A simple procedure for decreasing the statistical error associated with Monte Carlo integration of oscillatory functions is presented. The method uses available information about the integral of a similar oscillatory function to correlate the estimates of the positive and negative components of the integral. Numerical tests show that information guided noise reduction (IGNoR) leads to substanti...

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggr...

The conventional second-order path-integral Monte Carlo method is plagued with the sign problem in solving many-fermion systems. This is due to the large number of antisymmetric free-fermion propagators that are needed to extract the ground state wave function at large imaginary time. In this work we show that optimized fourth-order path-integral Monte Carlo methods, which use no more than five...

Because of the need for rapid detection and location of diseases in clinical applications, this work proposes a composite measurement of magnetic induction tomography (MIT) and electrical impedance tomography (EIT). This paper is composed of the following aspects: portable and integral hardware design, stable dual constant-current sources, the composite detection method, cross-plane data acquir...

Positron range is one of the main physical effects limiting the spatial resolution of positron emission tomography (PET) images. If positrons travel inside a magnetic field, for instance inside a nuclear magnetic resonance (MR) tomograph, the mean range will be smaller but still significant. In this investigation we examined a method to correct for the positron range effect in iterative image r...

This paper compares fault position and Monte Carlo methods as the most common methods in stochastic assessment of voltage sags. To compare their abilities, symmetrical and unsymmetrical faults with different probability distribution of fault positions along the lines are applied in a test system. The voltage sag magnitude in different nodes of test system is calculated. The problem with the...

Using the geometric deenition of the topological charge we decompose the path integral of 2-dimensional U(1) lattice gauge theory into topological sectors. In a Monte Carlo simulation we compute the average value of the action as well as the distribution of its values for each sector separately. These numbers are compared with analytic lower bounds of the action which are relevant for classical...

II. Classical and Path Integral Monte Carlo (Filinov, Bonitz; Nov. 10,12,14, 17) a) Introduction to classical Metropolis Monte Carlo b) Quantum Statistics, Density matrix c) Feynman’s path integral. Mapping onto an effective classical system d) Spin statistics, exchange, Fermion sign problem e) Generalized Metropolis algorithm for quantum systems, PIMC f) High-temperature N-particle density mat...

Plant canopy reflectance is calculated usinlg the got~ernin~ equation f)r photon transport. The integral equation of tran.sfer is solved by the Monte Carlo method. The main emphasis is on statistical estimation and simulation of the Marcov chain. The leaf dimensions are taken into account in obtaining the hot-spot effect of the canopy. Finally, nmnerieal results fi~r transport equation obtained...