Broadband XUV polarimetry of high harmonics from plasma surfaces using multiple Fresnel reflections

High-harmonic generation (HHG) by nonlinear interaction of intense laser pulses with gases or plasma surfaces is the most prominent way of creating highly coherent extreme ultraviolet (EUV/XUV) pulses. In the last years, several scientific applications have been found which require the measurement of the polarization of the harmonic radiation. We present a broadband XUV polarimeter based on multiple Fresnel reflections providing an extinction rate of 5-25 for 17-45 nm which is particularly suited for surface harmonics. The device has first been tested at a gas harmonic source providing linearly polarized XUV radiation. In a further experiment using HHG from plasma surfaces, the XUV polarimeter allowed a polarization measurement of high harmonic radiation from plasma surfaces for the first time which reveals a linear polarization state as predicted for our generation parameters. The generation and control of intense polarized XUV pulses-together with the availability of broadband polarizers in the XUV-open the way for a series of new experiments. For instance, dichroism in the XUV, elliptically polarized harmonics from aligned molecules, or the selection rules of relativistic surface harmonics can be studied with the broadband XUV polarimeter.

A spatial approach to network generation for three properties:Degree distribution, clustering coefficient and degree assortativity

Social networks generally display a positively skewed degree distribution and higher values for clustering coefficient and degree assortativity than would be expected from the degree sequence. For some types of simulation studies, these properties need to be varied in the artificial networks over which simulations are to be conducted. Various algorithms to generate networks have been described in the literature but their ability to control all three of these network properties is limited. We introduce a spatially constructed algorithm that generates networks with constrained but arbitrary degree distribution, clustering coefficient and assortativity. Both a general approach and specific implementation are presented. The specific implementation is validated and used to generate networks with a constrained but broad range of property values. © Copyright JASSS.