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Learning a Markov Decision Process (MDP) from a fixed batch of trajectories is a non-trivial task whose outcome's quality depends on both the amount and the diversity of the sampled regions of the state-action space. Yet, many MDPs are…

Machine Learning · Computer Science 2022-03-08 Giorgio Angelotti , Nicolas Drougard , Caroline P. C. Chanel

We present a new algorithm which is named the Dynamical Functional Particle Method, DFPM. It is based on the idea of formulating a finite dimensional damped dynamical system whose stationary points are the solution to the original…

Numerical Analysis · Mathematics 2013-03-25 Mårten Gulliksson , Sverker Edvardsson , Andreas Lind

We exploit the rich algebraic structure of the interacting boson model to explain the notion of partial dynamical symmetry (PDS), and present a procedure for constructing Hamiltonians with this property. We demonstrate the relevance of PDS…

Nuclear Theory · Physics 2013-04-16 A. Leviatan

The quantization of systems with a position dependent mass (PDM) is studied. We present a method that starts with the study of the existence of Killing vector fields for the PDM geodesic motion (Lagrangian with a PDM kinetic term but…

Mathematical Physics · Physics 2017-11-22 José F. Cariñena , Manuel F. Rañada , Mariano Santander

A methodology for deriving dual variational principles for the classical Newtonian mechanics of mass points in the presence of applied forces, interaction forces, and constraints, all with a general dependence on particle velocities and…

Mathematical Physics · Physics 2024-07-02 Amit Acharya , Ambar N. Sengupta

We introduce new machine-learning techniques for analyzing chaotic dynamical systems. The primary objectives of the study include the development of a new and simple method for calculating the Lyapunov exponent using only two trajectory…

Chaotic Dynamics · Physics 2024-08-06 Lazare Osmanov

In this work, we introduce a machine/deep learning methodology to solve parametric integrals. Besides classical machine learning approaches, we consider a differential learning framework that incorporates derivative information during…

Machine Learning · Computer Science 2025-12-15 Álvaro Leitao , Jonatan Ráfales

We investigate the problem of numerical differentiation of bivariate functions from weighted Wiener classes using Chebyshev polynomial expansions. We develop and analyze a new version of the truncation method based on Chebyshev polynomials…

Numerical Analysis · Mathematics 2026-02-02 Maksym Kyselov , Sergiy G. Solodky

We present a new automated method for finding integrable symplectic maps of the plane. These dynamical systems possess a hidden symmetry associated with an existence of conserved quantities, i.e. integrals of motion. The core idea of the…

Exactly Solvable and Integrable Systems · Physics 2025-10-21 Timofey Zolkin , Yaroslav Kharkov , Sergei Nagaitsev

We consider a generalisation of Ulam's method for approximating invariant densities of one-dimensional chaotic maps. Rather than use piecewise constant polynomials to approximate the density, we use polynomials of degree n which are defined…

Numerical Analysis · Mathematics 2011-11-28 Philip J. Aston , Oliver Junge

In this work we investigate dynamical systems designed to approach the solution sets of inclusion problems involving the sum of two maximally monotone operators. Our aim is to design methods which guarantee strong convergence of…

Optimization and Control · Mathematics 2020-08-31 Radu Ioan Boţ , Sorin-Mihai Grad , Dennis Meier , Mathias Staudigl

We consider super Yang-Mills theory on supermanifolds $\mathcal{M}^{(D|m)}$ using integral forms. The latter are used to define a geometric theory of integration and are essential for a consistent action principle. The construction relies…

High Energy Physics - Theory · Physics 2017-11-01 Pietro Fré , Pietro Antonio Grassi

A new systematic method is developed to study to what extent the symmetry requirements alone, above all the invariance under 16 supersymmetries (SUSY), determine the completely off-shell effective action $\Gamma$ of a D-particle, i.e.…

High Energy Physics - Theory · Physics 2011-07-19 Y. Kazama , T. Muramatsu

In this paper the numerical approximation of solutions of Liouville-Master Equations for time-dependent distribution functions of Piecewise Deterministic Processes with memory is considered. These equations are linear hyperbolic PDEs with…

Numerical Analysis · Mathematics 2007-05-23 Mario Annunziato

This paper presents a novel method to synthesize stochastic control Lyapunov functions for a class of nonlinear, stochastic control systems. In this work, the classical nonlinear Hamilton-Jacobi-Bellman partial differential equation is…

Optimization and Control · Mathematics 2016-11-17 Yoke Peng Leong , Matanya B. Horowitz , Joel W. Burdick

"Sticky" motion in mixed phase space of conservative systems is difficult to detect and to characterize, in particular for high dimensional phase spaces. Its effect on quasi-regular motion is quantified here with four different measures,…

Chaotic Dynamics · Physics 2010-10-13 C. Manchein , M. W. Beims , J. M. Rost

The position-based dynamics (PBD) algorithm is a popular and versatile technique for real-time simulation of deformable bodies, but is only applicable to forces that can be expressed as linearly compliant constraints. In this work, we…

Graphics · Computer Science 2025-12-01 Manas Chaudhary , Chandradeep Pokhariya , Rahul Narain

In this paper, we address stability of parabolic linear Partial Differential Equations (PDEs). We consider PDEs with two spatial variables and spatially dependent polynomial coefficients. We parameterize a class of Lyapunov functionals and…

Optimization and Control · Mathematics 2015-09-15 Evgeny Meyer , Matthew M. Peet

We consider superintegrability in classical mechanics in the presence of magnetic fields. We focus on three-dimensional systems which are separable in Cartesian coordinates. We construct all possible minimally and maximally superintegrable…

Mathematical Physics · Physics 2020-03-13 Antonella Marchesiello , Libor Šnobl

Using the well known position-dependent mass (PDM) von Roos Hamiltonian, Dutra and Oliveira (2009 J. Phys. A: Math. Theor. 42 025304) have studied the problem of two-dimensional PDM particles in the presence of magnetic fields. They have…

Quantum Physics · Physics 2019-03-28 Omar Mustafa