inspired by the recent proposed Legendre orthogonal polynomial representation of imaginary-time Green's functions, we develop an alternate representation for the Green's functions of quantum impurity models and combine it with the…

Strongly Correlated Electrons · Physics 2016-12-08 Li Huang , Liang Du

In this paper, the Green's function and decomposition technique is proposed for solving the coupled Lane-Emden equations. This approach depends on constructing Green's function before establishing the recursive scheme for the series…

Numerical Analysis · Mathematics 2020-05-25 Randhir Singh

We present a family of algorithms for the numerical approximation of the Schr\"odinger equation with potential concentrated at a finite set of points. Our methods belong to the so-called fast and oblivious convolution quadrature algorithms.…

Numerical Analysis · Mathematics 2019-12-02 Lehel Banjai , María López-Fernández

A three-dimensional (3D) Poisson solver with longitudinal periodic and transverse open boundary conditions can have important applications in beam physics of particle accelerators. In this paper, we present a fast efficient method to solve…

Accelerator Physics · Physics 2017-09-13 Ji Qiang

We present a symmetry-enabled direct quantum protocol for computing many-body Green's functions, a central tool for studying strongly correlated quantum systems. Our protocol relies only on native time evolution and straightforward…

Quantum Physics · Physics 2026-03-03 Changhao Yi , Cunlu Zhou

The single particle Green's function provides valuable information on the momentum and energy-resolved spectral properties for a strongly correlated system. In large-scale numerical calculations using quantum Monte Carlo (QMC), dynamical…

Strongly Correlated Electrons · Physics 2024-10-01 Maksymilian Kliczkowski , Lauren Keyes , Sayantan Roy , Thereza Paiva , Mohit Randeria , Nandini Trivedi , Maciej M. Maska

This paper examines the effectiveness of the Dyson-Schwinger (DS) equations as a calculational tool in quantum field theory. The DS equations are an infinite sequence of coupled equations that are satisfied exactly by the connected Green's…

Mathematical Physics · Physics 2023-03-29 Carl M. Bender , Christos Karapoulitidis , S. P. Klevansky

Highly heterogeneous, anisotropic coefficients, e.g. in the simulation of carbon-fibre composite components, can lead to extremely challenging finite element systems. Direct solvers for the resulting large and sparse linear systems suffer…

Numerical Analysis · Mathematics 2021-06-16 Peter Bastian , Robert Scheichl , Linus Seelinger , Arne Strehlow

In contexts where relevant problems can easily attain configuration spaces of enormous sizes, solving Linear Differential Equations (LDEs) can become a hard achievement for classical computers; on the other hand, the rise of quantum…

Quantum Physics · Physics 2023-01-31 João H. Romeiro , Frederico Brito

In this paper, we present a novel spectral renormalization exponential integrator method for solving gradient flow problems. Our method is specifically designed to simultaneously satisfy discrete analogues of the energy dissipation laws and…

Numerical Analysis · Mathematics 2023-10-03 Dianming Hou , Lili Ju , Zhonghua Qiao

We present a new boundary integral formulation for time-harmonic wave diffraction from two-dimensional structures with many layers of arbitrary periodic shape, such as multilayer dielectric gratings in TM polarization. Our scheme is robust…

Numerical Analysis · Mathematics 2015-06-23 Min Hyung Cho , Alex H. Barnett

We introduce the Shifted Legendre Symbol Problem and some variants along with efficient quantum algorithms to solve them. The problems and their algorithms are different from previous work on quantum computation in that they do not appear…

Quantum Physics · Physics 2007-05-23 Wim van Dam , Sean Hallgren

Discrete diffusion models have emerged as a powerful generative modeling framework for discrete data with successful applications spanning from text generation to image synthesis. However, their deployment faces challenges due to the high…

Machine Learning · Computer Science 2025-12-01 Yinuo Ren , Haoxuan Chen , Yuchen Zhu , Wei Guo , Yongxin Chen , Grant M. Rotskoff , Molei Tao , Lexing Ying