The impact of the air-fluorescence yield on the reconstructed shower parameters of ultra-high energy cosmic rays

An accurate knowledge of the fluorescence yield and its dependence on atmospheric properties such as pressure, temperature or humidity is essential to obtain a reliable measurement of the primary energy of cosmic rays in experiments using the fluorescence technique. In this work, several sets of fluorescence yield data (i.e. absolute value and quenching parameters) are described and compared. A simple procedure to study the effect of the assumed fluorescence yield on the reconstructed shower parameters (energy and shower maximum depth) as a function of the primary features has been developed. As an application, the effect of water vapor and temperature dependence of the collisional cross section on the fluorescence yield and its impact on the reconstruction of primary energy and shower maximum depth has been studied.Comment: Accepted in Astroparticle Physic

Anisotropic Dependence of Giant Magneto-Impedance of Amorphous Ferromagnetic Ribbon on Biasing Field

The magneto-impedance (MI) in amorphous ribbon of nominal composition Fe73.5Nb3Cu1Si13.5B9 has been measured at 1MHz and at room temperature for different configurations of exciting a.c and biasing d.c. fields. A large drop in both resistance and reactance is observed as a function of d.c magnetic field. When the d.c and a.c fields are parallel but normal to the axis of ribbon, smaller magnetic field is needed to reduce the impedance to its small saturated value compared to the situation when fields are along the axis of ribbon. Larger d.c. field is required to lower the impedance when the d.c field acts perpendicular to the plane of the ribbon. Such anisotropy in magneto-impedance is related to the anisotropic response of the magnetization of ribbon. The large change of impedance is attributed to large variation of a.c permeability on the direction and magnitude of the dc biasing field.Comment: 12 pages, 7 figures, to be published in "International Journal of Modern Physics B

Agent Based Models of Language Competition: Macroscopic descriptions and Order-Disorder transitions

We investigate the dynamics of two agent based models of language competition. In the first model, each individual can be in one of two possible states, either using language $X$ or language $Y$, while the second model incorporates a third state XY, representing individuals that use both languages (bilinguals). We analyze the models on complex networks and two-dimensional square lattices by analytical and numerical methods, and show that they exhibit a transition from one-language dominance to language coexistence. We find that the coexistence of languages is more difficult to maintain in the Bilinguals model, where the presence of bilinguals in use facilitates the ultimate dominance of one of the two languages. A stability analysis reveals that the coexistence is more unlikely to happen in poorly-connected than in fully connected networks, and that the dominance of only one language is enhanced as the connectivity decreases. This dominance effect is even stronger in a two-dimensional space, where domain coarsening tends to drive the system towards language consensus.Comment: 30 pages, 11 figure

Analytical Solution of the Voter Model on Disordered Networks

We present a mathematical description of the voter model dynamics on heterogeneous networks. When the average degree of the graph is $\mu \leq 2$ the system reaches complete order exponentially fast. For $\mu >2$, a finite system falls, before it fully orders, in a quasistationary state in which the average density of active links (links between opposite-state nodes) in surviving runs is constant and equal to $\frac{(\mu-2)}{3(\mu-1)}$, while an infinite large system stays ad infinitum in a partially ordered stationary active state. The mean life time of the quasistationary state is proportional to the mean time to reach the fully ordered state $T$, which scales as $T \sim \frac{(\mu-1) \mu^2 N}{(\mu-2) \mu_2}$, where $N$ is the number of nodes of the network, and $\mu_2$ is the second moment of the degree distribution. We find good agreement between these analytical results and numerical simulations on random networks with various degree distributions.Comment: 20 pages, 8 figure

Gestion en temps réel d'un réseau d'assainissement : vérification de l'optimalité et de l'applicabilité de la théorie des graphes par rapport à la programmation linéaire mixte

