Stochastic group selection model for the evolution of altruism

We study numerically and analytically a stochastic group selection model in which a population of asexually reproducing individuals, each of which can be either altruist or non-altruist, is subdivided into $M$ reproductively isolated groups (demes) of size $N$. The cost associated with being altruistic is modelled by assigning the fitness $1- \tau$, with $\tau \in [0,1]$, to the altruists and the fitness 1 to the non-altruists. In the case that the altruistic disadvantage $\tau$ is not too large, we show that the finite $M$ fluctuations are small and practically do not alter the deterministic results obtained for $M \to \infty$. However, for large $\tau$ these fluctuations greatly increase the instability of the altruistic demes to mutations. These results may be relevant to the dynamics of parasite-host systems and, in particular, to explain the importance of mutation in the evolution of parasite virulence.Comment: 12 pages, 7 figure

Constructive summation of the (2,2) quasi normal mode from a population of black holes

The quasi normal modes (QNMs) associated with gravitational-wave signals from binary black hole (BBH) mergers can provide deep insight into the remnant's properties. Once design sensitivity is achieved, present ground-based gravitational wave interferometers could detect potentially hundreds of BBH signals in the coming years. For most, the ringdown phase will have a very weak signal-to-noise ratio (SNR). Signal summation techniques allow information extraction from the weak SNR ringdowns. We propose a method to constructively sum the (2,2) QNM from different BBH signals by synchronizing and rescaling them. The parameter space adopted to test the method is presently limited to mass ratio $q\leq3$, initially non-spinning black holes with face-on orientation. Moreover, since the synchronisation procedure fails for the weakest signals, we select all ringdowns with SNR above 2.6. Under these conditions, we show that for different BBH populations, 40 to 70% of all the potential detections could be used for the summation while still ensuring a summed SNR of $\sim$80% of the maximal achievable SNR (i.e. for ideally synchronized signals).Comment: 7 pages, 10 figure

Influence of Refractory Periods in the Hopfield model

We study both analytically and numerically the effects of including refractory periods in the Hopfield model for associative memory. These periods are introduced in the dynamics of the network as thresholds that depend on the state of the neuron at the previous time. Both the retrieval properties and the dynamical behaviour are analyzed.Comment: Revtex, 7 pages, 7 figure