Topological massive Dirac edge modes and long-range superconducting Hamiltonians

We discover novel topological effects in the one-dimensional Kitaev chain modified by long-range Hamiltonian deformations in the hopping and pairing terms. This class of models display symmetry-protected topological order measured by the Berry/Zak phase of the lower-band eigenvector and the winding number of the Hamiltonians. For exponentially decaying hopping amplitudes, the topological sector can be significantly augmented as the penetration length increases, something experimentally achievable. For power-law decaying superconducting pairings, the massless Majorana modes at the edges get paired together into a massive nonlocal Dirac fermion localized at both edges of the chain: a new topological quasiparticle that we call topological massive Dirac fermion. This topological phase has fractional topological numbers as a consequence of the long-range couplings. Possible applications to current experimental setups and topological quantum computation are also discussed.

Electrical AC behaviour of MPCVD diamond Schottky diodes

The present work reports some experimental results on the electrical AC behaviour of metal-undoped diamond Schottky diodes fabricated with a free-standing MPCVD diamond film (5 mum thick). The metals are gold for the ohmic contact and aluminium for the rectifier. The capacitance and loss tangent vs, frequency shows that capacitance presents a relaxation maximum at frequencies near 10 kHz at room temperature. Although the simple model (small equivalent circuit) can justify the values for the relaxation, it cannot justify the departure from the Debye model, also verified in the Cole-Cole plot. Taking into account the existence of traps in the depletion region, a best fit to the experimental results was obtained. The difference between the Fermi level and the band edge of 0.2-0.3 eV is in agreement with the activation energy found from the loss tangent analysis. The capacitance with applied voltage (Mott-Schottky plots) gives a defect density of 10(16) cm(-3) with contact potentials near 0.5 V and the profile of defect density obtained shows a major density (approx. 10(17) cm(-3)) in a layer with a thickness less than 50 nm from the junction, decreasing by one order of magnitude with increasing distance. Finally a structural model is proposed to explain the AC behaviour found. (C) 2001 Elsevier Science B.V. All rights reserved.

Edge centrality via the Holevo quantity

In the study of complex networks, vertex centrality measures are used to identify the most important vertices within a graph. A related problem is that of measuring the centrality of an edge. In this paper, we propose a novel edge centrality index rooted in quantum information. More specifically, we measure the importance of an edge in terms of the contribution that it gives to the Von Neumann entropy of the graph. We show that this can be computed in terms of the Holevo quantity, a well known quantum information theoretical measure. While computing the Von Neumann entropy and hence the Holevo quantity requires computing the spectrum of the graph Laplacian, we show how to obtain a simplified measure through a quadratic approximation of the Shannon entropy. This in turns shows that the proposed centrality measure is strongly correlated with the negative degree centrality on the line graph. We evaluate our centrality measure through an extensive set of experiments on real-world as well as synthetic networks, and we compare it against commonly used alternative measures.

Adaptive edge analytics for distributed networked control of water systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

On the Bleeding Edge : Debloating Internet Access Networks

As ever more devices are connected to the internet, and applications turn ever more interactive, it becomes more important that the network can be counted on to respond reliably and without unnecessary delay. However, this is far from always the case today, as there can be many potential sources of unnecessary delay. In this thesis we focus on one of them: Excess queueing delay in network routers along the path, also known as bufferbloat. We focus on the home network, and treat the issue in three stages. We examine latency variation and queueing delay on the public internet and show that significant excess delay is often present. Then, we evaluate several modern AQM algorithms and packet schedulers in a residential setting, and show that modern AQMs can almost entirely eliminate bufferbloat and extra queueing latency for wired connections, but that they are not as effective for WiFi links. Finally, we go on to design and implement a solution for bufferbloat at the WiFi link, and also design a workable scheduler-based solution for realising airtime fairness in WiFi. Also included in this thesis is a description of Flent, a measurement tool used to perform most of the experiments in the other papers, and also used widely in the bufferbloat community.

Edge enhancement improves disruptive camouflage by emphasising false edges and creating pictorial relief

Disruptive colouration is a visual camouflage composed of false edges and boundaries. Many disruptively camouflaged animals feature enhanced edges; light patches are surrounded by a lighter outline and/or a dark patches are surrounded by a darker outline. This camouflage is particularly common in amphibians, reptiles and lepidopterans. We explored the role that this pattern has in creating effective camouflage. In a visual search task utilising an ultra-large display area mimicking search tasks that might be found in nature, edge enhanced disruptive camouflage increases crypsis, even on substrates that do not provide an obvious visual match. Specifically, edge enhanced camouflage is effective on backgrounds both with and without shadows; i.e. this is not solely due to background matching of the dark edge enhancement element with the shadows. Furthermore, when the dark component of the edge enhancement is omitted the camouflage still provided better crypsis than control patterns without edge enhancement. This kind of edge enhancement improved camouflage on all background types. Lastly, we show that edge enhancement can create a perception of multiple surfaces. We conclude that edge enhancement increases the effectiveness of disruptive camouflage through mechanisms that may include the improved disruption of the object outline by implying pictorial relief.