Abstract:
The dynamical evolution of small systems undergoing a chiral symmetry breaking transition in the course of rapid expansion is discussed. The time evolution of the dynamical correlation length for trajectories passing through a second-order critical point is extracted. It is shown that while the maximum value of the correlation length is bound from above by dynamical effects, the time interval during which it is near its maximum grows steadily with the system size and with decreasing expansion rate.

Abstract:
We study the hydrodynamical expansion of a hot and baryon-dense quark fluid coupled to classical real-time evolution of the long wavelength modes of the chiral field. Significant density inhomogeneities develop dynamically when the transition to the symmetry-broken state occurs. We find that the amplitude of the density inhomogeneities is larger for expansion trajectories crossing the line of first-order transitions than for crossovers, which could provide some information on the location of a critical point. A few possible experimental signatures for inhomogeneous decoupling surfaces are mentioned briefly.

Abstract:
A variety of physical phenomena can lead to viscous effects. Several sources of shear and bulk viscosity are reviewed with an emphasis on the bulk viscosity associated with chiral restoration and with chemical non-equilibrium. We show that in a mean-field treatment of the limiting case of a second order phase transition, the bulk viscosity peaks in a singularity at the critical point.

Abstract:
A variety of physical phenomena can lead to viscous effects. In this talk we review several sources of shear and bulk viscosity with an emphasis on the bulk viscosity associated with chiral restoration. We show that in the limit of a second order phase transition, the viscosity peaks in a singularity at the critical point.

Abstract:
As an increasing number of well measured type Ia supernovae (SNe Ia) become available, the statistical uncertainty on w has been reduced to the same size as the systematic uncertainty. The statistical error will decrease further in the near future, and hence the improvement of systematic uncertainties needs to be addressed, if further progress is to be made. We study how uncertainties in the primary reference spectrum - which are a main contribution to the systematic uncertainty budget - affect the measurement of the Dark Energy equation of state parameter w from SNe Ia. The increasing number of SN observations can be used to reduce the uncertainties by including perturbations of the reference spectrum as nuisance parameters in a cosmology fit, thus "self-calibrating" the Hubble diagram. We employ this method to real SNe data for the first time and find the perturbations of the reference spectrum consistent with zero at the 1%-level. For future surveys we estimate that ~3500 SNe will be required for our method to outperform the standard method of deriving the cosmological parameters.

Abstract:
We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic follow up. Efficient target selection can improve the ML redshift uncertainties as calculated on an independent sample, while requiring less targets to be observed. We compare the ML targeting algorithms with the Sloan Digital Sky Survey (SDSS) target order, and with a random targeting algorithm. The ML inspired algorithms are constructed iteratively by estimating which of the remaining target galaxies will be most difficult for the machine learning methods to accurately estimate redshifts using the previously observed data. This is performed by predicting the expected redshift error and redshift offset (or bias) of all of the remaining target galaxies. We find that the predicted values of bias and error are accurate to better than 10-30% of the true values, even with only limited training sample sizes. We construct a hypothetical follow-up survey and find that some of the ML targeting algorithms are able to obtain the same redshift predictive power with 2-3 times less observing time, as compared to that of the SDSS, or random, target selection algorithms. The reduction in the required follow up resources could allow for a change to the follow-up strategy, for example by obtaining deeper spectroscopy, which could improve ML redshift estimates for deeper test data.

Abstract:
Although digital imaging techniques are also available for ultrasound imaging with most of the modern machines, only contrast optimization is regularly used. The possible improvement in image quality by digital reprocessing with different filtering techniques was assessed. An independent sonography specialist assessed the shoulder of a healthy test person. Previously described and frequently used standard setup slices were used for this study. A video print was generated after every standard setup, the images were then reprocessed. The resulting edited sonographic images were investigated and judged by 5 experienced sonologists. Several combinations of sonographic views and digital enhancement techniques significantly improved image quality. In conclusion digital reprocessing can improve the quality of images in ultrasound studies of the healthy shoulder.

Abstract:
Massive galaxy clusters at intermediate redshifts act as gravitational lenses that can magnify supernovae (SNe) occurring in background galaxies. We assess the possibility to use lensed SNe to put constraints on the mass models of galaxy clusters and the Hubble parameter at high redshift. Due to the standard candle nature of Type Ia supernovae (SNe Ia), observational information on the lensing magnification from an intervening galaxy cluster can be used to constrain the model for the cluster mass distribution. A statistical analysis using parametric cluster models was performed to investigate the possible improvements from lensed SNe Ia for the accurately modeled galaxy cluster A1689 and the less well constrained cluster A2204. Time delay measurements obtained from SNe lensed by accurately modeled galaxy clusters can be used to measure the Hubble parameter. For a survey of A1689 we estimate the expected rate of detectable SNe Ia and of multiply imaged SNe. The velocity dispersion and core radius of the main cluster potential show strong correlations with the predicted magnifications and can therefore be constrained by observations of SNe Ia in background galaxies. This technique proves especially powerful for galaxy clusters with only few known multiple image systems. The main uncertainty for measurements of the Hubble parameter from the time delay of strongly lensed SNe is due to cluster model uncertainties. For the extremely well modeled cluster A1689, a single time delay measurement could be used to determine the Hubble parameter with a precision of ~ 10%. We conclude that observations of SNe Ia behind galaxy clusters can be used to improve the mass modeling of the large scale component of galaxy clusters and thus the distribution of dark matter. Time delays from SNe strongly lensed by accurately modeled galaxy clusters can be used to measure the Hubble constant at high redshifts.