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Stochastic differential equations (SDEs) are established tools to model physical phenomena whose dynamics are affected by random noise. By estimating parameters of an SDE intrinsic randomness of a system around its drift can be identified…

Computation · Statistics 2012-05-03 Umberto Picchini , Susanne Ditlevsen

Nonlinear Dirac equations (NLDE) are derived through a group N^2 of nonlinear (gauge) transformation acting in the corresponding state space. The construction generalises a construction for nonlinear Schr\"odinger equations. To relate N^2…

Quantum Physics · Physics 2007-05-23 H. -D. Doebner , R. Zhdanov

Simplified analytic methods are frequently used to model the light curves of supernovae and other energetic transients and to extract physical quantities, such as the ejecta mass and amount of radioactive heating. The applicability and…

High Energy Astrophysical Phenomena · Physics 2019-10-02 David K. Khatami , Daniel N. Kasen

Stochastic differential equations (SDEs) are well suited to modelling noisy and irregularly sampled time series found in finance, physics, and machine learning. Traditional approaches require costly numerical solvers to sample between…

Machine Learning · Computer Science 2025-10-30 Naoki Kiyohara , Edward Johns , Yingzhen Li

In nonlinear dynamical systems with highly nonorthogonal linear eigenvectors, linear non-modal analysis is more useful than normal mode analysis in predicting turbulent properties. However, the non-trivial time evolution of non-modal…

Plasma Physics · Physics 2015-06-22 Brett Friedman , Troy A. Carter

Motivated by upcoming photometric and spectroscopic surveys (Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Manuakea Spectroscopic Explorer), we design the statistical proxies to measure the cadence effects on active…

Gravitationally lensed quasars offer a unique opportunity to study cosmological and extragalactic phenomena, using reliable light curves of the lensed images. This requires accurate deblending of the quasar images, which is not trivial due…

Instrumentation and Methods for Astrophysics · Physics 2025-04-24 Favio Neira , Frédéric Courbin , Frédéric Dux , Georgios Vernardos

We present nonlinear dynamic equations for nematic and smectic $A$ liquid crystals in the presence of an alternating electric field and explain their derivation in detail. The local electric field acting in any liquid-crystalline system is…

Soft Condensed Matter · Physics 2023-06-30 E. S. Pikina , E. I. Kats , A. R. Muratov , V. V. Lebedev

Taking a multidimensional time-homogeneous dynamical system and adding a randomly perturbed time-dependent deterministic signal to some of its components gives rise to a high-dimensional system of stochastic differential equations which is…

Statistics Theory · Mathematics 2019-08-02 Simon Holbach

In this letter, we propose a method for period estimation in light curves from periodic variable stars using correntropy. Light curves are astronomical time series of stellar brightness over time, and are characterized as being noisy and…

Information Theory · Computer Science 2014-12-08 Pablo Huijse , Pablo A. Estévez , Pablo Zegers , José Príncipe , Pavlos Protopapas

I present an homogeneous analysis of the transit light curves of 14 well-observed transiting extrasolar planets. The light curves are modelled using JKTEBOP, random errors are measured using Monte Carlo simulations, and the effects of…

Astrophysics · Physics 2009-11-13 John Southworth

Nonlinear stochastic differential equations (NSDEs) are a pillar of mathematical modeling for scientific and engineering applications. Accurate and efficient simulation of large-scale NSDEs is prohibitive on classical computers due to the…

Quantum Physics · Physics 2026-03-16 Xiangyu Li , Ahmet Burak Catli , Ho Kiat Lim , Matthew Pocrnic , Dong An , Jin-Peng Liu , Nathan Wiebe

Anomaly subsequence detection is to detect inconsistent data, which always contains important information, among time series. Due to the high dimensionality of the time series, traditional anomaly detection often requires a large time…

Machine Learning · Computer Science 2019-07-02 Chunkai Zhang , Yingyang Chen , Ao Yin

Dynamical systems techniques are a powerful tool to analyse systems of ordinary differential equations, written in an appropriate form. For a given theory of gravity, the cosmological field equations typically lead to a system of ordinary…

General Relativity and Quantum Cosmology · Physics 2026-05-13 Christian G. Boehmer , Antonio d'Alfonso del Sordo

A general input-output modelling technique for aperiodic-sampling linear systems has been developed. The procedure describes the dynamics of the system and includes the sequence of sampling periods among the variables to be handled. Some…

Discrete Mathematics · Computer Science 2016-08-14 Amparo Fúster-Sabater , J. M. Guillén

Context. The classification of active galactic nuclei (AGNs) is a challenge in astrophysics. Variability features extracted from light curves offer a promising avenue for distinguishing AGNs and their subclasses. This approach would be very…

The evolution of images with physics-based dynamics is often spatially localized and nonlinear. A switching linear dynamic system (SLDS) is a natural model under which to pose such problems when the system's evolution randomly switches over…

Systems and Control · Electrical Eng. & Systems 2021-02-23 Parisa Karimi , Mark Butala , Zhizhen Zhao , Farzad Kamalabadi

An external description for nonperiodically sampled multivariable linear systems has been developed. Emphasis is on the sampling period sequence, included among the variables to be handled. The computational procedure is simple and no use…

Dynamical Systems · Mathematics 2010-06-08 Amparo Fúster-Sabater

Dynamic power system models are instrumental in real-time stability, monitoring, and control. Such models are traditionally posed as systems of nonlinear differential algebraic equations (DAEs): the dynamical part models generator…

Systems and Control · Electrical Eng. & Systems 2024-02-02 Mohamad H. Kazma , Ahmad F. Taha

In this paper we consider in detail the properties of dynamical heterogeneity in lattice glass models (LGMs). LGMs are lattice models whose dynamical rules are based on thermodynamic, as opposed to purely kinetic, considerations. We devise…

Statistical Mechanics · Physics 2012-10-02 Richard K. Darst , David R. Reichman , Giulio Biroli