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The determination of the true source polarization given a set of measurements is complicated by the requirement that the polarization always be positive. This positive bias also hinders construction of upper limits, uncertainties, and confidence regions, especially at low signal-to-noise levels. We generate the likelihood function for linear polarization measurements and use it to create confidence regions and upper limits. This is accomplished by integrating the likelihood function over the true polarization (parameter space), rather than the measured polarization (data space). These regions are valid for both low and high signal-to-noise measurements.
We present an efficient analytical method to predict the maximum transit timing variations of a circumbinary exoplanet, given some basic parameters of the host binary. We derive an analytical model giving limits on the potential location of transits
The theory of general relativity, for which we celebrate the centennial at this Symposium, is based on the Einstein equivalence principle. This principle could be violated through a pseudoscalar-photon interaction, which would also produce a rotation
Systematic errors are inevitable in most measurements performed in real life because of imperfect measurement devices. Reducing systematic errors is crucial to ensuring the accuracy and reliability of measurement results. To this end, delicate error-
With the forthcoming release of high precision polarization measurements, such as from the Planck satellite, the metrology of polarization needs to improve. In particular, it is crucial to take into account full knowledge of the noise properties when
The flow of information reaching us via the online media platforms is optimized not by the information content or relevance but by popularity and proximity to the target. This is typically performed in order to maximise platform usage. As a side effe