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Nonlinear systems and interaction forces are pervasive in many scientific fields, such as nanoscale metrology and materials science, but their accurate identification is challenging due to their complex behaviour and inaccessibility of…

Systems and Control · Electrical Eng. & Systems 2023-06-05 Eyal Baruch , Izhak Bucher

This paper presents an online algorithm for identification of partial differential equations (PDEs) based on the weak-form sparse identification of nonlinear dynamics algorithm (WSINDy). The algorithm is online in a sense that if performs…

Optimization and Control · Mathematics 2022-03-09 Daniel A. Messenger , Emiliano Dall'Anese , David M. Bortz

The sparse identification of nonlinear dynamics (SINDy) is a regression framework for the discovery of parsimonious dynamic models and governing equations from time-series data. As with all system identification methods, noisy measurements…

Signal Processing · Electrical Eng. & Systems 2020-10-01 Kadierdan Kaheman , Steven L. Brunton , J. Nathan Kutz

Low-order nonlinear phase gates allow the construction of versatile higher-order nonlinearities for bosonic systems and grant access to continuous variable quantum simulations of many unexplored aspects of nonlinear quantum dynamics. The…

Quantum Physics · Physics 2025-10-15 Darren W. Moore , Radim Filip

High-fidelity wall-resolved large-eddy simulations (LES) are utilized to investigate the flow-physics of small-amplitude pitch oscillations of an airfoil at Re = 100,000. The investigation of the unsteady phenomenon is done in the context…

We propose a novel method of resolving the optimal anisotropy function. The idea is to construct the optimal anisotropy function as a solution to the inverse Wulff problem, i.e. as a minimizer for the anisoperimetric ratio for a given…

Optimization and Control · Mathematics 2014-03-19 Daniel Sevcovic , Maria Trnovska

The quantitative formulation of evolution equations is the backbone for prediction, control, and understanding of dynamical systems across diverse scientific fields. Besides deriving differential equations for dynamical systems based on…

Data Analysis, Statistics and Probability · Physics 2025-01-06 Tim W. Kroll , Oliver Kamps

We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic…

Reconstruction of unsteady vortical flow fields from limited sensor measurements is challenging. We develop machine learning methods to reconstruct flow features from sparse sensor measurements during transient vortex-airfoil wake…

Fluid Dynamics · Physics 2023-06-21 Yonghong Zhong , Kai Fukami , Byungjin An , Kunihiko Taira

In many compressive sensing problems today, the relationship between the measurements and the unknowns could be nonlinear. Traditional treatment of such nonlinear relationships have been to approximate the nonlinearity via a linear model…

Information Theory · Computer Science 2013-02-12 Henrik Ohlsson , Allen Y. Yang , Roy Dong , Michel Verhaegen , S. Shankar Sastry

Non-Gaussian correlations in a pure state are inextricably linked with non-classical features, such as a non positive-definite Wigner function. In a commonly used simulation technique in ultracold atoms and quantum optics, known as the…

Quantum Physics · Physics 2015-03-05 J. F. Corney , M. K. Olsen

We present a perturbation theory by extending a prescription due to Feynman for computing the probability density function for the random flight motion. The method can be applied to a wide variety of otherwise difficult circumstances. The…

Classical Physics · Physics 2007-05-23 S. Tim Hatamian

We consider systems characterized by the presence of a rapidly oscillating force. A general method is presented for the construction of the effective action governing the large-scale nonlinear dynamics of such systems order by order in…

Chaotic Dynamics · Physics 2026-05-29 Afshin Besharat , Alexander A. Penin

We introduce an adaptive method with formal quality guarantees for weak supervision in a non-stationary setting. Our goal is to infer the unknown labels of a sequence of data by using weak supervision sources that provide independent noisy…

Machine Learning · Computer Science 2025-05-05 Alessio Mazzetto , Reza Esfandiarpoor , Akash Singirikonda , Eli Upfal , Stephen H. Bach

Discovering governing equations from observational data remains a fundamental challenge in scientific modeling, particularly when the underlying mathematical structure is unknown. Traditional sparse identification methods like SINDy excel…

Machine Learning · Computer Science 2026-05-12 Mohammad Amin Basiri , Charles Nicholson

The paper presents a stochastic approach to estimate the aerodynamic forces with local dynamics on wind turbine blades in unsteady wind inflow. This is done by integrating a stochastic model of lift and drag dynamics for an airfoil into the…

Fluid Dynamics · Physics 2015-06-12 Muhammad Ramzan Luhur , Joachim Peinke , Martin Kühn , Matthias Wächter

In the present paper we consider the problem of Laplace deconvolution with noisy discrete non-equally spaced observations on a finite time interval. We propose a new method for Laplace deconvolution which is based on expansions of the…

Methodology · Statistics 2015-03-17 Fabienne Comte , Charles-A. Cuenod , Marianna Pensky , Yves Rozenholc

The nonlinear space-fractional problems often allow multiple stationary solutions, which can be much more complicated than the corresponding integer-order problems. In this paper, we systematically compute the solution landscapes of…

Numerical Analysis · Mathematics 2022-08-31 Bing Yu , Lei Zhang , Pingwen Zhang , Xiangcheng Zheng

Integral representations are considered of solutions of the inhomogeneous Airy differential equation $w''-z w=\pm1/\pi$. The solutions of these equations are also known as Scorer functions. Certain functional relations for these functions…

Numerical Analysis · Mathematics 2025-10-20 Amparo Gil , Javier Segura , Nico M. Temme

Accurately modeling the nonlinear dynamics of a system from measurement data is a challenging yet vital topic. The sparse identification of nonlinear dynamics (SINDy) algorithm is one approach to discover dynamical systems models from data.…

Machine Learning · Computer Science 2021-04-28 Kadierdan Kaheman , J. Nathan Kutz , Steven L. Brunton
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