English
Related papers

Related papers: Killing versus branching: Unexplored facets of dif…

200 papers

Relaxation to equilibrium of a drifted Brownian motion is quantified by a probability density function, whose main (multiplicative) entry is an inferred Feynman-Kac kernel of the Schr\"{o}dinger semigroup operator. Although seemingly devoid…

Statistical Mechanics · Physics 2026-05-26 Piotr Garbaczewski , Mariusz Żaba

We address diffusion processes in a bounded domain, while focusing on somewhat unexplored affinities between the presence of absorbing and/or inaccessible boundaries. For the Brownian motion (L\'{e}vy-stable cases are briefly mentioned)…

Statistical Mechanics · Physics 2017-10-24 Piotr Garbaczewski

Branching random walks are key to the description of several physical and biological systems, such as neutron multiplication, genetics and population dynamics. For a broad class of such processes, in this Letter we derive the discrete…

Statistical Mechanics · Physics 2012-07-10 Andrea Zoia , Eric Dumonteil , Alain Mazzolo

For distinguishable particles it is well known that Brownian motion and a Feynman-Kac functional can be used to calculate the path integral (for imaginary times) for a general class of scalar potentials. In order to treat identical…

Condensed Matter · Physics 2009-10-28 L. F. Lemmens , F. Brosens , J. T. Devreese

This paper provides a theoretical framework of deriving the forward and backward Feynman-Kac equations for the distribution of functionals of the path of a particle undergoing both diffusion and chemical reaction. Very general forms of the…

Statistical Mechanics · Physics 2018-03-20 Ru Hou , Weihua Deng

Branching random flights are key to describing the evolution of many physical and biological systems, ranging from neutron multiplication to gene mutations. When their paths evolve in bounded regions, we establish a relation between the…

Statistical Mechanics · Physics 2012-12-17 Andrea Zoia , Eric Dumonteil , Alain Mazzolo

In this article we study the long time behavior of linear functionals of branching diffusion processesas well as the time reversal of the spinal process by means of spectral properties of the Feynman-Kacsemigroup. We generalize for this non…

Probability · Mathematics 2024-04-16 Pierre Collet , Sylvie Méléard , Jaime San MARTIN

Functionals of Brownian motion have diverse applications in physics, mathematics, and other fields. The probability density function (PDF) of Brownian functionals satisfies the Feynman-Kac formula, which is a Schrodinger equation in…

Statistical Mechanics · Physics 2010-11-25 Shai Carmi , Lior Turgeman , Eli Barkai

The Feynman-Kac equations are a type of partial differential equations describing the distribution of functionals of diffusive motion. The probability density function (PDF) of Brownian functionals satisfies the Feynman-Kac formula, being a…

Computational Physics · Physics 2015-02-03 Weihua Deng , Minghua Chen , Eli Barkai

We present the idea of intertwining of two diffusions by Feynman-Kac operators. We present some variations and implications of the method and give examples of its applications. Among others, it turns out to be a very useful tool for finding…

Probability · Mathematics 2014-10-21 Maciej Wiśniewolski , Jacek Jakubowski

Discretizations of the Feynman-Kac path integral representation of the quantum mechanical density matrix are investigated. Each infinite-dimensional path integral is approximated by a Riemann integral over a finite-dimensional function…

Statistical Mechanics · Physics 2007-05-23 Stephen D. Bond , Brian B. Laird , Benedict J. Leimkuhler

Barrier crossing is a widespread phenomenon across natural and engineering systems. While an abundant cross-disciplinary literature on the topic has emerged over the years, the stochastic underpinnings of the process are yet to be linked…

Statistical Mechanics · Physics 2024-12-19 Toby Kay , Luca Giuggioli

We study the one-dimensional motion of a Brownian particle inside a confinement described by two reactive boundaries which can partially reflect or absorb the particle. Understanding the effects of such boundaries is important in physics,…

Statistical Mechanics · Physics 2021-03-30 Arnab Pal , Isaac Pérez Castillo , Anupam Kundu

Diffusion processes with branching play an important role in statistical dynamics. They are a common approach to the computing of quantum mechanical groundstates, and serve as models for population dynamics and as physical pictures for…

Condensed Matter · Physics 2008-02-03 Thomas Fricke

Functionals of Brownian/non-Brownian motions have diverse applications and attracted a lot of interest of scientists. This paper focuses on deriving the forward and backward fractional Feynman-Kac equations describing the distribution of…

Data Analysis, Statistics and Probability · Physics 2016-04-06 Xiaochao Wu , Weihua Deng , Eli Barkai

We study the high-temperature behavior of quantum-mechanical path integrals. Starting from the Feynman-Kac formula, we derive a new functional representation of the Wigner-Kirkwood perturbation expansion for quantum Boltzmann densities. As…

Statistical Mechanics · Physics 2014-01-24 Petr Jizba , Vaclav Zatloukal

We investigate signatures of convergence for a sequence of diffusion processes on a line, in conservative force fields stemming from superharmonic potentials $U(x)\sim x^m$, $m=2n \geq 2$. This is paralleled by a transformation of each…

Statistical Mechanics · Physics 2020-10-23 Piotr Garbaczewski , Mariusz Zaba

Probabilistic solutions of the so called Schr\"{o}dinger boundary data problem provide for a unique Markovian interpolation between any two strictly positive probability densities designed to form the input-output statistics data for the…

Quantum Physics · Physics 2009-10-28 Piotr Garbaczewski , Robert Olkiewicz

The existing formulations of the Schr\"{o}dinger interpolating dynamics, which is constrained by the prescribed input-output statistics data, utilize strictly positive Feynman-Kac kernels. This implies that the related Markov diffusion…

Quantum Physics · Physics 2009-10-28 Ph. Blanchard , P. Garbaczewski , R. Olkiewicz

The challenge to fruitfully merge state-of-the-art techniques from mathematical finance and numerical analysis has inspired researchers to develop fast deterministic option pricing methods. As a result, highly efficient algorithms to…

Computational Finance · Quantitative Finance 2015-11-06 Kathrin Glau
‹ Prev 1 2 3 10 Next ›