310 research outputs found
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)
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