Convergence of adaptive mixtures of importance sampling schemes

In the design of efficient simulation algorithms, one is often beset with a poor choice of proposal distributions. Although the performance of a given simulation kernel can clarify a posteriori how adequate this kernel is for the problem at hand, a permanent on-line modification of kernels causes concerns about the validity of the resulting algorithm. While the issue is most often intractable for MCMC algorithms, the equivalent version for importance sampling algorithms can be validated quite precisely. We derive sufficient convergence conditions for adaptive mixtures of population Monte Carlo algorithms and show that Rao--Blackwellized versions asymptotically achieve an optimum in terms of a Kullback divergence criterion, while more rudimentary versions do not benefit from repeated updating.Comment: Published at http://dx.doi.org/10.1214/009053606000001154 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Recursion relations for generalized Fresnel coefficients: Casimir force in a planar cavity

We emphasize and demonstrate that, besides using the usual recursion relations involving successive layers, generalized Fresnel coefficients of a multilayer can equivalently be calculated using the recursion relations involving stacks of layers, as introduced some time ago [M. S. Tomas, Phys. Rev. A 51, 2545 (1995)]. Moreover, since the definition of the generalized Fresnel coefficients employed does not imply properties of the stacks, these nonstandard recursion relations can be used to calculate Fresnel coefficients not only for local systems but also for a general multilayer consisting of various types (local, nonlocal, inhomogeneous etc.) of layers. Their utility is illustrated by deriving a few simple algorithms for calculating the reflectivity of a Bragg mirror and extending the formula for the Casimir force in a planar cavity to arbitrary media.Comment: 5 pages, 2 figures, slightly expande

Tilted excitation implies odd periodic resonances

This work was supported by the Brazilian agencies FAPESP and CNPq. MSB also acknowledges the Engineering and Physical Sciences Research Council grant Ref. EP/I032606/1. GID thanks Felipe A. C. Pereira for fruitful discussions.Peer reviewedPostprin

A low-luminosity type-1 QSO sample; III. Optical spectroscopic properties and activity classification

We report on the optical spectroscopic analysis of a sample of 99 low-luminosity quasi-stellar objects (LLQSOs) at $z\leq 0.06$ base the Hamburg/ESO QSO survey (HES). The LLQSOs presented here offer the possibility of studying the faint end of the QSO population at smaller cosmological distances and, therefore, in greater detail. A small number of our LLQSO present no broad component. Two sources show double broad components, whereas six comply with the classic NLS1 requirements. As expected in NLR of broad line AGNs, the [S{\sc{ii}}]$-$based electron density values range between 100 and 1000 N$_{e}$/cm$^{3}$. Using the optical characteristics of Populations A and B, we find that 50\% of our sources with H$\beta$ broad emission are consistent with the radio-quiet sources definition. The remaining sources could be interpreted as low-luminosity radio-loud quasar. The BPT-based classification renders an AGN/Seyfert activity between 50 to 60\%. For the remaining sources, the possible star burst contribution might control the LINER and HII classification. Finally, we discuss the aperture effect as responsible for the differences found between data sets, although variability in the BLR could play a significant role as well.Comment: 22 pages; 5 tables; 17 figures; in press with A&

A COMPARISON BETWEEN RANDOM AND DETERMINISTIC DYNAMICS OF RIVER DRAINAGE BASINS FORMATION

This work contributes to the discussion on how and why tree networks in drainage basin arises in nature. A fully deterministic erosion model recently developed was used to explain the spontaneous origin of river networks, which until then was assumed to be due to the optimal reduction of the flow resistance in a area to point flow. A random evolution model was devised in order to investigate the contribution of two separate features: the relative area size of the network and the structure (configuration) of the network. Two random models were applied, namely, restricted random choosing selection and fully random. Results showed that indeed the mere presence of low flow resistance portions of the basin does improve global performance and that randomness does not create networks. Further gain in performance is given by the network formation by erosion or by optimization. This suggest that local factors also are important to the explanation of the very existence of natural networks