Clusters of galaxies: setting the stage

Clusters of galaxies are self-gravitating systems of mass ~10^14-10^15 Msun. They consist of dark matter (~80 %), hot diffuse intracluster plasma (< 20 %) and a small fraction of stars, dust, and cold gas, mostly locked in galaxies. In most clusters, scaling relations between their properties testify that the cluster components are in approximate dynamical equilibrium within the cluster gravitational potential well. However, spatially inhomogeneous thermal and non-thermal emission of the intracluster medium (ICM), observed in some clusters in the X-ray and radio bands, and the kinematic and morphological segregation of galaxies are a signature of non-gravitational processes, ongoing cluster merging and interactions. In the current bottom-up scenario for the formation of cosmic structure, clusters are the most massive nodes of the filamentary large-scale structure of the cosmic web and form by anisotropic and episodic accretion of mass. In this model of the universe dominated by cold dark matter, at the present time most baryons are expected to be in a diffuse component rather than in stars and galaxies; moreover, ~50 % of this diffuse component has temperature ~0.01-1 keV and permeates the filamentary distribution of the dark matter. The temperature of this Warm-Hot Intergalactic Medium (WHIM) increases with the local density and its search in the outer regions of clusters and lower density regions has been the quest of much recent observational effort. Over the last thirty years, an impressive coherent picture of the formation and evolution of cosmic structures has emerged from the intense interplay between observations, theory and numerical experiments. Future efforts will continue to test whether this picture keeps being valid, needs corrections or suffers dramatic failures in its predictive power.Comment: 20 pages, 8 figures, accepted for publication in Space Science Reviews, special issue "Clusters of galaxies: beyond the thermal view", Editor J.S. Kaastra, Chapter 2; work done by an international team at the International Space Science Institute (ISSI), Bern, organised by J.S. Kaastra, A.M. Bykov, S. Schindler & J.A.M. Bleeke

Computational Methods for Complex Stochastic Systems: A Review of Some Alternatives to MCMC.

We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situations they can be difficult to implement; and suffer from problems such as poor mixing, and the difficulty of diagnosing convergence. Here we review three alternatives to MCMC methods: importance sampling, the forward-backward algorithm, and sequential Monte Carlo (SMC). We discuss how to design good proposal densities for importance sampling, show some of the range of models for which the forward-backward algorithm can be applied, and show how resampling ideas from SMC can be used to improve the efficiency of the other two methods. We demonstrate these methods on a range of examples, including estimating the transition density of a diffusion and of a discrete-state continuous-time Markov chain; inferring structure in population genetics; and segmenting genetic divergence data

Prospective memory and ageing paradox with event-based tasks : A study of young, young-old, and old-old participants

Research on ageing and prospective memory—remembering to do something in the future—has resulted in paradoxical findings, whereby older adults are often impaired in the laboratory but perform significantly better than younger adults in naturalistic settings. Nevertheless, there are very few studies that have examined prospective memory both in and outside the laboratory using the same sample of young and old participants. Moreover, most naturalistic studies have used time-based tasks, and it is unclear whether the prospective memory and ageing paradox extends to event-based tasks. In this study, 72 young (18–30 years), 79 young-old (61–70 years), and 72 old-old (71–80 years) participants completed several event-based tasks in and outside the laboratory. Results showed that the ageing paradox does exist for event-based tasks but manifests itself differently from that in time-based tasks. Thus, younger adults outperformed old-old participants in two laboratory event-based tasks, but there were no age effects for a naturalistic task completed at home (remembering to write the date and time in the upper left corner of a questionnaire). The young and old-old also did not differ in remembering to retrieve a wristwatch from a pocket at the end of the laboratory session. This indicates that the paradox may be due to differences in ongoing task demands in the lab and everyday life, rather than the location per se. The findings call for a concentrated effort towards a theory of cognitive ageing that identifies the variables that do, or do not, account for this paradoxPeer reviewedSubmitted Versio