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We use the diagrammatic Monte Carlo approach to solve the problem of a single spin-down fermion resonantly interacting with a Fermi gas of spin-up particles. Our solution is important for understandin...
In Monte Carlo simulations, the thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. As the stochastic error of the simula...
Abstract: Finding the parameter values of differential equation models from data is an important part of the modelling process. Large models and sparse data often make the parameters very difficult to...
Abstract: This paper extends the idea of E.Gobet, J.P.Lemor and X.Warin from the setting of Backward Stochastic Differential Equations to that of Backward Doubly Stochastic Differential equations. We ...
Metastable structures, e.g. amorphous solids of colloids [1] and stalks in membrane fusion [2, 3], are observed in various systems. Such non-equilibrium states often have long lifetimes and cause di...
A Markov Chain Monte Carlo model for integrating the observations of inorganic species with a thermodynamic equilibrium model was presented in Part I of this series. Using observations taken at three ...
The equilibrium inorganic aerosol model ISORROPIA was embedded in a Markov Chain Monte Carlo algorithm to develop a powerful tool to analyze aerosol data and predict gas phase concentrations where the...
In this paper we present a new Monte Carlo algorithm for finding the solution of Dirichlet partial differential equations (DPDE). Here, we show the solution of a given DPDE, can be found by a new effi...

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