Truncation method for Green's functions in time-dependent fields

We investigate the influence of a time dependent, homogeneous electric field on scattering properties of non-interacting electrons in an arbitrary static potential. We develop a method to calculate the (Keldysh) Green's function in two complementary approaches. Starting from a plane wave basis, a formally exact solution is given in terms of the inverse of a matrix containing infinitely many 'photoblocks' which can be evaluated approximately by truncation. In the exact eigenstate basis of the scattering potential, we obtain a version of the Floquet state theory in the Green's functions language. The formalism is checked for cases such as a simple model of a double barrier in a strong electric field. Furthermore, an exact relation between the inelastic scattering rate due to the microwave and the AC conductivity of the system is derived which in particular holds near or at a metal-insulator transition in disordered systems.Comment: to appear in Phys. Rev. B., 21 pages, 3 figures (ps-files

Circular polarization dependent study of the microwave photoconductivity in a two-dimensional electron system

The polarization dependence of the low field microwave photoconductivity and absorption of a two-dimensional electron system has been investigated in a quasi-optical setup in which linear and any circular polarization can be produced in-situ. The microwave induced resistance oscillations and the zero resistance regions are notedly immune to the sense of circular polarization. This observation is discrepant with a number of proposed theories. Deviations only occur near the cyclotron resonance absorption where an unprecedented large resistance response is observed.Comment: 5 pages, 3 figure

Dynamical scaling of the quantum Hall plateau transition

Using different experimental techniques we examine the dynamical scaling of the quantum Hall plateau transition in a frequency range f = 0.1-55 GHz. We present a scheme that allows for a simultaneous scaling analysis of these experiments and all other data in literature. We observe a universal scaling function with an exponent kappa = 0.5 +/- 0.1, yielding a dynamical exponent z = 0.9 +/- 0.2.Comment: v2: Length shortened to fulfil Journal criteri

Scalar-Tensor Cosmological Models

We analyze the qualitative behaviors of scalar-tensor cosmologies with an arbitrary monotonic $\omega(\Phi)$ function. In particular, we are interested on scalar-tensor theories distinguishable at early epochs from General Relativity (GR) but leading to predictions compatible with solar-system experiments. After extending the method developed by Lorentz-Petzold and Barrow, we establish the conditions required for convergence towards GR at $t\rightarrow\infty$. Then, we obtain all the asymptotic analytical solutions at early times which are possible in the framework of these theories. The subsequent qualitative evolution, from these asymptotic solutions until their later convergence towards GR, has been then analyzed by means of numerical computations. From this analysis, we have been able to establish a classification of the different qualitative behaviors of scalar-tensor cosmological models with an arbitrary monotonic $\omega(\Phi)$ function.Comment: uuencoded compressed postscript file containing 41 pages, with 9 figures, accepted for publication in Physical Review

A distributed optimization method for the geographically distributed data centres problem

The geographically distributed data centres problem (GDDC) is a naturally distributed resource allocation problem. The problem involves allocating a set of virtual machines (VM) amongst the data centres (DC) in each time period of an operating horizon. The goal is to optimize the allocation of workload across a set of DCs such that the energy cost is minimized, while respecting limitations on data centre capacities, migrations of VMs, etc. In this paper, we propose a distributed optimization method for GDDC using the distributed constraint optimization (DCOP) framework. First, we develop a new model of the GDDC as a DCOP where each DC operator is represented by an agent. Secondly, since traditional DCOP approaches are unsuited to these types of large-scale problem with multiple variables per agent and global constraints, we introduce a novel semi-asynchronous distributed algorithm for solving such DCOPs. Preliminary results illustrate the benefits of the new method

Territorial rights and colonial wrongs

What is wrong with colonialism? The standard—albeit often implicit—answer to this question has been that colonialism was wrong because it violated the territorial rights of indigenous peoples, where territorial rights were grounded on acquisition theories. Recently, the standard view has come under attack: according to critics, acquisition based accounts do not provide solid theoretical grounds to condemn colonial relations. Indeed, historically they were used to justify colonialism. Various alternative accounts of the wrong of colonialism have been developed. According to some, colonialism involved a violation of territorial rights grounded on legitimate state theory. Others reject all explanations of colonialism's wrongfulness based on territorial rights, and argue that colonial practices were wrong because they departed from ideals of economic, social, and political association. In this article, we articulate and defend the standard view against critics: colonialism involved a procedural wrong; this wrong is not the violation of standards of equality and reciprocity, but the violation of territorial rights; and the best foundation for such territorial rights is acquisition based, not legitimacy based. We argue that this issue is not just of historical interest, it has relevant implications for the normative evaluation of contemporary inequalities

A time predefined variable depth search for nurse rostering

This paper presents a variable depth search for the nurse rostering problem. The algorithm works by chaining together single neighbourhood swaps into more effective compound moves. It achieves this by using heuristics to decide whether to continue extending a chain and which candidates to examine as the next potential link in the chain. Because end users vary in how long they are willing to wait for solutions, a particular goal of this research was to create an algorithm that accepts a user specified computational time limit and uses it effectively. When compared against previously published approaches the results show that the algorithm is very competitive

Neonatal intervention

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68335/2/10.1177_027112148300300105.pd