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In this paper, we present a fixed point method for high-precision computation of number $\pi$ based on the sine function. Let $P\in \mathbb{N}$. We define the function: \[ S\left(x\right) =x+\sum_{k=1}^{P}\left(\prod_{\ell=1}^{k-1}\frac…

General Mathematics · Mathematics 2026-03-18 Alois Schiessl

Low precision arithmetic, in particular half precision floating point arithmetic, is now available in commercial hardware. Using lower precision can offer significant savings in computation and communication costs with proportional savings…

Numerical Analysis · Mathematics 2021-11-16 Eda Oktay , Erin Carson

Spectral deferred correction (SDC) methods are an attractive approach to iteratively computing collocation solutions to an ODE by performing so-called sweeps with a low-order time stepping method. SDC allows to easily construct high order…

Numerical Analysis · Mathematics 2016-03-18 Robert Speck , Daniel Ruprecht , Michael Minion , Matthew Emmett , Rolf Krause

In this article we investigate a finite element formulation of strongly monotone quasi-linear elliptic PDEs in the context of fixed-point iterations. As opposed to Newton's method, which requires information from the previous iteration in…

Numerical Analysis · Mathematics 2015-07-01 Scott Congreve , Thomas P. Wihler

In this paper, we develop a low-rank method with high-order temporal accuracy using spectral deferred correction (SDC) to compute linear matrix differential equations. In [1], a low rank numerical method is proposed to correct the modeling…

Numerical Analysis · Mathematics 2024-12-13 Shun Li , Yan Jiang , Yingda Cheng

This paper provides the first proof that Anderson acceleration (AA) improves the convergence rate of general fixed point iterations. AA has been used for decades to speed up nonlinear solvers in many applications, however a rigorous…

Numerical Analysis · Mathematics 2019-02-22 Claire Evans , Sara Pollock , Leo G. Rebholz , Mengying Xiao

Recently, a class of algorithms combining classical fixed point iterations with repeated random sparsification of approximate solution vectors has been successfully applied to eigenproblems with matrices as large as $10^{108} \times…

Numerical Analysis · Mathematics 2025-04-28 Jonathan Weare , Robert J. Webber

This paper proposes a novel parallel stochastic gradient descent (SGD) method that is obtained by applying parallel sets of SGD iterations (each set operating on one node using the data residing in it) for finding the direction in each…

Machine Learning · Computer Science 2013-11-05 Dhruv Mahajan , S. Sathiya Keerthi , S. Sundararajan , Leon Bottou

We consider a class of L\'evy-driven stochastic differential equations (SDEs) with McKean-Vlasov (MK-V) interaction in the drift coefficient. It is assumed that the coefficient is bounded, affine in the state variable, and only measurable…

Probability · Mathematics 2018-12-13 Ankush Agarwal , Stefano Pagliarani

This paper presents a way to define, classify and accelerate the order of convergence of an uncountable family of fractional fixed point methods, which may be useful to continue expanding the applications of fractional operators. The…

Numerical Analysis · Mathematics 2024-03-27 A. Torres-Hernandez , F. Brambila-Paz , R. Montufar-Chaveznava

Solving linear systems is a ubiquitous task in science and engineering. Because directly inverting a large-scale linear system can be computationally expensive, iterative algorithms are often used to numerically find the inverse. To…

Numerical Analysis · Mathematics 2021-07-20 Zheyuan Zhu , Andrew B. Klein , Guifang Li , Shuo Pang

Recently, Krukier et al. [Generalized skew-Hermitian triangular splitting iteration methods for saddle-point linear systems, Numer. Linear Algebra Appl. 21 (2014) 152-170] proposed an efficient generalized skew-Hermitian triangular…

Numerical Analysis · Mathematics 2014-02-25 Yan Dou , Ai-Li Yang , Yu-Jiang Wu

Although Anderson acceleration (AA) is known to speed up fixed-point iterations, it is rarely applied in constrained optimization, in particular sequential quadratic programming (SQP). We show that the local convergence behavior of a…

Optimization and Control · Mathematics 2026-04-17 Jonathan Frey , David Kiessling , Katrin Baumgärtner , Moritz Diehl

Symmetric positive semi-definite (SPSD) matrix approximation methods have been extensively used to speed up large-scale eigenvalue computation and kernel learning methods. The standard sketch based method, which we call the prototype model,…

Machine Learning · Computer Science 2016-12-13 Shusen Wang , Zhihua Zhang , Tong Zhang

We propose and analyze an iterative high-order hybridized discontinuous Galerkin (iHDG) discretization for linear partial differential equations. We improve our previous work (SIAM J. Sci. Comput. Vol. 39, No. 5, pp. S782--S808) in several…

Numerical Analysis · Mathematics 2018-05-23 Sriramkrishnan Muralikrishnan , Minh-Binh Tran , Tan Bui-Thanh

By developing new efficient techniques and using an appropriate fixed point theorem, we derive several new sufficient conditions for the pseudo almost periodic solutions with double measure for some system of differential equations with…

Analysis of PDEs · Mathematics 2020-03-11 Mohsen Miraoui , Dušan D. Repovš

This article presents a class of new relaxation modulus-based iterative methods to process the large and sparse implicit complementarity problem (ICP). Using two positive diagonal matrices, we formulate a fixed-point equation and prove that…

Optimization and Control · Mathematics 2023-06-07 Bharat Kumar , Deepmala , A. K. Das

In this paper, we introduce a new modified Ishikawa iteration for finding a common element of the set of solutions of an equilibrium problem and the set of fixed points of generalized hybrid mappings in a Hilbert space. Our results…

Functional Analysis · Mathematics 2014-10-21 Sattar Alizadeh , Fridoun Moradlou

For a linear complementarity problem, we present a relaxaiton accelerated two-sweep matrix splitting iteration method. The convergence analysis illustrates that the proposed method converges to the exact solution of the linear…

Optimization and Control · Mathematics 2020-12-02 Dongkai Li , Li Wang , Yuying Liu

For a wide class of polynomially nonlinear systems of partial differential equations we suggest an algorithmic approach that combines differential and difference algebra to analyze s(trong)-consistency of finite difference approximations.…

Symbolic Computation · Computer Science 2020-09-04 Vladimir P. Gerdt , Daniel Robertz , Yuri A. Blinkov