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We study stochastic equations of non-negative processes with jumps. The existence and uniqueness of strong solutions are established under Lipschitz and non-Lipschitz conditions. The comparison property of two solutions are proved under…

Probability · Mathematics 2008-02-08 Zongfei Fu , Zenghu Li

In this paper, we present a new fractal derivative with a nonsingular kernel and analyze its fundamental properties. The effectiveness of the proposed operator is illustrated through the study of economic models using both the Caputo…

General Mathematics · Mathematics 2026-02-23 Krishna Mani Nath , Bipan Hazarika , Hemanta Kalita

We study spectral-theoretic properties of non-self-adjoint operators arising in the study of one-dimensional L\'evy processes with completely monotone jumps with a one-sided barrier. With no further assumptions, we provide an integral…

Spectral Theory · Mathematics 2024-11-19 Mateusz Kwaśnicki

In this paper we establish the existence and uniqueness of heat kernels to a large class of time-inhomogenous non-symmetric nonlocal operators with Dini's continuous kernels. Moreover, quantitative estimates including two-sided estimates,…

Analysis of PDEs · Mathematics 2020-10-09 Zhen-Qing Chen , Xicheng Zhang

This short study reformulates the statistical Bayesian learning problem using a quantum mechanics framework. Density operators representing ensembles of pure states of sample wave functions are used in place probability densities. We show…

Statistics Theory · Mathematics 2023-01-18 Yann Berquin

Pure-jump L\'evy processes are popular classes of stochastic processes which have found many applications in finance, statistics or machine learning. In this paper, we propose a novel family of self-decomposable L\'evy processes where one…

Methodology · Statistics 2025-02-06 Fadhel Ayed , Juho Lee , François Caron

What is the connection of random matrices with integrable systems? Is this connection really useful? The answer to these questions leads to a new and unifying approach to the theory of random matrices. Introducing an appropriate time…

solv-int · Physics 2007-05-23 M. Adler , T. Shiota , P. van Moerbeke

We study the composition of bivariate L\'evy process with bivariate inverse subordinator. The explicit expressions for its dispersion and auto correlation matrices are obtained. Also, the time-changed two parameter L\'evy processes with…

Probability · Mathematics 2025-03-07 Pradeep Vishwakarma , Manisha Dhillon , Kuldeep Kumar Kataria

We show the existence of L\'evy-type stochastic processes in one space dimension with characteristic triplets that are either discontinuous at thresholds, or are stable-like with stability index functions for which the closures of the…

Probability · Mathematics 2012-08-09 Peter Imkeller , Niklas Willrich

In this paper, the behavior for commutators of a class of bilinear singular integral operator associated with non-smooth kernels on the products of weighted Lebesgue spaces is considered. By some new maximal functions to control the…

Classical Analysis and ODEs · Mathematics 2014-11-10 Rui Bu , Jiecheng Chen

In this article, some logistic models in the settings of Caputo fractional operators with multi-parametered Mittag-Leffer kernels (ABC) are studied. This study mainly focuses on modified quadratic and cubic logistic models in the presence…

General Mathematics · Mathematics 2019-12-19 Thabet Abdeljawad , Mohamed A. Hajji , Qasem Al-Mdallal , Fahd Jarad

L\'evy stable (jump-type) processes are examples of intrinsically nonlocal random motions. This property becomes a serious obstacle if one attempts to model conditions under which a particular L\'evy process may be subject to physically…

Mathematical Physics · Physics 2015-11-10 Piotr Garbaczewski , Mariusz Żaba

L\'evy copulas are an important tool which can be used to build dependent L\'evy processes. In a classical setting, they have been used to model financial applications. In a Bayesian framework they have been employed to introduce dependent…

Methodology · Statistics 2020-09-01 Alan Riva Palacio , Fabrizio Leisen

We investigate the capabilities of a quantum computer based on cold trapped ions in presence of non-dissipative decoherence. The latter is accounted by using the evolution time as a random variable and then averaging on a properly defined…

Quantum Physics · Physics 2009-11-06 Stefano Mancini , Rodolfo Bonifacio

Piecewise-deterministic Markov processes form a general class of non-diffusion stochastic models that involve both deterministic trajectories and random jumps at random times. In this paper, we state a new characterization of the jump rate…

Methodology · Statistics 2017-05-03 Romain Azaïs , Alexandre Genadot

In this paper, we study a class of convolution operators on the space of distributions that enlarge the well-studied class of passive operators. In this larger class, we are able to associate, to each operator, a holomorphic function in the…

Functional Analysis · Mathematics 2018-11-27 Mitja Nedic

We consider the analysis of probability distributions through their associated covariance operators from reproducing kernel Hilbert spaces. We show that the von Neumann entropy and relative entropy of these operators are intimately related…

Information Theory · Computer Science 2022-08-29 Francis Bach

We study stochastic differential equations with jumps with no diffusion part. We provide some basic stochastic characterizations of solutions of the corresponding non-local partial differential equations and prove the Harnack inequality for…

Probability · Mathematics 2015-10-06 Ari Arapostathis , Anup Biswas , Luis Caffarelli

By using Fourier's transform and Fefferman-Stein's theorem, we investigate the $L^p$-maximal regularity of nonlocal parabolic and elliptic equations with singular and non-symmetric L\'evy operators, and obtain the unique strong solvability…

Analysis of PDEs · Mathematics 2012-01-04 Xicheng Zhang

We connect shift-invariant characteristic kernels to infinitely divisible distributions on $\mathbb{R}^{d}$. Characteristic kernels play an important role in machine learning applications with their kernel means to distinguish any two…

Machine Learning · Statistics 2016-10-26 Yu Nishiyama , Kenji Fukumizu