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We prove a rough It\^o formula for path-dependent functionals of $\alpha$-H\"older continuous paths for $\alpha\in(0,1)$. Our approach combines the sewing lemma and a Taylor approximation in terms of path-dependent derivatives.

Probability · Mathematics 2025-07-14 Franziska Bielert

We construct an explicit one-to-one correspondence between non-relativistic stochastic processes and solutions of the Schrodinger equation and between relativistic stochastic processes and solutions of the Klein-Gordon equation. The…

Quantum Physics · Physics 2023-06-21 Folkert Kuipers

Inspired by recent advances in singular SPDE theory, we use the Poincar\'e inequality on Wiener space to show that controlled complementary Young regularity is sufficient to obtain Gaussian rough paths lifts. This allows us to completely…

Probability · Mathematics 2024-12-09 Paul Gassiat , Tom Klose

We propose a modification of the Faddeev-Popov procedure to construct a path integral representation for the transition amplitude and the partition function for gauge theories whose orbit space has a non-Euclidean geometry. Our approach is…

High Energy Physics - Theory · Physics 2009-10-31 Sergei V. Shabanov , John R. Klauder

Motivated by applications in trajectory inference and particle tracking, we introduce Smooth Schr\"odinger Bridges. Our proposal generalizes prior work by allowing the reference process in the Schr\"odinger Bridge problem to be a smooth…

Machine Learning · Statistics 2025-03-04 Wanli Hong , Yuliang Shi , Jonathan Niles-Weed

We investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial…

Numerical Analysis · Mathematics 2022-01-05 Erika Hausenblas , Mihály Kovács

In this paper, we study different scaling rough path limit regimes in space and time for the Langevin dynamics on a quasi-planar fluctuating Helfrich surfaces. The convergence results of the processes were already proven in the work by…

Probability · Mathematics 2022-07-14 Ana Djurdjevac , Helena Kremp , Nicolas Perkowski

This paper is dedicated to studying pointwise estimates of the fundamental solution for the higher order Schr\"{o}dinger equation: % we investigate the fundamental solution of the higher order Schr\"{o}dinger equation…

Analysis of PDEs · Mathematics 2025-01-07 Xinyi Chen , Han Cheng , Shanlin Huang

In this paper the problem of recovering a regularized solution of the Fredholm integral equations of the first kind with Hermitian and square-integrable kernels, and with data corrupted by additive noise, is considered. Instead of using a…

Classical Analysis and ODEs · Mathematics 2007-05-23 Enrico De Micheli , Nicodemo Magnoli , Giovanni Alberto Viano

We present new higher-order quadratures for a family of boundary integral operators re-derived using the approach introduced in [Kublik, Tanushev, and Tsai - J. Comp. Phys. 247: 279-311, 2013]. In this formulation, a boundary integral over…

Numerical Analysis · Mathematics 2022-04-04 Federico Izzo , Olof Runborg , Richard Tsai

Interfacial Stokes flow can be efficiently computed using the Boundary Integral Equation method. In 3D, the fluid velocity at a target point is given by a 2D surface integral over all interfaces, thus reducing the dimension of the problem.…

Numerical Analysis · Mathematics 2025-04-03 Monika Nitsche , Bowei Wu , Ling Xu

We consider a simplified version of the problem of insider trading in a financial market. We approach it by means of anticipating stochastic calculus and compare the use of the Hitsuda-Skorokhod, the Ayed-Kuo, and the Russo-Vallois forward…

Probability · Mathematics 2018-09-13 Joan C. Bastons , Carlos Escudero

We study the existence and uniqueness of solutions to stochastic differential equations with Volterra processes driven by L\'evy noise. For this purpose, we study in detail smoothness properties of these processes. Special attention is…

Probability · Mathematics 2020-08-26 Giulia Di Nunno , Yuliya Mishura , Kostiantyn Ralchenko

Gaussian processes scale prohibitively with the size of the dataset. In response, many approximation methods have been developed, which inevitably introduce approximation error. This additional source of uncertainty, due to limited…

Machine Learning · Computer Science 2023-10-11 Jonathan Wenger , Geoff Pleiss , Marvin Pförtner , Philipp Hennig , John P. Cunningham

The article is devoted to the expansion of iterated Stratonovich stochastic integrals of second multiplicity into the double series of products of standard Gaussian random variables. The proof of expansion is based on the application of…

Probability · Mathematics 2026-02-18 Dmitriy F. Kuznetsov

A new algorithm for the approximation and simulation of twofold iterated stochastic integrals together with the corresponding L\'{e}vy areas driven by a multidimensional Brownian motion is proposed. The algorithm is based on a truncated…

Probability · Mathematics 2021-01-26 Jan Mrongowius , Andreas Rößler

We consider a simplified version of the problem of insider trading in a financial market. We approach it by means of anticipating stochastic calculus and compare the use of the Skorokhod and the Russo-Vallois forward integrals within this…

Probability · Mathematics 2018-04-20 Carlos Escudero

An elementary construction of the Wiener process is discussed, based on a proper sequence of simple symmetric random walks that uniformly converge on bounded intervals, with probability 1. This method is a simplification of F.B. Knight's…

Probability · Mathematics 2010-08-10 Tamas Szabados

We derive a nonlinear integral equation to calculate Root's solution of the Skorokhod embedding problem for atom-free target measures. We then use this to efficiently generate bounded time-space increments of Brownian motion and give a…

Probability · Mathematics 2016-08-11 Paul Gassiat , Aleksandar Mijatović , Harald Oberhauser

We solve the $n$-marginal Skorokhod embedding problem for a continuous local martingale and a sequence of probability measures $\mu_1,...,\mu_n$ which are in convex order and satisfy an additional technical assumption. Our construction is…

Probability · Mathematics 2014-01-07 Jan Obłój , Peter Spoida
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