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This paper introduces a meta-learning approach for parameterized pseudo-differential operators with deep neural networks. With the help of the nonstandard wavelet form, the pseudo-differential operators can be approximated in a compressed…

Numerical Analysis · Mathematics 2020-02-26 Jordi Feliu-Faba , Yuwei Fan , Lexing Ying

By using path integrals, the stochastic process associated to the time evolution of the quantum probability density is formally rewritten in terms of a stochastic differential equation, given by Newton's equation of motion with an…

Quantum Physics · Physics 2018-01-04 Marco Patriarca

Markov branching systems form a fundamental class of stochastic models that are extensively applied in biology, physics, finance, and other domains. These systems are distinguished by their continuous-time evolution and inherent branching…

Motivated by the recent paper of Boggiatto-Garello in J. Pseudo-Differ. Oper. Appl. \textbf{11} (2020), 93-117, where a Gabor operator is regarded as pseudodifferential operator with symbol $p(x,\omega)$ periodic on both the variables, we…

Analysis of PDEs · Mathematics 2023-03-13 Gianluca Garello , Alessandro Morando

Qualitative and quantitative aspects for variational inequalities governed by strongly pseudomonotone operators on Hilbert space are investigated in this paper. First, we establish a global error bound for the solution set of the given…

Optimization and Control · Mathematics 2020-10-07 Pham Tien Kha , Pham Duy Khanh

In this article we study a class of stochastic functional differential equations driven by L\'{e}vy processes (in particular, $\alpha$-stable processes), and obtain the existence and uniqueness of Markov solutions in small time intervals.…

Probability · Mathematics 2012-11-30 Xicheng Zhang

In this work, we extend Wigner's original framework to analyze linear operators by examining the relationship between their Wigner and Schwartz kernels. Our approach includes the introduction of (quasi-)algebras of Fourier integral…

Analysis of PDEs · Mathematics 2024-06-18 Elena Cordero , Gianluca Giacchi , Edoardo Pucci

In this paper, we provide a compositional methodology for constructing symbolic models for networks of discrete-time switched systems. We first define a notion of so-called augmented-storage functions to relate switched subsystems and their…

Systems and Control · Computer Science 2019-05-31 Abdalla Swikir , Majid Zamani

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second order differential equation can be analyzed this way by…

Data Analysis, Statistics and Probability · Physics 2014-12-09 Bernd Lehle , Joachim Peinke

We investigate the parameter recovery of Markov-switching ordinary differential processes from discrete observations, where the differential equations are nonlinear additive models. This framework has been widely applied in biological…

Methodology · Statistics 2025-01-03 Katherine Tsai , Mladen Kolar , Sanmi Koyejo

When analysing statistical systems or stochastic processes, it is often interesting to ask how they behave given that some observable takes some prescribed value. This conditioning problem is well understood within the linear operator…

Statistical Mechanics · Physics 2022-03-09 Lydia Chabane , Alexandre Lazarescu , Gatien Verley

We define a class of discrete operators acting on infinite, finite or periodic sequences mimicking the standard properties of pseudo-differential operators. In particular we can define the notion of order and regularity, and we recover the…

Analysis of PDEs · Mathematics 2021-10-01 Erwan Faou , Benoît Grébert

A family of orthonormal bases, the ultrametric wavelet bases, is introduced in quadratically integrable complex valued functions spaces for a wide family of ultrametric spaces. A general family of pseudodifferential operators, acting on…

Mathematical Physics · Physics 2015-06-26 A. Yu. Khrennikov , S. V. Kozyrev

Markov processes play an important role in physics and the theory of open systems in particular. In this paper we study the asymptotic evolution of trace-nonincreasing homogenous quantum Markov processes (both types, discrete quantum Markov…

Quantum Physics · Physics 2019-02-19 Jaroslav Novotný , Jirí Maryška , Igor Jex

The usual Weyl calculus is intimately associated with the choice of the standard symplectic structure on $\mathbb{R}^{n}\oplus\mathbb{R}^{n}$. In this paper we will show that the replacement of this structure by an arbitrary symplectic…

Functional Analysis · Mathematics 2012-09-11 Nuno Costa Dias , Maurice de Gosson , Franz Luef , João Nuno Prata

In this article we study the Cauchy problem for a new class of parabolic-type pseudodifferential equations with variable coefficients for which the fundamental solutions are transition density functions of Markov processes in the four…

Analysis of PDEs · Mathematics 2013-12-10 O. F. Casas-Sánchez , W. A. Zúñiga-Galindo

We study a time-non-homogeneous Markov process which arose from free probability, and which also appeared in the study of stochastic processes with linear regressions and quadratic conditional variances. Our main result is the explicit…

Probability · Mathematics 2013-09-16 Wlodek Bryc

In this paper, we study weak and strong transience of a class of Feller processes associated with pseudo-differential operators, the so-called L\'evy-type processes. As a main result, we derive Chung-Fuchs type conditions (in terms of the…

Probability · Mathematics 2016-04-14 Nikola Sandrić

In quantum statistical mechanics, Moyal's equation governs the time evolution of Wigner functions and of more general Weyl symbols that represent the density matrix of arbitrary mixed states. A formal solution to Moyal's equation is given…

Quantum Physics · Physics 2021-05-19 E. Gozzi , C. Pagani , M. Reuter

Mixed-norm $\alpha$-modulation spaces were introduced recently by Cleanthous and Georgiadis [Trans.\ Amer.\ Math.\ Soc.\ 373 (2020), no. 5, 3323-3356]. The mixed-norm spaces $M^{s,\alpha}_{\vec{p},q}(\mathbb{R}^n)$, $\alpha\in [0,1]$, form…

Functional Analysis · Mathematics 2022-03-30 Morten Nielsen