We consider the quantum thermal statistics à la Gibbs-Shannon-Szilard-Jaynes based on q-entropies S q ͓͔ϭ(qϪ1) Ϫ1 "1Ϫtr(q)… (0Ͻq 1) and the nonstandard ''internal energy'' functionals U q ͓͔ϭtr(q H) proposed by C. Tsallis ͓J.

We report on early results of a numerical and statistical study of binary black hole inspirals. The two black holes are evolved using post-Newtonian approximations starting with initially randomly distributed spin vectors. We characterize certain aspects of the distribution shortly before merger. In particular we note the uniform distribution of black hole spin vector dot products shortly before merger and a high correlation between the initial and final black hole spin vector dot products in the equal-mass, maximally spinning case. These simulations were performed on Graphics Processing Units, and we demonstrate a speed-up of a factor 50 over a more conventional CPU implementation.PACS numbers:

BackgroundAssembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Although roughly a thousand genes are expected to be important for this function in Drosophila melanogaster, just a few hundreds of them are known so far.ResultsIn this work we trained three learning algorithms to predict a “synaptic function” for genes of Drosophila using data from a whole-body developmental transcriptome published by others. Using statistical and biological criteria to analyze and combine the predictions, we obtained a gene catalogue that is highly enriched in genes of relevance for Drosophila synapse assembly and function but still not recognized as such.ConclusionsThe utility of our approach is that it reduces the number of genes to be tested through hypothesis-driven experimentation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1888-3) contains supplementary material, which is available to authorized users.

We perform a statistical analysis of the binary black hole problem in the post-Newtonian approximation by systematically sampling and evolving the parameter space of initial configurations for quasi-circular inspirals. Through a principal component analysis of spin and orbital angular momentum variables we systematically look for uncorrelated quantities and find three of them which are highly conserved in a statistical sense, both as functions of time and with respect to variations in initial spin orientations. We also look for and find the variables that account for the largest variations in the problem. We present binary black hole simulations of the full Einstein equations analyzing to what extent these results might carry over to the full theory in the inspiral and merger regimes. Among other applications these results should be useful both in semi-analytical and numerical building of templates of gravitational waves for gravitational wave detectors.

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