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Related papers: New Algorithm for Mixmaster Dynamics

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We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian inference in high-dimensional settings. Specifically, we…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-06 Davide Piras , Alicja Polanska , Alessio Spurio Mancini , Matthew A. Price , Jason D. McEwen

We develop a relativistic framework to investigate the evolution of cosmological structures from the initial density perturbations to the highly nonlinear regime. Our approach involves proposing a procedure to match ``best-fit", exact…

General Relativity and Quantum Cosmology · Physics 2024-04-29 Przemyslaw Malkiewicz , Jan J. Ostrowski , Ismael Delgado Gaspar

We introduce a novel, fast, and efficient generative model built upon scattering covariances, the most recent iteration of the scattering transforms statistics. This model is designed to augment by several orders of magnitude the number of…

Cosmology and Nongalactic Astrophysics · Physics 2025-08-13 P. Campeti , J. -M. Delouis , L. Pagano , E. Allys , M. Lattanzi , M. Gerbino

This survey is devoted to the asymptotic behavior of solutions of evolution equations generated by maximal monotone operators in Hilbert spaces. The emphasis is in the comparison of the continuous time trajectories to sequences generated by…

Optimization and Control · Mathematics 2009-05-11 Juan Peypouquet , Sylvain Sorin

We present a new method for developing time step controllers based on a technique from the field of machine learning. This method is applicable to stable time integrators that have an embedded scheme, i.e., that have local error estimation…

Numerical Analysis · Mathematics 2025-12-23 Thomas Izgin , Hendrik Ranocha

This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The algorithm is derived via a low-variance…

Machine Learning · Computer Science 2013-11-04 Trevor Campbell , Miao Liu , Brian Kulis , Jonathan P. How , Lawrence Carin

Modern N-body techniques for planetary dynamics are generally based on symplectic algorithms specially adapted to the Kepler problem. These methods have proven very useful in studying planet formation, but typically require the timestep for…

Astrophysics · Physics 2009-11-13 D. S. McNeil , R. P. Nelson

A recently developed method for the calculation of Lyapunov exponents of dynamical systems is described. The method is applicable whenever the linearized dynamics is Hamiltonian. By utilizing the exponential representation of symplectic…

acc-phys · Physics 2008-02-03 Salman Habib , Robert D. Ryne

We show how to apply the absorbing Markov chain Monte Carlo algorithm of Novotny to simulate kinetically constrained models of glasses. We consider in detail one-spin facilitated models, such as the East model and its generalizations to…

Statistical Mechanics · Physics 2009-11-11 Douglas J. Ashton , Lester O. Hedges , Juan P. Garrahan

This article introduces novel and practicable Bayesian factor analysis frameworks that are computationally feasible for moderate to large spatiotemporal data. Previous Bayesian analysis of spatiotemporal data has utilized a Bayesian factor…

Methodology · Statistics 2025-02-18 Yifan Cheng , Cheng Li

Bianchi type I and type IX ('Mixmaster') geometries are investigated within the framework of Ho\v{r}ava-Witten cosmology. We consider the models for which the fifth coordinate is a $S^1/Z_2$ orbifold while the four coordinates are such that…

High Energy Physics - Theory · Physics 2009-10-31 Mariusz P. Dabrowski

Prior work on computable defect-based local error estimators for (linear) time-reversible integrators is extended to nonlinear and nonautonomous evolution equations. We prove that the asymptotic results from the linear case [W. Auzinger and…

Numerical Analysis · Mathematics 2019-01-03 Winfried Auzinger , Harald Hofstätter , Othmar Koch

In this paper we study asymptotic properties of different data-augmentation-type Markov chain Monte Carlo algorithms sampling from mixture models comprising discrete as well as continuous random variables. Of particular interest to us is…

Computation · Statistics 2014-04-04 Randal Douc , Florian Maire , Jimmy Olsson

We present a quantum version of the vacuum Bianchi IX model by implementing affine coherent state quantization combined with a Born-Oppenheimer-like adiabatic approximation. The analytical treatment is carried out on both quantum and…

General Relativity and Quantum Cosmology · Physics 2015-09-16 Hervé Bergeron , Ewa Czuchry , Jean Pierre Gazeau , Przemysław Małkiewicz , Włodzimierz Piechocki

We analyze the Bianchi IX Universe in the Polymer Quantum Mechanics framework by facing both semiclassical and purely quantum effects near the cosmological singularity. We adopt Misner variables to describe the model dynamics, applying the…

General Relativity and Quantum Cosmology · Physics 2019-12-03 Eleonora Giovannetti , Giovanni Montani

Monte Carlo simulation using a combination of Wang Landau (WL) and Transition Matrix (TM) Monte Carlo algorithms to simulate two lattice spin models with continuous energy is described. One of the models, the one dimensional Lebwohl-Lasher…

Statistical Mechanics · Physics 2009-11-13 Shyamal Bhar , Soumen Kumar Roy

A novel MIMO homogeneous Super-Twisting Algorithm is proposed in this paper for nonlinear systems with relative degree one, having a time and state-varying uncertain control matrix. The uncertainty is represented by a constant but unknown…

Systems and Control · Electrical Eng. & Systems 2022-08-09 Juan F. Garcia-Mathey , Jaime A. Moreno

An approach to quantum cosmology, relying on strengths of both canonical and path integral formalisms, is applied to the cosmological model, Bianchi type IX. Physical quantum states are constructed on the maximal slice of the cosmological…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Seth Major , Lee Smolin

In this paper, we consider the data-driven discovery of stable dynamical models with a single equilibrium. The proposed approach uses a basis-function parameterization of the differential equations and the associated Lyapunov function. This…

Systems and Control · Electrical Eng. & Systems 2026-04-10 Zhe Li , Ilias Mitrai

In this paper, an asymptotic stability proof for a class of methods for inexact nonlinear model predictive control is presented. General Q-linearly convergent online optimization methods are considered and an asymptotic stability result is…

Optimization and Control · Mathematics 2021-12-01 Andrea Zanelli , Quoc Tran Dinh , Moritz Diehl
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