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Multipoint polynomial evaluation and interpolation are fundamental for modern symbolic and numerical computing. The known algorithms solve both problems over any field of constants in nearly linear arithmetic time, but the cost grows to…

Numerical Analysis · Mathematics 2017-04-19 Victor Y. Pan

A Green's function based solver for the modified Bessel equation has been developed with the primary motivation of solving the Poisson equation in cylindrical geometries. The method is implemented using a Discrete Hankel Transform and a…

Numerical Analysis · Mathematics 2011-10-11 Michael Carley

A numerical method is developed for calculating the real time Green's functions of very large sparse Hamiltonian matrices, which exploits the numerical solution of the inhomogeneous time-dependent Schroedinger equation. The method has a…

Computational Physics · Physics 2007-05-23 Toshiaki Iitaka

This paper proposes a novel method, Explicit Flow Matching (ExFM), for training and analyzing flow-based generative models. ExFM leverages a theoretically grounded loss function, ExFM loss (a tractable form of Flow Matching (FM) loss), to…

Machine Learning · Computer Science 2024-07-03 Gleb Ryzhakov , Svetlana Pavlova , Egor Sevriugov , Ivan Oseledets

We propose a simple interpolation-based method for the efficient approximation of gradients in neural ODE models. We compare it with the reverse dynamic method (known in the literature as "adjoint method") to train neural ODEs on…

Neural and Evolutionary Computing · Computer Science 2020-11-03 Talgat Daulbaev , Alexandr Katrutsa , Larisa Markeeva , Julia Gusak , Andrzej Cichocki , Ivan Oseledets

The two-time Green function method in quantum electrodynamics of high-Z few-electron atoms is described in detail. This method provides a simple procedure for deriving formulas for the energy shift of a single level and for the energies and…

Atomic Physics · Physics 2009-11-06 V. M. Shabaev

The Fast Marching Method is a very popular algorithm to compute times-of-arrival maps (distances map measured in time units). Since their proposal in 1995, it has been applied to many different applications such as robotics, medical…

Numerical Analysis · Computer Science 2015-06-12 Javier V. Gomez , David Alvarez , Santiago Garrido , Luis Moreno

Diffusion Monte Carlo (DMC) simulations for fermions are becoming the standard to provide high quality reference data in systems that are too large to be investigated via quantum chemical approaches. DMC with the fixed-node approximation…

Chemical Physics · Physics 2016-07-06 Andrea Zen , Sandro Sorella , Michael J. Gillan , Angelos Michaelides , Dario Alfè

We introduce a general scheme to consistently truncate equations of motion for Green's functions. Our scheme is guaranteed to generate physical Green's functions with real excitation energies and positive spectral weights. There are free…

Strongly Correlated Electrons · Physics 2021-02-24 Francesco Catalano , Johan Nilsson

Generative policies based on diffusion and flow matching achieve strong performance in robotic manipulation by modeling multi-modal human demonstrations. However, their reliance on iterative Ordinary Differential Equation (ODE) integration…

We present a fast algorithm that constructs a data-sparse approximation of matrices arising in the context of integral equation methods for elliptic partial differential equations. The new algorithm uses Green's representation formula in…

Numerical Analysis · Mathematics 2015-10-27 Steffen Börm , Sven Christophersen

In this paper, we propose a new trigonometric interpolation algorithm and establish relevant convergent properties. The method adjusts an existing trigonometric interpolation algorithm such that it can better leverage Fast Fourier Transform…

Numerical Analysis · Mathematics 2025-05-06 Xiaorong Zou

In this article we use linear algebra to improve the computational time for the obtaining of Green's functions of linear differential equations with reflection (DER). This is achieved by decomposing both the `reduced' equation (the ODE…

Classical Analysis and ODEs · Mathematics 2017-07-05 F. Adrián F. Tojo

The need to approximate functions is ubiquitous in science, either due to empirical constraints or high computational cost of accessing the function. In high-energy physics, the precise computation of the scattering cross-section of a…

High Energy Physics - Phenomenology · Physics 2022-06-08 Ibrahim Chahrour , James D. Wells

This report details an approach to improve the accuracy and precision of free energy difference estimates using thermodynamic integration data (slope of the free energy with respect to the switching variable lambda) and its application to…

Computational Physics · Physics 2010-01-19 Conrad Shyu , F. Marty Ytreberg

This paper proposes a compressed sensing-based high-resolution direction-of-arrival estimation method called gradient orthogonal matching pursuit (GOMP). It contains two main steps: a sparse coding approximation step using the well-known…

Signal Processing · Electrical Eng. & Systems 2021-10-08 Khaled Ardah , Martin Haardt

The ill-posed analytic continuation problem for Green's functions or self-energies can be done using the Pad\'e rational polynomial approximation. However, to extract accurate results from this approximation, high precision input data of…

Strongly Correlated Electrons · Physics 2017-06-28 Xing-Jie Han , Hai-Jun Liao , Hai-Dong Xie , Rui-Zhen Huang , Zi Yang Meng , Tao Xiang

Recently, Gimbutas et al derived an elegant representation for the Green's functions of Stokes flow in a half-space. We present a fast summation method for sums involving these half-space Green's functions (stokeslets, stresslets and…

Numerical Analysis · Mathematics 2019-11-19 Shriram Srinivasan , Anna-Karin Tornberg

This paper presents a windowed Green function (WGF) method for the numerical solution of problems of elastic scattering by "locally-rough surfaces" (i.e., local perturbations of a half space), under either Dirichlet or Neumann boundary…

Computational Physics · Physics 2021-02-03 Oscar P. Bruno , Tao Yin

In simulation-based inferences for partially observed Markov process models (POMP), the by-product of the Monte Carlo filtering is an approximation of the log likelihood function. Recently, iterated filtering [14, 13] has originally been…

Methodology · Statistics 2018-02-26 Dao Nguyen
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