Quantum Effects in Matter-Wave Diffraction

Advances in micro-technology of the last years have made it possible to carry optics textbooks experiments over to atomic and molecular beams, such as diffraction by a double slit or transmission grating. The usual wave-optical approach gives a good qualitative description of these experiments. However, small deviations therefrom and sophisticated quantum mechanics yield new surprising insights on the size of particles and on their interaction with surfaces.Comment: 6 pages, 3 Postscript figures. To appear in the Proceedings of Quantum Theory and Symmetry, Cracow, July 2001, edited by E. Kapuscik and A. Horzela, World Scientifi

Tree modules

After stating several tools which can be used to construct indecomposable tree modules for quivers without oriented cycles, we use these methods to construct indecomposable tree modules for every imaginary Schur root. These methods also give a recipe for the construction of tree modules for every root. Moreover, we give several examples illustrating the results.Comment: Typos corrected; references added; deleted former Lemma 3.13 which is not neede

Perspective: network-guided pattern formation of neural dynamics

The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain's network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs, or hierarchical network organization) are derived from these deviations. An alternative strategy could be to study deviations of network architectures from regular graphs (rings, lattices) and consider the implications of such deviations for self-organized dynamic patterns on the network. Following this strategy, we draw on the theory of spatiotemporal pattern formation and propose a novel perspective for analyzing dynamics on networks, by evaluating how the self-organized dynamics are confined by network architecture to a small set of permissible collective states. In particular, we discuss the role of prominent topological features of brain connectivity, such as hubs, modules and hierarchy, in shaping activity patterns. We illustrate the notion of network-guided pattern formation with numerical simulations and outline how it can facilitate the understanding of neural dynamics

Generalization of the noise model for time-distance helioseismology

In time-distance helioseismology, information about the solar interior is encoded in measurements of travel times between pairs of points on the solar surface. Travel times are deduced from the cross-covariance of the random wave field. Here we consider travel times and also products of travel times as observables. They contain information about e.g. the statistical properties of convection in the Sun. The basic assumption of the model is that noise is the result of the stochastic excitation of solar waves, a random process which is stationary and Gaussian. We generalize the existing noise model (Gizon and Birch 2004) by dropping the assumption of horizontal spatial homogeneity. Using a recurrence relation, we calculate the noise covariance matrices for the moments of order 4, 6, and 8 of the observed wave field, for the moments of order 2, 3 and 4 of the cross-covariance, and for the moments of order 2, 3 and 4 of the travel times. All noise covariance matrices depend only on the expectation value of the cross-covariance of the observed wave field. For products of travel times, the noise covariance matrix consists of three terms proportional to $1/T$, $1/T^2$, and $1/T^3$, where $T$ is the duration of the observations. For typical observation times of a few hours, the term proportional to $1/T^2$ dominates and $Cov[\tau_1 \tau_2, \tau_3 \tau_4] \approx Cov[\tau_1, \tau_3] Cov[\tau_2, \tau_4] + Cov[\tau_1, \tau_4] Cov[\tau_2, \tau_3]$, where the $\tau_i$ are arbitrary travel times. This result is confirmed for $p_1$ travel times by Monte Carlo simulations and comparisons with SDO/HMI observations. General and accurate formulae have been derived to model the noise covariance matrix of helioseismic travel times and products of travel times. These results could easily be generalized to other methods of local helioseismology, such as helioseismic holography and ring diagram analysis

Relation between directed polymers in random media and random bond dimer models

We reassess the relation between classical lattice dimer models and the continuum elastic description of a lattice of fluctuating polymers. In the absence of randomness we determine the density and line tension of the polymers in terms of the bond weights of hard-core dimers on the square and the hexagonal lattice. For the latter, we demonstrate the equivalence of the canonical ensemble for the dimer model and the grand-canonical description for polymers by performing explicitly the continuum limit. Using this equivalence for the random bond dimer model on a square lattice, we resolve a previously observed discrepancy between numerical results for the random dimer model and a replica approach for polymers in random media. Further potential applications of the equivalence are briefly discussed.Comment: 6 pages, 3 figure

Star formation and molecular hydrogen in dwarf galaxies: a non-equilibrium view

We study the connection of star formation to atomic (HI) and molecular hydrogen (H$_2$) in isolated, low metallicity dwarf galaxies with high-resolution ($m_{\rm gas}$ = 4 M$_\odot$, $N_{\rm ngb}$ = 100) SPH simulations. The model includes self-gravity, non-equilibrium cooling, shielding from an interstellar radiation field, the chemistry of H$_2$ formation, H$_2$-independent star formation, supernova feedback and metal enrichment. We find that the H$_2$ mass fraction is sensitive to the adopted dust-to-gas ratio and the strength of the interstellar radiation field, while the star formation rate is not. Star formation is regulated by stellar feedback, keeping the gas out of thermal equilibrium for densities $n <$ 1 cm$^{-3}$. Because of the long chemical timescales, the H$_2$ mass remains out of chemical equilibrium throughout the simulation. Star formation is well-correlated with cold ( T $\leqslant$ 100 K ) gas, but this dense and cold gas - the reservoir for star formation - is dominated by HI, not H$_2$. In addition, a significant fraction of H$_2$ resides in a diffuse, warm phase, which is not star-forming. The ISM is dominated by warm gas (100 K $<$ T $\leqslant 3\times 10^4$ K) both in mass and in volume. The scale height of the gaseous disc increases with radius while the cold gas is always confined to a thin layer in the mid-plane. The cold gas fraction is regulated by feedback at small radii and by the assumed radiation field at large radii. The decreasing cold gas fractions result in a rapid increase in depletion time (up to 100 Gyrs) for total gas surface densities $\Sigma_{\rm HI+H_2} \lesssim$ 10 M$_\odot$pc$^{-2}$, in agreement with observations of dwarf galaxies in the Kennicutt-Schmidt plane.Comment: Accepted for publication in MNRAS. Changes (including a pamameter study in Appendix C) highlighte