A new measure for party coherence: Applying a physics-based concept to the Swiss party system

The paper revives a theoretical definition of party coherence as being composed of two basic elements, cohesion and factionalism, to propose and apply a novel empirical measure based on spin physics. The simultaneous analysis of both components using a single measurement concept is applied to data representing the political beliefs of candidates in the Swiss general elections of 2003 and 2007, proposing a connection between the coherence of the beliefs party members hold and the assessment of parties being at risk of splitting. We also compare our measure with established polarization measures and demonstrate its advantage with respect to multi-dimensional data that lack clear structure. Furthermore, we outline how our analysis supports the distinction between bottom-up and top-down mechanisms of party splitting. In this way, we are able to turn the intuition of coherence into a defined quantitative concept that, additionally, offers a methodological basis for comparative research of party coherence. Our work serves as an example of how a complex systems approach allows to get a new perspective on a long-standing issue in political science.

Extraction of spin periods of space debris from optical light curves

The population of space debris increased drastically during the last years. These objects have become a great threat for active satellites. Because the relative velocities between space debris and satellites are high, space debris objects may destroy active satellites through collisions. Furthermore, collisions involving massive objects produce large number of fragments leading to significant growth of the space debris population. The long term evolution of the debris population is essentially driven by so-called catastrophic collisions. An effective remediation measure in order to stabilize the population in Low Earth Orbit (LEO) is therefore the removal of large, massive space debris. To remove these objects, not only precise orbits, but also more detailed information about their attitude states will be required. One important property of an object targeted for removal is its spin period, spin axis orientation and their change over time. Rotating objects will produce periodic brightness variations with frequencies which are related to the spin periods. Such a brightness variation over time is called a light curve. Collecting, but also processing light curves is challenging due to several reasons. Light curves may be undersampled, low frequency components due to phase angle and atmospheric extinction changes may be present, and beat frequencies may occur when the rotation period is close to a multiple of the sampling period. Depending on the method which is used to extract the frequencies, also method-specific properties have to be taken into account. The astronomical Institute of the University of Bern (AIUB) light curve database will be introduced, which contains more than 1,300 light curves acquired over more than seven years. We will discuss properties and reliability of different time series analysis methods tested and currently used by AIUB for the light curve processing. Extracted frequencies and reconstructed phases for some interesting targets, e.g. GLONASS satellites, for which also SLR data were available for the period confirmation, will be presented. Finally we will present the reconstructed phase and its evolution over time of a High-Area-to-Mass-Ratio (HAMR) object, which AIUB observed for several years.