Initial condition inverse problems are ill-posed and computationally expensive to solve. We present a computational approach for solving inverse problems in the realm of onedimensional contaminant transport. The approach employs finite differencing as a forward solver and probabilistic methods for inversion. Markov Chain Monte Carlo sampling is used to efficiently recover posterior probabilitie...

Options is an important financial derivative products, therefore it is important to reasonable pricing. According to the financial asset returns typically exhibit the feature of aiguilles large remaining part and hypothesis, it obeys normal inverse Gaussian distribution, using Monte Carlo simulation based on normal inverse Gaussian distribution on its pricing and improving it by antithesis vari...

abstract background: accurate methods of radiation therapy dose calculation. there are different monte carlo codesfor simulation of photons, electrons and the coupled transport of electrons and photons. mcnpis a general purpose monte carlo code that can be used for electron, photon and coupledphoton-electron transport.monte carlo simulation of radiation transport is considered to be one of the ...

This work aims at the comparison between a classical regularization technique and a method within the Bayesian framework, as applied to the solution of an inverse heat conduction problem. The two solution approaches compared are Alifanov's iterative regularization technique and the Markov chain Monte Carlo method. The inverse problem examined in this work deals with the estimation of a transien...

We present a numerical study of the random Blume-Capel model in three dimensions. The phase diagram is characterized by spin-glass-paramagnet phase transitions of both first and second order in the thermodynamic sense. Numerical simulations are performed using the exchange Monte Carlo algorithm, providing clear evidence for inverse freezing. The main features at criticality and in the phase coe...