Evolution of the X-ray Profiles of Poor Clusters from the XMM-LSS Survey

A sample consisting of 27 X-ray selected galaxy clusters from the XMM-LSS survey is used to study the evolution in the X-ray surface brightness profiles of the hot intracluster plasma. These systems are mostly groups and poor clusters, with temperatures 0.6-4.8 keV, spanning the redshift range 0.05 to 1.05. Comparing the profiles with a standard beta-model motivated by studies of low redshift groups, we find 54% of our systems to possess a central excess, which we identify with a cuspy cool core. Fitting beta-model profiles, allowing for blurring by the XMM point spread function, we investigate trends with both temperature and redshift in the outer slope (beta) of the X-ray surface brightness, and in the incidence of cuspy cores. Fits to individual cluster profiles and to profiles stacked in bands of redshift and temperature indicate that the incidence of cuspy cores does not decline at high redshifts, as has been reported in rich clusters. Rather such cores become more prominent with increasing redshift. Beta shows a positive correlation with both redshift and temperature. Given the beta-T trend seen in local systems, we assume that temperature is the primary driver for this trend. Our results then demonstrate that this correlation is still present at z~0.3, where most of our clusters reside.Comment: Accepted for publication in MNRAS. 15 pages, 12 figure

Covariance matrices for halo number counts and correlation functions

We study the mean number counts and two-point correlation functions, along with their covariance matrices, of cosmological surveys such as for clusters. In particular, we consider correlation functions averaged over finite redshift intervals, which are well suited to cluster surveys or populations of rare objects, where one needs to integrate over nonzero redshift bins to accumulate enough statistics. We develop an analytical formalism to obtain explicit expressions of all contributions to these means and covariance matrices, taking into account both shot-noise and sample-variance effects. We compute low-order as well as high-order (including non-Gaussian) terms. We derive expressions for the number counts per redshift bins both for the general case and for the small window approximation. We estimate the range of validity of Limber's approximation and the amount of correlation between different redshift bins. We also obtain explicit expressions for the integrated 3D correlation function and the 2D angular correlation. We compare the relative importance of shot-noise and sample-variance contributions, and of low-order and high-order terms. We check the validity of our analytical results through a comparison with the Horizon full-sky numerical simulations, and we obtain forecasts for several future cluster surveys.Comment: 37 page

Le hasina : monnaie, parole, regard

L’article explore, dans une perspective psychanalytique, la notion de hasina – variante malgache du mana associant ou condensant la monnaie rituelle lors de l’ancien rite du « Bain royal », la parole politique, le regard comme instrument de domination politique – et ses prolongements actuels dans les rites d’exhumation des morts et les parcours généalogiques ancestraux lors des alliances, c’est-à-dire dans la reproduction sociale des groupes. La dimension inconsciente du hasina défini comme noyau originaire du pouvoir et éviction de l’omnipotence narcissique viendrait s’actualiser dans les rites en répétant, par sa figuration in situ, le mythe oublié, conférant ainsi une identité collective aux groupes, dont l’ancêtre mort est le pivot.Hasina: Money, Speech, Sigh. A Principle of Exchange and Social Reproduction. – The notion of hasina – a Malagasy variant of mana associated with the ritual money used during the ancient “Royal Bath” ceremony and with political speech and sight as a means of political domination – is explored from a psychoanalytic perspective. The current forms of this notion are also explored as it appears in rites for exhuming the dead and in ancestral genealogical itineraries during marital alliances, in other words, in the social reproduction of groups. The unconscious dimension of hasina, defined as the original kernel of power and the eviction of narcissistic omnipotence, actualizes rites by repeating, owing to its figuration in situ, the forgotten myth, thus conferring a collective identity on groups, for whom the dead ancestor is the pivot

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Application to Microgrid Management

We consider a microgrid where different prosumers exchange energy altogether by the edges of a given network. Each prosumer is located to a node of the network and encompasses energy consumption, energy production and storage capacities (battery, electrical hot water tank). The problem is coupled both in time and in space, so that a direct resolution of the problem for large microgrids is out of reach (curse of dimensionality). By affecting price or resources to each node in the network and resolving each nodal sub-problem independently by Dynamic Programming, we provide decomposition algorithms that allow to compute a set of decomposed local value functions in a parallel manner. By summing the local value functions together, we are able, on the one hand, to obtain upper and lower bounds for the optimal value of the problem, and, on the other hand, to design global admissible policies for the original system. Numerical experiments are conducted on microgrids of different size, derived from data given by the research and development centre Efficacity, dedicated to urban energy transition. These experiments show that the decomposition algorithms give better results than the standard SDDP method, both in terms of bounds and policy values. Moreover, the decomposition methods are much faster than the SDDP method in terms of computation time, thus allowing to tackle problem instances incorporating more than 60 state variables in a Dynamic Programming framework

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Decomposition Methods

We consider a large scale multistage stochastic optimization problem involving multiple units. Each unit is a (small) control system. Static constraints couple units at each stage. To tackle such large scale problems, we propose two decomposition methods, whether handling the coupling constraints by prices or by resources. We introduce the sequence (one per stage) of global Bellman functions, depending on the collection of local states of all units. We show that every Bellman function is bounded above by a sum of local resource-decomposed value functions, and below by a sum of local price-decomposed value functions-each local decomposed function having for arguments the corresponding local unit state variables. We provide conditions under which these local value functions can be computed by Dynamic Programming. These conditions are established assuming a centralized information structure, that is, when the information available for each unit consists of the collection of noises affecting all the units. We finally study the case where each unit only observes its own local noise (decentralized information structure)