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We use the Wa\'zewski topological principle to establish a number of new sufficient conditions for the existence of proper (defined on the entire time axis) solutions of essentially nonlinear nonautonomous systems. The systems under…

Classical Analysis and ODEs · Mathematics 2009-01-05 Volodymyr Lagoda , Igor Parasyuk

The general relativistic non--linear dynamics of a self--gravitating collisionless fluid with vanishing vorticity is studied in synchronous and comoving -- i.e. {\em Lagrangian} -- coordinates. Writing the equations in terms of the metric…

Astrophysics · Physics 2007-05-23 Sabino Matarrese

The thesis is devoted to the phase space representation of relativistic quantum mechanics. For a class of observables with matrix-valued Weyl symbols proportional to the identity matrix, the Weyl-Wigner-Moyal formalism is proposed. The…

Quantum Physics · Physics 2007-05-23 A. A. Semenov

Latent dynamics discovery is challenging in extracting complex dynamics from high-dimensional noisy neural data. Many dimensionality reduction methods have been widely adopted to extract low-dimensional, smooth and time-evolving latent…

Machine Learning · Computer Science 2019-07-02 Qi She , Anqi Wu

The linear theory for rotating compressible convection in a plane layer geometry is presented for the astrophysically-relevant case of low Prandtl number gases. When the rotation rate of the system is large, the flow remains geostrophically…

Geophysics · Physics 2015-03-02 Michael A. Calkins , Keith Julien , Philippe Marti

Beginning with the stress-energy tensor of an elastic string this paper derives a relativistic string and its form in a parallel transported Fermi frame including its reduction in the Newtonian limit to a Cosserat string. In a Fermi frame…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Peter Bollada

Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. Classical solutions such that Kalman filter and Particle filter are introduced in this report. Gaussian processes have been introduced as…

Information Theory · Computer Science 2010-11-04 Mr. Chong Han , Dr. Ido Nevat , Dr. Gareth Peters , Prof. Jinhong Yuan

An equation of motion of the mass point with internal degrees of freedom in scalar potential $U$ depending on relative coordinates and time, velocity and accelerations is obtained both for non-relativistic and relativistic case. In…

High Energy Physics - Theory · Physics 2010-10-25 A. N. Tarakanov

By modeling the interaction of a system with an environment through a renewal approach, we demonstrate that completely positive non-Markovian dynamics may develop some unexplored non-standard statistical properties. The renewal approach is…

Quantum Physics · Physics 2009-08-07 Adrian A. Budini Paolo Grigolini

Inverse analysis, such as model calibration, often suffers from a lack of informative data in complex real-world scenarios. The standard remedy, designing new experimental setups, is often costly and time-consuming, while readily available…

Computational Engineering, Finance, and Science · Computer Science 2026-01-16 Lea J. Haeusel , Jonas Nitzler , Lea J. Köglmeier , Wolfgang A. Wall

Autonomous motion planning under unknown nonlinear dynamics presents significant challenges. An agent needs to continuously explore the system dynamics to acquire its properties, such as reachability, in order to guide system navigation…

Robotics · Computer Science 2025-03-06 Zhiquan Zhang , Gokul Puthumanaillam , Manav Vora , Melkior Ornik

This paper addresses the problem of identifying sparse linear time-invariant (LTI) systems from a single sample trajectory generated by the system dynamics. We introduce a Lasso-like estimator for the parameters of the system, taking into…

Systems and Control · Computer Science 2019-04-23 Salar Fattahi , Nikolai Matni , Somayeh Sojoudi

We analyze the dynamics of an algorithm for approximate inference with large Gaussian latent variable models in a student-teacher scenario. To model nontrivial dependencies between the latent variables, we assume random covariance matrices…

Machine Learning · Computer Science 2020-08-26 Burak Çakmak , Manfred Opper

GenASiS (General Astrophysical Simulation System) is a code being developed initially and primarily, though not exclusively, for the simulation of core-collapse supernovae on the world's leading capability supercomputers. This paper -- the…

High Energy Astrophysical Phenomena · Physics 2026-02-04 Christian Y. Cardall , Reuben D. Budiardja , R. Daniel Murphy , Eirik Endeve

We propose a principled method for projecting an arbitrary square matrix to the non-convex set of asymptotically stable matrices. Leveraging ideas from large deviations theory, we show that this projection is optimal in an…

Optimization and Control · Mathematics 2023-06-21 Wouter Jongeneel , Tobias Sutter , Daniel Kuhn

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over…

Statistical Mechanics · Physics 2009-10-31 J. C. Lemm , J. Uhlig , A. Weiguny

The non-extensive statistical mechanics has been applied to describe a variety of complex systems with inherent correlations and feedback loops. Here we present a dynamical model based on previously proposed static model exhibiting in the…

Statistical Mechanics · Physics 2016-04-20 A. Kononovicius , J. Ruseckas

Smoothness of the subdiagonals of the Cholesky factor of large covariance matrices is closely related to the degrees of nonstationarity of autoregressive models for time series and longitudinal data. Heuristically, one expects for a nearly…

Machine Learning · Statistics 2020-07-23 Aramayis Dallakyan , Mohsen Pourahmadi

We investigate evolutional paths of an extended quintessence with a non-minimally coupled phantom scalar field $\psi$ to the Ricci curvature. The dynamical system methods are used to investigate typical regimes of dynamics at the late time.…

High Energy Physics - Theory · Physics 2008-11-26 Orest Hrycyna , Marek Szydlowski

This article describes a robust algorithm to estimate a conditional probability density f(t|x) as a non-parametric smooth regression function. It is based on a neural network and the Bayesian interpretation of the network output as a…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Michael Feindt
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