Dans le cas de la gestion en temps réel des réseaux d'assainissement, la première étape peut, par exemple, consister à vérifier qu'une manipulation des organes de contrôle tels que les vannes et pompes est capable de minimiser les déversements vers le milieu naturel. Cette gestion, que l'on appellera " gestion de référence ", permet de déterminer les stratégies de commande sur toute la durée de l'événement pluvieux connu à l'avance. Ce calcul se fait donc à la fin de l'événement pluvieux et permet de dire ce qui aurait pu être fait avec les organes de régulation en terme de minimisation des volumes déversés. La programmation linéaire par les graphes et la programmation linéaire mixte permettent de déterminer une solution optimale. Cet article s'intéresse à la vérification de l'optimalité et à l'applicabilité de la programmation linéaire par les graphes comparée à la programmation linéaire mixte dans le cas de la " gestion de référence " sur le réseau d'assainissement de Saverne (France). En comparant les volumes déversés par ces deux techniques d'optimisation sur 34 événements pluvieux, nous pouvons confirmer que l'approche par les graphes ne donne pas toujours le minimum global. Les résultats ont montré que la programmation linéaire mixte fournit des temps de calcul qui peuvent atteindre plus de 24 heures. Par contre, l'approche par les graphes permet un temps de calcul de l'ordre de 5 minutes en moyenne avec un minimum global en terme de volume déversé atteint qui n'excède pas 5% par rapport à la solution fournie par la programmation linéaire mixte.The first stage of real-time management of wastewater systems could, for example, consist of making sure that the use of controls such as valves and pumps can indeed minimise the discharge into the natural environment. This management step, referred to as reference management, is used to determine the control strategies over the entire duration of a rainfall event known in advance. The calculation is therefore performed at the end of the rainfall event and is used to determine what could have been done with the regulation components (e.g. in terms of minimising the volumes discharged). The calculation can also show whether or not it is necessary to control the valves and pumps during the rainfall occurrence (dynamic management) rather than fixing the flow rates in advance (static management) if the receiving body of water is to be protected from discharges.In the area of operational research, management controls can be determined with the help of linear programming. Here the aim is to minimise the linear function (f), generally called the cost function or objective function, under different linear constraints (g). There are several variants of linear programming. The first one is mixed linear programming, where some variables are required to be integers or even binary. Conventional calculation techniques such as branch-and-bound method provide a global minimum solution, but the calculation is very lengthy.Another variant of linear programming is graph programming. This optimisation technique consists of modelling the hydraulic behaviour of most of the constructions that can be found in wastewater systems (main drains, storm overflows, storm water basins, etc.). It has been applied to the wastewater system of Saverne in order to minimise the volumes discharged into the natural environment. In order to ensure that the constructions are modelled correctly and to optimise the functioning of the controls, saturation constraints had to be added to the choice of the arcs of the graph. The primal-dual algorithm no longer provides a global minimum solution when these constraints are added. In contrast, the calculation time is much shorter than that for mixed linear programming.This article is aimed at comparing the results in terms of the minimisation of the discharged volumes by means of linear programming with graphs and mixed linear programming, as part of the reference management applied to the wastewater system of Saverne. The final goal was to be able to select a compromise between the relevance or the accuracy of the results and the means to achieve them.We have shown that wastewater constructions such as main drains, storm basins and overflows can be modelled simply with the two techniques above. However, it is necessary to add binary variables in the case of mixed linear programming and a degree of arc saturation if the graph approach is used. The branch-and-bound algorithm used for mixed linear programming can be used to obtain a global minimum solution, with a very long calculation time. In contrast, even though the convergence time is very short for linear programming with graphs, the global minimum cannot be ensured because the algorithm used imposes independence with respect to the choice of the arcs to be saturated.Given the benefits and drawbacks of each approach, we have attempted to use the example of the wastewater system of Saverne to quantify the calculation time and the differences in terms of the discharged volume. The results have shown that mixed linear programming requires calculation times that can last over 24 h. In contrast, with the graph approach, the calculation takes approximately five minutes on average, with a global minimum in terms of volume that does not exceed 5% as compared to the solution obtained by mixed linear programming. We have shown that a solution requiring a much shorter calculation time is available and offers a compromise between exact determination and an optimised associated calculation time

Generic Absorbing Transition in Coevolution Dynamics

We study a coevolution voter model on a network that evolves according to the state of the nodes. In a single update, a link between opposite-state nodes is rewired with probability $p$, while with probability $1-p$ one of the nodes takes its neighbor's state. A mean-field approximation reveals an absorbing transition from an active to a frozen phase at a critical value $p_c=\frac{\mu-2}{\mu-1}$ that only depends on the average degree $\mu$ of the network. The approach to the final state is characterized by a time scale that diverges at the critical point as $\tau \sim |p_c-p|^{-1}$. We find that the active and frozen phases correspond to a connected and a fragmented network respectively. We show that the transition in finite-size systems can be seen as the sudden change in the trajectory of an equivalent random walk at the critical rewiring rate $p_c$, highlighting the fact that the mechanism behind the transition is a competition between the rates at which the network and the state of the nodes evolve.Comment: 5 pages, 4 figure