The global illumination or transport problems can also be considered as a sequence of integrals, while its MonteCarlo solutions as different sampling techniques. Multiple importance sampling takes advantage of different sampling strategies and combines the results obtained with them. In this paper we propose the combination of very different global illumination algorithms in a way that their st...

In this paper, a Bit Error Rate (BER) analysis is presented for Multiple-Input Multiple-Output (MIMO) schemes in the 3GPP Long Term Evolution (LTE) system. Analytical expressions for the average BER of the system are derived over flat Rayleigh fading channels for two different MIMO schemes as defined in LTE, assuming M-ary quadrature amplitude modulation (M-QAM) schemes and are evaluated numeri...

We propose an alternative approach to stochastic programming based on MonteCarlo sampling and stochastic gradient optimization. The procedure is by essence probabilistic and the computed solution is a random variable. The associated objective value is doubly random, since it depends on two outcomes: the event in the stochastic program and the randomized algorithm. We propose a solution concept ...

This paper gives an overview of a reconstruction algorithm for muon events in ATLAS experiment at CERN. After a short introduction on ATLAS Muon Spectrometer, we will describe the procedure performed by the algorithms Muonbox and Muonboy (last version) in order to achieve correctly the reconstruction task. These algorithms have been developed in Fortran language and are working in the official ...

Presented here is an algorithm for a type-II quantum computer which simulates the Ising model in one and two dimensions. It is equivalent to the Metropolis MonteCarlo method and takes advantage of quantum superposition for random number generation. This algorithm does not require the ensemble of states to be measured at the end of each iteration, as is required for other type-II algorithms. Onl...

A very computationally-efficient MonteCarlo algorithm for the calculation of Dempster-Shafer belief is described. If Bel is the combination using Dempster’s Rule of belief functions Bel1, . . . ,Belm then, for subset b of the frame Θ, Bel(b) can be calculated in time linear in |Θ| and m (given that the weight of conflict is bounded). The algorithm can also be used to improve the complexity of t...

For combinatorial search in single-player games nested MonteCarlo search is an apparent alternative to algorithms like UCT that are applied in two-player and general games. To trade exploration with exploitation the randomized search procedure intensifies the search with increasing recursion depth. If a concise mapping from states to actions is available, the integration of policy learning yiel...

This paper proposes simple feedback loops, inspired from extremum-seeking, that use the photon emission times of a single quantum system following quantum MonteCarlo trajectories in order to lock in real time a probe frequency to the system’s transition frequency. Two specific settings are addressed: a 3-level system coupling one ground to two excited states (one highly unstable and one metasta...

The first author’s name is cited incorrectly. The correct name for the citation is: Di Giorgio L. The correct citation is: Di Giorgio L, Flaxman AD, Moses MW, Fullman N, Hanlon M, Conner RO, et al. (2016) Efficiency of Health Care Production in Low-Resource Settings: A MonteCarlo Simulation to Compare the Performance of Data Envelopment Analysis, Stochastic Distance Functions, and an Ensemble M...

We present version 3.0 of the atmospheric chemistry box model CAABA/MECCA. In addition to a complete update of the rate coefficients to the most recent recommendations, a number of new features have been added: chemistry in multiple aerosol size bins; automatic multiple simulations reaching steady-state conditions; MonteCarlo simulations with randomly varied rate coefficients within their exper...