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Related papers: Exact numerical simulation of power-law noises

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In a recent paper I have introduced a package for the exact simulation of power-law noises and other colored noises (E. Milotti, Comput. Phys. Commun. {\bf 175} (2006) 212): in particular the algorithm generates $1/f^\alpha$ noises with $0…

Computational Physics · Physics 2009-11-13 Edoardo Milotti

Power-law noises abound in nature and have been observed extensively in both time series and spatially varying environmental parameters. Although, recent years have seen the extension of traditional stochastic partial differential equations…

Computation · Statistics 2014-10-20 Hans-Werner van Wyk , Max Gunzburger , John Burkardt , Miroslav Stoyanov

Real-world measurement noise in applications like robotics is often correlated in time, but we typically assume i.i.d. Gaussian noise for filtering. We propose general Gaussian Processes as a non-parametric model for correlated measurement…

Machine Learning · Statistics 2019-09-25 Vince Kurtz , Hai Lin

An overdamped system with a linear restoring force and two multiplicative colored noises is considered. Noise amplitudes depend on the system state $x$ as $x$ and $|x|^{\alpha}$. An exactly soluble model of a system is constructed due to…

Statistical Mechanics · Physics 2007-05-23 A. N. Vitrenko

Stochastic averaging problems with Gaussian forcing have been studied thoroughly for many years, but far less attention has been paid to problems where the stochastic forcing has infinite variance, such as an {\alpha}-stable noise forcing.…

Dynamical Systems · Mathematics 2017-05-24 William F. Thompson , Rachel A. Kuske , Adam. H. Monahan

The ability to quantify stochastic fluctuations present in biochemical and other systems is becoming increasing important. Analytical descriptions of these fluctuations are attractive, as stochastic simulations are computationally…

Statistical Mechanics · Physics 2013-02-07 Joseph D. Challenger , Alan J. McKane , Jürgen Pahle

A linear Gaussian state-space smoothing algorithm is presented for estimation of derivatives from a sequence of noisy measurements. The algorithm uses numerically stable square-root formulas, can handle simultaneous independent measurements…

Methodology · Statistics 2016-10-17 Robert Piche

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

Quantum error correction protocols have been developed to offset the high sensitivity to noise inherent in quantum systems. However, much is still unknown about the behaviour of a quantum error-correcting code under general noise, including…

Quantum Physics · Physics 2021-06-09 Stefanie J. Beale , Joel J. Wallman

The evaluation of the path-integral representation for stochastic processes in the weak-noise limit shows that these systems are governed by a set of equations which are those of a classical dynamics. We show that, even when the noise is…

Condensed Matter · Physics 2009-10-22 S. J. B. Einchcomb , A. J. McKane

A method for simulating power law noise in clocks and oscillators is presented based on modification of the spectrum of white phase noise, then Fourier transforming to the time domain. Symmetric real matrices are introduced whose…

Data Analysis, Statistics and Probability · Physics 2011-03-28 Neil Ashby

This paper develops new analytical process noise covariance models for both absolute and relative spacecraft states. Process noise is always present when propagating a spacecraft state due to dynamics modeling deficiencies. Accurately…

Dynamical Systems · Mathematics 2022-03-02 Nathan Stacey , Simone D'Amico

Numerical algorithms for the integration of stochastic differential equations in the presence of white noise are introduced and compared. Algorithms for the integration of stochastic correlated forces are also briefly reviewed. Finally, a…

Statistical Mechanics · Physics 2008-02-03 Riccardo Mannella

We present a classical algorithm that approximately samples from the output distribution of certain noisy Boson Sampling experiments. This algorithm is inspired by a recent result of Aharonov, Gao, Landau, Liu and Vazirani and makes use of…

Quantum Physics · Physics 2023-01-30 Changhun Oh , Liang Jiang , Bill Fefferman

We introduce the concept of numerical Gaussian processes, which we define as Gaussian processes with covariance functions resulting from temporal discretization of time-dependent partial differential equations. Numerical Gaussian processes,…

Machine Learning · Statistics 2017-03-31 Maziar Raissi , Paris Perdikaris , George Em Karniadakis

To make arbitrarily accurate quantum computation possible, practical realization of quantum computers will require suppressing noise in quantum memory and gate operations to make it below a threshold value. A scheme based on realistic…

Quantum Physics · Physics 2007-05-23 Lu-Ming Duan , Guang-Can Guo

$1/f^\alpha$ noises are ubiquitous and affect many measurements. These noises are both a nuisance and a peculiarity of several physical systems; in dielectrics, glasses and networked liquids it is very common to study this noise to gather…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Edoardo Milotti

We address the use of a single qubit as a quantum probe to characterize the properties of classical noise. In particular, we focus on the characterization of classical noise arising from the interaction with a stochastic field described by…

Quantum Physics · Physics 2015-10-07 Claudia Benedetti , Matteo G. A. Paris

This chapter presents specific aspects of Gaussian process modeling in the presence of complex noise. Starting from the standard homoscedastic model, various generalizations from the literature are presented: input varying noise variance,…

Optimization and Control · Mathematics 2024-12-11 Mickael Binois , Arindam Fadikar , Abby Stevens

We provide the strong approximation of empirical copula processes by a Gaussian process. In addition we establish a strong approximation of the smoothed empirical copula processes and a law of iterated logarithm.

Statistics Theory · Mathematics 2019-03-06 Salim Bouzebda , Tarek Zari
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