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Discrete distributions, particularly in high-dimensional deep models, are often highly multimodal due to inherent discontinuities. While gradient-based discrete sampling has proven effective, it is susceptible to becoming trapped in local…

Machine Learning · Computer Science 2024-10-28 Patrick Pynadath , Riddhiman Bhattacharya , Arun Hariharan , Ruqi Zhang

We propose a new scheme for the long time approximation of a diffusion when the drift vector field is not globally Lipschitz. Under this assumption, regular explicit Euler scheme --with constant or decreasing step-- may explode and implicit…

Probability · Mathematics 2018-02-20 Vincent Lemaire

A continuous-time dynamical system with parameter $\varepsilon$ is nearly-periodic if all its trajectories are periodic with nowhere-vanishing angular frequency as $\varepsilon$ approaches 0. Nearly-periodic maps are discrete-time analogues…

Machine Learning · Computer Science 2023-05-11 Valentin Duruisseaux , Joshua W. Burby , Qi Tang

We show equivalence of pure point diffraction and pure point dynamical spectrum for measurable dynamical systems build from locally finite measures on locally compact Abelian groups. This generalizes all earlier results of this type. Our…

Mathematical Physics · Physics 2020-04-02 Daniel Lenz , Nicolae Strungaru

The state of an open quantum system undergoing an adiabatic process evolves by following the instantaneous stationary state of its time-dependent generator. This observation allows one to characterize, for a generic adiabatic evolution, the…

Statistical Mechanics · Physics 2024-01-23 Paulo J. Paulino , Igor Lesanovsky , Federico Carollo

This article develops variational integrators for a class of underactuated mechanical systems using the theory of discrete mechanics. Further, a discrete optimal control problem is formulated for the considered class of systems and…

Systems and Control · Computer Science 2018-11-16 Siddharth H. Nair , Ravi N. Banavar

A novel first-order autoregressive moving average model for analyzing discrete-time series observed at irregularly spaced times is introduced. Under Gaussianity, it is established that the model is strictly stationary and ergodic. In the…

Methodology · Statistics 2022-03-31 Cesar Ojeda , Wilfredo Palma , Susana Eyheramendy , Felipe Elorrieta

We present a generalized version of the discretization-invariant neural operator and prove that the network is a universal approximation in the operator sense. Moreover, by incorporating additional terms in the architecture, we establish a…

Numerical Analysis · Mathematics 2023-07-20 Zecheng Zhang , Wing Tat Leung , Hayden Schaeffer

A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative…

Optimization and Control · Mathematics 2019-03-15 Melike Sirlanci , Susan E. Luczak , I. Gary Rosen

We study close-packed dimers on the quasiperiodic Ammann-Beenker (AB) graph, that was recently shown to have the unusual feature that hard-core dimer constraints are exactly reproduced at successive discrete length scales. This observation…

Statistical Mechanics · Physics 2023-02-17 Sounak Biswas , S. A. Parameswaran

The averaging method is a classical powerful tool in perturbation theory of dynamical systems. There are two major obstacles to applying the averaging method, resonances and separatrices. In this paper we obtain realistic asymptotic…

Dynamical Systems · Mathematics 2022-02-14 Anatoly Neishtadt , Alexey Okunev

This paper focuses on the invariance control problem for discrete-time switched nonlinear systems. The proposed approach computes controlled invariant sets in a finite number of iterations and directly yields a partition-based invariance…

Optimization and Control · Mathematics 2016-09-01 Yinan Li , Jun Liu

The application of adiabatic protocols in quantum technologies is severely limited by environmental sources of noise and decoherence. Shortcuts to adiabaticity by counterdiabatic driving constitute a powerful alternative that speed up…

Quantum Physics · Physics 2019-07-12 Shuoming An , Dingshun Lv , Adolfo del Campo , Kihwan Kim

In multi-level systems, the commonly used adiabatic elimination is a method for approximating the dynamics of the system by eliminating irrelevant, non-resonantly coupled levels. This procedure is, however, somewhat ambiguous and it is not…

Quantum Physics · Physics 2014-05-23 Vanessa Paulisch , Rui Han , Hui Khoon Ng , Berthold-Georg Englert

Random walk has wide applications in many fields, such as machine learning, biology, physics, and chemistry. Random walk can be discrete or continuous in time and space. Asymmetric random walk could be described by drift-diffusion equation.…

Statistical Mechanics · Physics 2024-03-01 Guoxing Lin , Shaokun Zheng

We generalise the celebrated semiclassical wavepacket approach from the adiabatic to the non-adiabatic regime. A unified description covering both of these regimes is particularly desired for systems with spatially varying band structures…

Mesoscale and Nanoscale Physics · Physics 2020-07-29 Matisse Wei-Yuan Tu , Ci Li , Wang Yao

In this paper, we present methods of obtaining single moments of order statistics arising from posibly dependent and non-identically distributed discrete random variables. We derive exact and approximate formulas convenient for numerical…

Probability · Mathematics 2019-11-28 Anna Dembińska , Agnieszka Goroncy

Motivated by recent problems in mathematical cosmology, in which temporal averaging methods are applied in order to analyze the future asymptotics of models which exhibit oscillatory behavior, we provide a theorem concerning the large-time…

Dynamical Systems · Mathematics 2021-03-03 David Fajman , Gernot Heißel , Jin Woo Jang

Flatness of discrete-time systems can be characterized by two simple properties. There exists a map, a submersion, from the flat coordinates and their forward shifts to the state and the input of the discrete-time system, such that the…

Differential Geometry · Mathematics 2023-03-10 Schlacher Kurt , Lindorfer Martin

In this paper, we provide sufficient conditions for dissipativity and local asymptotic stability of discrete-time dynamical systems parametrized by deep neural networks. We leverage the representation of neural networks as pointwise affine…

Machine Learning · Computer Science 2022-06-09 Jan Drgona , Soumya Vasisht , Aaron Tuor , Draguna Vrabie