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We investigate the random variable defined by the volume of the zero set of a smooth Gaussian field, on a general Riemannian manifold possibly with boundary, a fundamental object in probability and geometry. We prove a new explicit formula…

Probability · Mathematics 2025-07-11 Michele Stecconi , Anna Paola Todino

We propose a generalization of nonlinear stability of numerical one-step integrators to Riemannian manifolds in the spirit of Butcher's notion of B-stability. Taking inspiration from Simpson-Porco and Bullo, we introduce non-expansive…

Numerical Analysis · Mathematics 2024-02-09 Martin Arnold , Elena Celledoni , Ergys Çokaj , Brynjulf Owren , Denise Tumiotto

In order to solve Prandtl-type equations we propose a collocation-quadrature method based on VP filtered interpolation at Chebyshev nodes. Uniform convergence and stability are proved in a couple of Holder - Zygmund spaces of locally…

Numerical Analysis · Mathematics 2020-09-04 Maria Carmela De Bonis , Donatella Occorsio , Woula Themistoclakis

Formulating a statistical inverse problem as one of inference in a Bayesian model has great appeal, notably for what this brings in terms of coherence, the interpretability of regularisation penalties, the integration of all uncertainties,…

Statistics Theory · Mathematics 2012-12-19 Natalia A. Bochkina , Peter J. Green

We establish effective versions of Oppenheim's conjecture for generic inhomogeneous quadratic forms. We prove such results for fixed shift vectors and generic quadratic forms. When the shift is rational we prove a counting result which…

Number Theory · Mathematics 2020-08-18 Anish Ghosh , Dubi Kelmer , Shucheng Yu

We investigate the relevance of the conformal method by investigating stability issues for the Einstein-Lichnerowicz conformal constraint system in a nonlinear scalar-field setting. We prove the stability of the system with respect to…

Analysis of PDEs · Mathematics 2015-02-17 Bruno Premoselli

This work focuses on quantum reservoir computing and, in particular, on quantum Wiener architectures (qWiener), consisting of quantum linear dynamic networks with weak continuous measurements and classical nonlinear static readouts. We…

Quantum Physics · Physics 2026-01-09 Alessio Benavoli , Felix Binder

We consider convolution integral equations on a finite interval with a real-valued kernel of even parity, a problem equivalent to finding a Wiener-Hopf factorisation of a notoriously difficult class of $2\times 2$ matrices. The kernel…

Spectral Theory · Mathematics 2021-06-09 Dmitry Ponomarev

The paper investigates uniform convergence of wavelet expansions of Gaussian random processes. The convergence is obtained under simple general conditions on processes and wavelets which can be easily verified. Applications of the developed…

Probability · Mathematics 2013-07-29 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

In this paper, we analyze the properties of invertible neural networks, which provide a way of solving inverse problems. Our main focus lies on investigating and controlling the Lipschitz constants of the corresponding inverse networks.…

Machine Learning · Computer Science 2021-09-01 Paul Hagemann , Sebastian Neumayer

We report surprising steady oscillations in aggregation-fragmentation processes. Oscillating solutions are observed for the class of aggregation kernels $K_{i,j} = i^{\nu}j^{\mu} + j^{\nu}i^{\mu}$ homogeneous in masses $i$ and $j$ of…

Statistical Mechanics · Physics 2023-07-18 N. V. Brilliantov , W. Otieno , S. A. Matveev , A. P. Smirnov , E. E. Tyrtyshnikov , P. L. Krapivsky

We show convexity of solutions to a class of convex variational problems in the Gauss and in the Wiener space. An important tool in the proof is a representation formula for integral functionals in this infinite dimensional setting, that…

Analysis of PDEs · Mathematics 2012-05-29 Antonin Chambolle , Michael Goldman , Matteo Novaga

The positive definiteness of real quadratic forms with convolution structures plays an important role in stability analysis for time-stepping schemes for nonlocal operators.In this work, we present a novel analysis tool to handle discrete…

Numerical Analysis · Mathematics 2023-11-23 Hong-lin Liao , Tao Tang , Tao Zhou

We consider a problem of replication of random vectors by ordinary integrals in the setting when a underlying random variable is generated by a Wiener process. The goal is to find an optimal adapted process such that its cumulative integral…

Optimization and Control · Mathematics 2012-08-09 Nikolai Dokuchaev

We continue the study of the rich family of norm-closed, automorphism invariant ideals of a continuous nest algebra. First we present a unified framework which captures all stable ideals as the kernels of limits of diagonal compressions. We…

Operator Algebras · Mathematics 2014-01-08 John Lindsay Orr

We prove the following extension of the Wiener--Wintner Theorem in Ergodic Theor and the Carleson Theorem on pointwise convergence of Fourier series: For all measure preserving flows $ (X,\mu , T_t)$ and $ f\in L^p (X,\mu)$, there is a set…

Classical Analysis and ODEs · Mathematics 2007-05-23 Michael Lacey , Erin Terwilleger

The velocity of a passive particle in a one-dimensional wave field is shown to converge in law to a Wiener process, in the limit of a dense wave spectrum with independent complex amplitudes, where the random phases distribution is invariant…

Mathematical Physics · Physics 2012-07-12 Yves Elskens

Sufficient conditions for existence and uniqueness of the solution of the Volterra integral equations of the first kind with piecewise continuous kernels are derived in framework of Sobolev-Schwartz distribution theory. The asymptotic…

Mathematical Physics · Physics 2012-04-26 Denis Sidorov

We derive a generalised It\=o formula for stochastic processes which are constructed by a convolution of a deterministic kernel with a centred L\'evy process. This formula has a unifying character in the sense that it contains the classical…

Probability · Mathematics 2015-03-03 Christian Bender , Robert Knobloch , Philip Oberacker

This paper provides a general framework for Stein's density method for multivariate continuous distributions. The approach associates to any probability density function a canonical operator and Stein class, as well as an infinite…

Probability · Mathematics 2023-04-27 Guillaume Mijoule , Martin Raič , Gesine Reinert , Yvik Swan
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