Low-energy electronic properties of clean CaRuO$_3$: elusive Landau quasiparticles

We have prepared high-quality epitaxial thin films of CaRuO$_3$ with residual resistivity ratios up to 55. Shubnikov-de Haas oscillations in the magnetoresistance and a $T^2$ temperature dependence in the electrical resistivity only below 1.5 K, whose coefficient is substantially suppressed in large magnetic fields, establish CaRuO$_3$ as a Fermi liquid (FL) with anomalously low coherence scale. Non-Fermi liquid (NFL) $T^{3/2}$ dependence is found between 2 and 25 K. The high sample quality allows access to the intrinsic electronic properties via THz spectroscopy. For frequencies below 0.6 THz, the conductivity is Drude-like and can be modeled by FL concepts, while for higher frequencies non-Drude behavior, inconsistent with FL predictions, is found. This establishes CaRuO$_3$ as a prime example of optical NFL behavior in the THz range.

Arrays of open, independently tunable microcavities

Optical cavities are of central importance in numerous areas of physics, including precision measurement, cavity optomechanics and cavity quantum electrodynamics. The miniaturisation and scaling to large numbers of sites is of interest for many of these applications, in particular for quantum computation and simulation. Here we present the first scaled microcavity system which enables the creation of large numbers of highly uniform, tunable light-matter interfaces using ions, neutral atoms or solid-state qubits. The microcavities are created by means of silicon micro-fabrication, are coupled directly to optical fibres and can be independently tuned to the chosen frequency, paving the way for arbitrarily large networks of optical microcavities.

Studying edge geometry in transiently turbulent shear flows

In linearly stable shear flows at moderate Re, turbulence spontaneously decays despite the existence of a codimension-one manifold, termed the edge of chaos, which separates decaying perturbations from those triggering turbulence. We statistically analyse the decay in plane Couette flow, quantify the breaking of self-sustaining feedback loops and demonstrate the existence of a whole continuum of possible decay paths. Drawing parallels with low-dimensional models and monitoring the location of the edge relative to decaying trajectories we provide evidence, that the edge of chaos separates state space not globally. It is instead wrapped around the turbulence generating structures and not an independent dynamical structure but part of the chaotic saddle. Thereby, decaying trajectories need not cross the edge, but circumnavigate it while unwrapping from the turbulent saddle.

Efficient algorithm to study interconnected networks

Interconnected networks have been shown to be much more vulnerable to random and targeted failures than isolated ones, raising several interesting questions regarding the identification and mitigation of their risk. The paradigm to address these questions is the percolation model, where the resilience of the system is quantified by the dependence of the size of the largest cluster on the number of failures. Numerically, the major challenge is the identification of this cluster and the calculation of its size. Here, we propose an efficient algorithm to tackle this problem. We show that the algorithm scales as O(N log N), where N is the number of nodes in the network, a significant improvement compared to O(N^2) for a greedy algorithm, what permits studying much larger networks. Our new strategy can be applied to any network topology and distribution of interdependencies, as well as any sequence of failures.

Optimal box-covering algorithm for fractal dimension of complex networks

The self-similarity of complex networks is typically investigated through computational algorithms the primary task of which is to cover the structure with a minimal number of boxes. Here we introduce a box-covering algorithm that not only outperforms previous ones, but also finds optimal solutions. For the two benchmark cases tested, namely, the E. Coli and the WWW networks, our results show that the improvement can be rather substantial, reaching up to 15% in the case of the WWW network.

Using the de Haas-van Alphen effect to map out the closed three-dimensional Fermi surface of natural graphite

The Fermi surface of graphite has been mapped out using de Haas van Alphen (dHvA) measurements at low temperature with in-situ rotation. For tilt angles $theta>60^{circ}$ between the magnetic field and the c-axis, the majority electron and hole dHvA periods no longer follow the $cos(theta)$ behavior demonstrating that graphite has a 3 dimensional closed Fermi surface. The Fermi surface of graphite is accurately described by highly elongated ellipsoids. A comparison with the calculated Fermi surface suggests that the SWM trigonal warping parameter $gamma_3$ is significantly larger than previously thought.

Towards designing robust coupled networks

Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy.

Snakes and ladders: localized solutions of plane Couette flow

We demonstrate the existence of a large number of exact solutions of plane Couette flow, which share the topology of known periodic solutions but are localized in space. Solutions of different size are organized in a snakes-and-ladders structure strikingly similar to that observed for simpler pattern-forming PDE systems. These new solutions are a step towards extending the dynamical systems view of transitional turbulence to spatially extended flows.

Network structure determines patterns of network reorganization during adult neurogenesis

New cells are generated throughout life and integrate into the hippocampus via the process of adult neurogenesis. Epileptogenic brain injury induces many structural changes in the hippocampus, including the death of interneurons and altered connectivity patterns. The pathological neurogenic niche is associated with aberrant neurogenesis, though the role of the network-level changes in development of epilepsy is not well understood. In this paper, we use computational simulations to investigate the effect of network environment on structural and functional outcomes of neurogenesis. We find that small-world networks with external stimulus are able to be augmented by activity-seeking neurons in a manner that enhances activity at the stimulated sites without altering the network as a whole. However, when inhibition is decreased or connectivity patterns are changed, new cells are both less responsive to stimulus and the new cells are more likely to drive the network into bursting dynamics. Our results suggest that network-level changes caused by epileptogenic injury can create an environment where neurogenic reorganization can induce or intensify epileptic dynamics and abnormal integration of new cells.

Pattern Formation of Glioma Cells: Effects of Adhesion

We investigate clustering of malignant glioma cells. emph{In vitro} experiments in collagen gels identified a cell line that formed clusters in a region of low cell density, whereas a very similar cell line (which lacks an important mutation) did not cluster significantly. We hypothesize that the mutation affects the strength of cell-cell adhesion. We investigate this effect in a new experiment, which follows the clustering dynamics of glioma cells on a surface. We interpret our results in terms of a stochastic model and identify two mechanisms of clustering. First, there is a critical value of the strength of adhesion; above the threshold, large clusters grow from a homogeneous suspension of cells; below it, the system remains homogeneous, similarly to the ordinary phase separation. Second, when cells form a cluster, we have evidence that they increase their proliferation rate. We have successfully reproduced the experimental findings and found that both mechanisms are crucial for cluster formation and growth.