Creature forcing and large continuum: The joy of halving

For $f,g\in\omega^\omega$ let $c^\forall_{f,g}$ be the minimal number of uniform $g$-splitting trees needed to cover the uniform $f$-splitting tree, i.e., for every branch $\nu$ of the $f$-tree, one of the $g$-trees contains $\nu$. Let $c^\exists_{f,g}$ be the dual notion: For every branch $\nu$, one of the $g$-trees guesses $\nu(m)$ infinitely often. We show that it is consistent that $c^\exists_{f_\epsilon,g_\epsilon}=c^\forall_{f_\epsilon,g_\epsilon}=\kappa_\epsilon$ for continuum many pairwise different cardinals $\kappa_\epsilon$ and suitable pairs $(f_\epsilon,g_\epsilon)$. For the proof we introduce a new mixed-limit creature forcing construction

Wide Angle Compton Scattering

We present the handbag contribution to Wide Angle Compton Scattering (WACS) at moderately large momentum transfer obtained with a proton distribution amplitude close to the asymptotic form. In comparison it is found to be significantly larger than results from the hard scattering (pQCD) approach.Comment: 5 pages, 6 figures, to appear in proceedings of the "Second Workshop on Physics with an Electron Polarized Light Ion Collider", MIT, Cambridge, MA, Sept. 14-16, 200

Quantifying information transfer and mediation along causal pathways in complex systems

Measures of information transfer have become a popular approach to analyze interactions in complex systems such as the Earth or the human brain from measured time series. Recent work has focused on causal definitions of information transfer excluding effects of common drivers and indirect influences. While the former clearly constitutes a spurious causality, the aim of the present article is to develop measures quantifying different notions of the strength of information transfer along indirect causal paths, based on first reconstructing the multivariate causal network (\emph{Tigramite} approach). Another class of novel measures quantifies to what extent different intermediate processes on causal paths contribute to an interaction mechanism to determine pathways of causal information transfer. A rigorous mathematical framework allows for a clear information-theoretic interpretation that can also be related to the underlying dynamics as proven for certain classes of processes. Generally, however, estimates of information transfer remain hard to interpret for nonlinearly intertwined complex systems. But, if experiments or mathematical models are not available, measuring pathways of information transfer within the causal dependency structure allows at least for an abstraction of the dynamics. The measures are illustrated on a climatological example to disentangle pathways of atmospheric flow over Europe.Comment: 20 pages, 6 figure

Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information

Conditional independence testing is a fundamental problem underlying causal discovery and a particularly challenging task in the presence of nonlinear and high-dimensional dependencies. Here a fully non-parametric test for continuous data based on conditional mutual information combined with a local permutation scheme is presented. Through a nearest neighbor approach, the test efficiently adapts also to non-smooth distributions due to strongly nonlinear dependencies. Numerical experiments demonstrate that the test reliably simulates the null distribution even for small sample sizes and with high-dimensional conditioning sets. The test is better calibrated than kernel-based tests utilizing an analytical approximation of the null distribution, especially for non-smooth densities, and reaches the same or higher power levels. Combining the local permutation scheme with the kernel tests leads to better calibration, but suffers in power. For smaller sample sizes and lower dimensions, the test is faster than random fourier feature-based kernel tests if the permutation scheme is (embarrassingly) parallelized, but the runtime increases more sharply with sample size and dimensionality. Thus, more theoretical research to analytically approximate the null distribution and speed up the estimation for larger sample sizes is desirable.Comment: 17 pages, 12 figures, 1 tabl

A note on sewage sludge - risk assessments and fertilization value

A number of recent studies of risk related to agricultural use of sewage sludge are reviewed, as a contribution to the discussion of potential for use in organic agriculture. Furthermore a very tentative assessment of the fertilization value of sewage sludge and its derived products is developed