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We show how to calculate correlation functions of two matrix models. Our method consists in making full use of the integrable hierarchies and their reductions, which were shown in previous papers to naturally appear in multi--matrix models.…

High Energy Physics - Theory · Physics 2008-02-03 L. Bonora , C. S. Xiong

We obtain exact, simple and very compact expressions for the linearization coefficients of the products of orthogonal polynomials; both the conventional Clebsch-Gordan-type and the modified version. The expressions are general depending…

Classical Analysis and ODEs · Mathematics 2023-06-09 A. D. Alhaidari

In a very high-dimensional vector space, two randomly-chosen vectors are almost orthogonal with high probability. Starting from this observation, we develop a statistical factor model, the random factor model, in which factors are chosen at…

Statistical Finance · Quantitative Finance 2018-12-27 Antti J. Tanskanen , Jani Lukkarinen , Kari Vatanen

Based on the concept of self-decomposable random variables we discuss the application of a model for a pair of dependent Poisson processes to energy facilities. Due to the resulting structure of the jump events we can see the…

Pricing of Securities · Quantitative Finance 2016-07-29 Nicola Cufaro Petroni , Piergiacomo Sabino

We derive an integration by parts formula for functionals of determinantal processes on compact sets, completing the arguments of [4]. This is used to show the existence of a configuration-valued diffusion process which is non-colliding and…

Probability · Mathematics 2015-09-30 Laurent Decreusefond , Ian Flint , Nicolas Privault , Giovanni Luca Torrisi

We present an option pricing formula for European options in a stochastic volatility model. In particular, the volatility process is defined using a fractional integral of a diffusion process and both the stock price and the volatility…

Pricing of Securities · Quantitative Finance 2020-07-29 Marc Lagunas-Merino , Salvador Ortiz-Latorre

We present a method which extends Monte Carlo studies to situations that require a large dynamic range in particle number. The underlying idea is that, in order to calculate the collisional evolution of a system, some particle interactions…

Astrophysics · Physics 2009-11-13 C. W. Ormel , M. Spaans

A highly efficient formulation of moment equations for stochastic reaction networks is introduced. It is based on a set of binomial moments that capture the combinatorics of the reaction processes. The resulting set of equations can be…

Statistical Mechanics · Physics 2015-05-20 Baruch Barzel , Ofer Biham

In this paper we discuss a closed-form approximation of the likelihood functions of an arbitrary diffusion process. The approximation is based on an exponential ansatz of the transition probability for a finite time step $\Delta t$, and a…

Physics and Society · Physics 2008-12-10 Luca Capriotti

We investigate the two-points correlation function for several boundary-driven interacting particle systems. Our goal is to show that the time evolution of that correlation function is solution to a partial differential equation that can be…

Probability · Mathematics 2024-10-24 P. Gonçalves , B. Salvador

We introduce a general procedure for computing higher-order moments of correlation functions in open quantum systems, extending the scope of our recent work on Memory Kernel Coupling Theory (MKCT) [W. Liu, Y. Su, Y. Wang, and W. Dou,…

Quantum Physics · Physics 2025-06-12 Rui-Hao Bi , Wei Liu , Wenjie Dou

A computational procedure is developed for determining the conversion probability for reaction-diffusion systems in which a first-order catalytic reaction is performed over active particles. We apply this general method to systems on metric…

Soft Condensed Matter · Physics 2020-03-19 Renato Feres , Matthew Wallace , Ari Stern , Gregory Yablonsky

Many real-world objects can be modeled as a stream of events on the nodes of a graph. In this paper, we propose a class of graphical event models named temporal point process graphical models for representing the temporal dependencies among…

Methodology · Statistics 2021-10-25 Yalong Lyu , Huiyuan Wang , Wei Lin

In real-world scenario, many phenomena produce a collection of events that occur in continuous time. Point Processes provide a natural mathematical framework for modeling these sequences of events. In this survey, we investigate…

The independent component model is a latent variable model where the components of the observed random vector are linear combinations of latent independent variables. The aim is to find an estimate for a transformation matrix back to…

Statistics Theory · Mathematics 2015-05-12 Joni Virta , Klaus Nordhausen , Hannu Oja

A key step in the comparison between inflationary predictions and cosmological observations is the computation of primordial correlators. Numerical methods have been developed that overcome some of the difficulties arising in analytical…

Cosmology and Nongalactic Astrophysics · Physics 2025-03-20 Andrea Costantini , Laura Iacconi , David J. Mulryne

In this paper, we study the computation of sensitivities with respect to spot of path dependent financial derivatives by means of path weighting. We propose explicit path weighting formula and variance reduction adjustment in order to…

Probability · Mathematics 2024-11-21 Liu Xuan , Gauthier Michel

The calculation of quantum canonical time correlation functions is considered in this paper. Transport properties, such as diffusion and reaction rate coefficients, can be determined from time integrals of these correlation functions.…

Other Condensed Matter · Physics 2010-11-17 Ali Nassimi , Raymond Kapral

We develop a comprehensive mathematical framework for polynomial jump-diffusions in a semimartingale context, which nest affine jump-diffusions and have broad applications in finance. We show that the polynomial property is preserved under…

Mathematical Finance · Quantitative Finance 2019-07-23 Damir Filipović , Martin Larsson

Probabilistic graphical models are widely used to model complex systems under uncertainty. Traditionally, Gaussian directed graphical models are applied for analysis of large networks with continuous variables as they can provide…

Methodology · Statistics 2024-05-27 Victoria Volodina , Nikki Sonenberg , Peter Challenor , Jim Q. Smith