Monte Carlo algorithms have a growing impact on nuclear medicine reconstruction processes. One of the main limitations myocardial perfusion imaging (MPI) is effective mitigation scattering component, which particularly challenging in Single Photon Emission Computed Tomography (SPECT). In SPECT, no timing information can be retrieved to locate primary source photons. methods allow an event-by-ev...

We present a Monte Carlo-derived Green's function for the propagation of partially spatially coherent fields. This Green's function, which is derived by sampling Huygens-Fresnel wavelets, can be used to propagate fields through an optical system and to compute first- and second-order field statistics directly. The concept is illustrated for a cylindrical f/1 imaging system. A Gaussian copula is...

In many practical applications of structural reliability analysis, one is interested in knowing the sensitivity of the probability of failure to design parameters that enter the definition of the limit-state function. This information is required for example in reliability-based design optimization. Parameter sensitivities are obtained by FORM/SORM, in terms of the sensitivity of the respective...

PURPOSE Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods tha...

Path Integral Monte Carlo simulations have been performed for U(1) lattice gauge theory in (2+1) dimensions on anisotropic lattices. We extract the static quark potential, the string tension and the low-lying “glueball” spectrum. The Euclidean string tension and mass gap decrease exponentially at weak coupling in excellent agreement with the predictions of Polyakov and Göpfert and Mack, but the...

The dynamic structure factor S(q, w) for a model of superfluid 4He in disorder is evaluated using Path Integral Monte Carlo and Maximum Entropy methods. Disorder is represented by randomly distributed static impurities interacting with the 4He atoms via a simple attractive potential. The potential is parametrized to yield different values of the variance and correlation length of the resulting ...

In palaeoclimate reconstruction, the natural modelling direction is forwards from climate to sensors to proxy measurements. Statistical methods can be used to invert this direction, making climate inferences from proxy measurements. Among these methods, the Bayesian method would seem to deal best with the substantial epistemic uncertainties about climate, and about its impact on sensors. The ma...

Purpose: Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein’s unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods th...