15,011 research outputs found
A stochastic model for multivariate surveillance of infectious diseases
We describe a stochastic model based on a branching process for analyzing surveillance data of infectious diseases that allows to make forecasts of the future development of the epidemic. The model is based on a Poisson branching process with immigration with additional adjustment for possible overdispersion. An extension to a space-time model for the multivariate case is described. The model is estimated in a Bayesian context using Markov Chain Monte Carlo (MCMC) techniques. We illustrate the applicability of the model through analyses of simulated and real data
Correlated-Electron Theory of Strongly Anisotropic Metamagnets
We present the first correlated-electron theory of metamagnetism in strongly
anisotropic antiferromagnets. Quantum-Monte-Carlo techniques are used to
calculate the field vs. temperature phase diagram of the infinite-dimensional
Hubbard model with easy axis. A metamagnetic transition scenario with 1.~order
and 2.~order phase transitions is found. The apparent similarities to the phase
diagram of FeBr and to mean-field results for the Ising model with
competing interactions are discussed.Comment: 4 pages, RevTeX + one uuencoded ps-file including 3 figure
Streamline integration as a method for structured grid generation in X-point geometry
We investigate structured grids aligned to the contours of a two-dimensional
flux-function with an X-point (saddle point). Our theoretical analysis finds
that orthogonal grids exist if and only if the Laplacian of the flux-function
vanishes at the X-point. In general, this condition is sufficient for the
existence of a structured aligned grid with an X-point. With the help of
streamline integration we then propose a numerical grid construction algorithm.
In a suitably chosen monitor metric the Laplacian of the flux-function vanishes
at the X-point such that a grid construction is possible.
We study the convergence of the solution to elliptic equations on the
proposed grid. The diverging volume element and cell sizes at the X-point
reduce the convergence rate. As a consequence, the proposed grid should be used
with grid refinement around the X-point in practical applications. We show that
grid refinement in the cells neighboring the X-point restores the expected
convergence rate
The influence of temperature dynamics and dynamic finite ion Larmor radius effects on seeded high amplitude plasma blobs
Thermal effects on the perpendicular convection of seeded pressure blobs in
the scrape-off layer of magnetised fusion plasmas are investigated. Our
numerical study is based on a four field full-F gyrofluid model, which entails
the consistent description of high fluctuation amplitudes and dynamic finite
Larmor radius effects. We find that the maximal radial blob velocity increases
with the square root of the initial pressure perturbation and that a finite
Larmor radius contributes to highly compact blob structures that propagate in
the poloidal direction. An extensive parameter study reveals that a smooth
transition to this compact blob regime occurs when the finite Larmor radius
effect strength, defined by the ratio of the magnetic field aligned component
of the ion diamagnetic to the vorticity, exceeds unity.
The maximal radial blob velocities agree excellently with the inertial velocity
scaling law over more than an order of magnitude. We show that the finite
Larmor radius effect strength affects the poloidal and total particle transport
and present an empirical scaling law for the poloidal and total blob
velocities. Distinctions to the blob behaviour in the isothermal limit with
constant finite Larmor radius effects are highlighted
Cluster Dynamical Mean-Field Methods for d-wave Superconductors: the Role of Geometry
We compare the accuracy of two cluster extensions of Dynamical Mean-Field
Theory in describing d-wave superconductors, using as a reference model a
saddle-point t-J model which can be solved exactly in the thermodynamic limit
and at the same time reasonably describes the properties of high-temperature
superconductors. The two methods are Cellular Dynamical Mean-Field Theory,
which is based on a real-space perspective, and Dynamical Cluster
Approximation, which enforces a momentum-space picture by imposing periodic
boundary conditions on the cluster, as opposed to the open boundary conditions
of the first method. We consider the scaling of the methods for large cluster
size, but we also focus on the behavior for small clusters, such as those
accessible by means of present techniques, with particular emphasis on the
geometrical structure, which is definitely a relevant issue in small clusters.Comment: 11 pages, 10 figure
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