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Related papers: Grid method for divergence of averages

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Analytic continuation of imaginary time or frequency data to the real axis is a crucial step in extracting dynamical properties from quantum Monte Carlo simulations. The average spectrum method provides an elegant solution by integrating…

Computational Physics · Physics 2020-07-15 Khaldoon Ghanem , Erik Koch

We consider pointwise convergence of weighted ergodic averages along the sequence $\Omega(n)$, where $\Omega(n)$ denotes the number of prime factors of $n$ counted with multiplicities. It was previously shown that $\Omega(n)$ satisfies the…

Dynamical Systems · Mathematics 2024-10-15 Kaitlyn Loyd , Sovanlal Mondal

Stochastic gradient descent (SGD) is a promising numerical method for solving large-scale inverse problems. However, its theoretical properties remain largely underexplored in the lens of classical regularization theory. In this note, we…

Numerical Analysis · Mathematics 2020-07-22 Tim Jahn , Bangti Jin

The average spectrum method is a promising approach for the analytic continuation of imaginary time or frequency data to the real axis. It determines the analytic continuation of noisy data from a functional average over all admissible…

Strongly Correlated Electrons · Physics 2020-02-14 Khaldoon Ghanem , Erik Koch

To describe the flow of a miscible quantity on a network, we introduce the graph wave equation where the standard continuous Laplacian is replaced by the graph Laplacian. This is a natural description of an array of inductances and…

Physics and Society · Physics 2012-10-25 Jean-Guy Caputo , Arnaud Knippel , Elie Simo

Sequences diverge either because they head off to infinity or because they oscillate. Part 1 \cite{Part1} of this paper laid the pure mathematics groundwork by defining Archimedean classes of infinite numbers as limits of smooth sequences.…

General Mathematics · Mathematics 2011-08-26 David Alan Paterson

Random graphs with prescribed degree sequences have been widely used as a model of complex networks. Comparing an observed network to an ensemble of such graphs allows one to detect deviations from randomness in network properties. Here we…

Statistical Mechanics · Physics 2007-05-23 R. Milo , N. Kashtan , S. Itzkovitz , M. E. J. Newman , U. Alon

The Abelian Sandpile Model is a discrete diffusion process defined on graphs (Dhar [10], Dhar et al. [11]) which serves as the standard model of self-organized criticality. The transience class of a sandpile is defined as the maximum number…

Mathematical Physics · Physics 2016-11-26 Ayush Choure , Sundar Vishwanathan

The goal of this expository article is a fairly self-contained account of some averaging processes of functions along sequences of the form $(\alpha^n x)^{}_{n\in\mathbb{N}}$, where $\alpha$ is a fixed real number with $| \alpha | > 1$ and…

Number Theory · Mathematics 2018-01-24 Michael Baake , Alan Haynes , Daniel Lenz

We prove the convergence of the law of grid-valued random walks, which can be seen as time-space Markov chains, to the law of a general diffusion process. This includes processes with sticky features, reflecting or absorbing boundaries and…

Probability · Mathematics 2024-11-15 Alexis Anagnostakis , Antoine Lejay , Denis Villemonais

In probability theory and statistics, the IID model represents a single population, and a large, potentially infinite sample from this population. Main theorems, in particular the central limit theorem and laws of large number (LLN) assure…

Statistics Theory · Mathematics 2017-10-02 Uwe Saint-Mont

In this paper we study an experimentally-observed connection between two seemingly unrelated processes, one from computational geometry and the other from differential geometry. The first one (which we call "grid peeling") is the…

Computational Geometry · Computer Science 2020-08-14 David Eppstein , Sariel Har-Peled , Gabriel Nivasch

We use techniques from the theory of electrical networks to give nearly tight bounds for the transience class of the Abelian sandpile model on the two-dimensional grid up to polylogarithmic factors. The Abelian sandpile model is a discrete…

Data Structures and Algorithms · Computer Science 2023-04-11 David Durfee , Matthew Fahrbach , Yu Gao , Tao Xiao

Averaging principle is an effective method for investigating dynamical systems with highly oscillating components. In this paper, we study three types of averaging principle for stochastic complex Ginzburg-Landau equations. Firstly, we…

Dynamical Systems · Mathematics 2022-11-22 Mengyu Cheng , Zhenxin Liu , Michael Röckner

This paper introduces an algorithmic approach to the analysis of bifurcation of limit cycles from the centers of nonlinear continuous differential systems via the averaging method. We develop three algorithms to implement the averaging…

Symbolic Computation · Computer Science 2019-05-10 Bo Huang , Chee Yap

A grid poset -- or grid for short -- is a product of chains. We ask, what does a random linear extension of a grid look like? In particular, we show that the average "jump number," i.e., the number of times that two consecutive elements in…

Combinatorics · Mathematics 2007-05-23 Joshua Cooper

This paper considers the problem of detecting nonstationary phenomena, and chirps in particular, from very noisy data. Chirps are waveforms of the very general form A(t) exp(i\lambda \phi(t)), where \lambda is a (large) base frequency, the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Emmanuel J. Candes , Philip R. Charlton , Hannes Helgason

Fibonacci sequence, generated by summing the preceding two terms, is a classical sequence renowned for its elegant properties. In this paper, leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of…

Combinatorics · Mathematics 2026-04-28 Zixian Yang , Jianchao Bai

Problems in exponential asymptotics are typically characterized by divergence of the associated asymptotic expansion in the form of a factorial divided by a power. In this paper, we demonstrate that in certain classes of problems that…

Classical Analysis and ODEs · Mathematics 2015-06-19 Philippe H. Trinh , S. Jonathan Chapman

For uncertainty propagation of highly complex and/or nonlinear problems, one must resort to sample-based non-intrusive approaches [1]. In such cases, minimizing the number of function evaluations required to evaluate the response surface is…

Numerical Analysis · Mathematics 2017-12-04 Anindya Bhaduri , Lori Graham-Brady
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