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Bayesian optimization is a sequential method for minimizing objective functions that are expensive to evaluate and about which few assumptions can be made. By using all gathered data to train a Gaussian process model for the function and…

Machine Learning · Computer Science 2026-05-07 Jesse Schneider , William J. Welch

Complications arising from the non-compact nature of the phase space of N-body systems prevent any asymptotic characterization of chaotic behaviour (since no equilibrium final states can exist). This leads us to revisit some of the old…

Astrophysics · Physics 2007-05-23 A. A. El-Zant

We consider nearly-integrable Hamiltonian systems defined over a non-resonant domain. In the neighborhood of resonances, we use Nekhoroshev-like estimates to provide effective stability bounds for the action variables over long time. The…

Dynamical Systems · Mathematics 2026-04-08 Alessandra Celletti , Anargyros Dogkas , Alessia Francesca Guido

A common problem to all applications of linear finite dynamical systems is analyzing the dynamics without enumerating every possible state transition. Of particular interest is the long term dynamical behaviour. In this paper, we study the…

Dynamical Systems · Mathematics 2019-04-01 Björn Lindenberg

Bayesian optimization is an approach to optimizing objective functions that take a long time (minutes or hours) to evaluate. It is best-suited for optimization over continuous domains of less than 20 dimensions, and tolerates stochastic…

Machine Learning · Statistics 2018-07-10 Peter I. Frazier

Current analysis of astronomical data are confronted with the daunting task of modeling the awkward features of astronomical data, among which heteroscedastic (point-dependent) errors, intrinsic scatter, non-ignorable data collection…

Instrumentation and Methods for Astrophysics · Physics 2011-12-19 S. Andreon

We describe an algorithm for constructing N-body realisations of equilibrium stellar systems. The algorithm complements existing orbit-based modelling techniques using linear programming or other optimization algorithms. The equilibria are…

Astrophysics · Physics 2015-06-24 D. Syer , S. Tremaine

Data generated from dynamical systems with unknown dynamics enable the learning of state observers that are: robust to modeling error, computationally tractable to design, and capable of operating with guaranteed performance. In this paper,…

Systems and Control · Electrical Eng. & Systems 2021-06-28 Ankush Chakrabarty , Mouhacine Benosman

The planetary dynamics of $4/3$, $3/2$, $5/2$, $3/1$ and $4/1$ mean motion resonances is studied by using the model of the general three body problem in a rotating frame and by determining families of periodic orbits for each resonance.…

Earth and Planetary Astrophysics · Physics 2017-02-10 K. I. Antoniadou , G. Voyatzis

Modelling gravity is a fundamental problem that must be tackled in N-body simulations of stellar systems, and satisfactory solutions require a deep understanding of the dynamical effects of softening. In a previous paper (Romeo 1997), we…

Astrophysics · Physics 2007-05-23 Alessandro B. Romeo

This paper introduces new techniques for using convex optimization to fit input-output data to a class of stable nonlinear dynamical models. We present an algorithm that guarantees consistent estimates of models in this class when a small…

Optimization and Control · Mathematics 2013-03-19 Mark M. Tobenkin , Ian R. Manchester , Alexandre Megretski

This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches…

Instrumentation and Methods for Astrophysics · Physics 2012-05-10 Eric D. Feigelson , G. Jogesh Babu

In this paper, we use dynamical systems to analyze stability of desynchronization algorithms at equilibrium. We start by illustrating the equilibrium of a dynamic systems and formalizing force components and time phases. Then, we use Linear…

Networking and Internet Architecture · Computer Science 2017-04-25 Supasate Choochaisri , Kittipat Apicharttrisorn , Chalermek Intanagonwiwat

Gaussian processes are frequently deployed as part of larger machine learning and decision-making systems, for instance in geospatial modeling, Bayesian optimization, or in latent Gaussian models. Within a system, the Gaussian process model…

Many relevant problems in the area of systems and control, such as controller synthesis, observer design and model reduction, can be viewed as optimization problems involving dynamical systems: for instance, maximizing performance in the…

Optimization and Control · Mathematics 2023-11-15 Pascal Den Boef , Jos Maubach , Wil Schilders , Nathan van de Wouw

We investigate the stability regions of hypothetical terrestrial planets around the Lagrangian equilibrium points L4 and L5 in some specific extrasolar planetary systems. The problem of their stability can be treated in the framework of the…

Astrophysics · Physics 2009-11-10 R. Dvorak , E. Pilat-Lohinger , R. Schwarz , F. Freistetter

Binary and multiple star systems are extreme environments for the formation and long-term presence of extrasolar planets. Circumstellar planets are subject to gravitational perturbations from the distant companion star, and this interaction…

Earth and Planetary Astrophysics · Physics 2019-08-06 Ákos Bazsó , Elke Pilat-Lohinger

Recent work in the literature has advocated using the Earth-Moon-planetoid Lagrangian points as observables, in order to test general relativity and effective field theories of gravity in the solar system. However, since the three-body…

General Relativity and Quantum Cosmology · Physics 2017-04-26 Emmanuele Battista , Simone Dell'Agnello , Giampiero Esposito , Luciano Di Fiore , Jules Simo , Aniello Grado

We consider the motion of point masses given by a natural extension of Newtonian gravitation to spaces of constant positive curvature. Our goal is to explore the spectral stability of tetrahedral orbits of the corresponding 4-body problem…

Dynamical Systems · Mathematics 2016-03-11 Florin Diacu , Regina Martinez , Ernesto Perez-Chavela , Carles Simo

This paper presents a novel robust trajectory optimization method for constrained nonlinear dynamical systems subject to unknown bounded disturbances. In particular, we seek optimal control policies that remain robustly feasible with…

Systems and Control · Electrical Eng. & Systems 2025-04-08 Arshiya Taj Abdul , Augustinos D. Saravanos , Evangelos A. Theodorou