We use a recently found parametrization of the solutions of the inverse Frobenius-Perron problem within the class of complete unimodal maps to develop a Monte-Carlo approach for the construction of one-dimensional chaotic dynamical laws with given statistical properties, i.e. invariant density and autocorrelation function. A variety of different examples are presented to demonstrate the power o...

The library LINPRO which provides the solution to the linear inverse problem for data contaminated by a statistical noise is presented. The library makes use of two methods: Maximum Entropy Method and Singular Value Decomposition. As an example it has been applied to perform an analytic continuation of the imaginary time propagator obtained within the Quantum Monte Carlo method.

We present an exact local bosonic algorithm for the simulation of dynamical fermions in lattice QCD. It is based on a non-hermitian polynomial approximation of the inverse of the quark matrix and a global Metropolis accept/reject correction of the systematic errors. We show that this algorithm is a real alternative to the Hybrid Monte Carlo algorithm.

With large-scale Monte Carlo simulations, we confirm that for the two-dimensional XY model, there is a logarithmic correction to scaling in the dynamic relaxation starting from a completely disordered state, while only an inverse power law correction in the case of starting from an ordered state. The dynamic exponent z is z=2.04(1).

Automatic glottal inverse filtering with the Markov chain Monte Carlo method Harri Auvinen a, Tuomo Raitio b,∗, Manu Airaksinen b, Samuli Siltanen a, Brad H. Story c, Paavo Alku b a Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland b Department of Signal Processing and Acoustics, Aalto University, Espoo, Finland c Department of Speech and Hearing Sciences, Univ...

Inverse problems in geophysics require the introduction of complex a priori information and are solved using computationally expensive Monte Carlo techniques where large portions of the model space are explored . The geostatistical method allows for fast integration of complex a priori information in the form of covariance functions and training images. We combine geostatistical methods and inv...

Electrical Capacitance Tomography is an ill-posed inverse problem that aims at recovering the spatial permittivity distribution of an inhomogeneous medium from capacitance measurements at the boundary. We consider the problem of fast robust estimation of inclusion shape and position in binary mixtures. The boundary of the inclusion is represented implicitly using a radial basis function represe...