Fast emergency paths schema to overcome transient link failures in ospf routing

A reliable network infrastructure must be able to sustain traffic flows, even when a failure occurs and changes the network topology. During the occurrence of a failure, routing protocols, like OSPF, take from hundreds of milliseconds to various seconds in order to converge. During this convergence period, packets might traverse a longer path or even a loop. An even worse transient behaviour is that packets are dropped even though destinations are reachable. In this context, this paper describes a proactive fast rerouting approach, named Fast Emergency Paths Schema (FEP-S), to overcome problems originating from transient link failures in OSPF routing. Extensive experiments were done using several network topologies with different dimensionality degrees. Results show that the recovery paths, obtained by FEPS, are shorter than those from other rerouting approaches and can improve the network reliability by reducing the packet loss rate during the routing protocols convergence caused by a failure.Comment: 18 page

Scaling and balancing carbon dioxide fluxes in a heterogeneous tundra ecosystem of the Lena River Delta

The current assessments of the carbon turnover in the Arctic tundra are subject to large uncertainties. This problem can (inter alia) be ascribed to both the general shortage of flux data from the vast and sparsely inhabited Arctic region, as well as the typically high spatiotemporal variability of carbon fluxes in tundra ecosystems. Addressing these challenges, carbon dioxide fluxes on an active flood plain situated in the Siberian Lena River Delta were studied during two growing seasons with the eddy covariance method. The footprint exhibited a heterogeneous surface, which generated mixed flux signals that could be partitioned in such a way that both respiratory loss and photosynthetic gain were obtained for each of two vegetation classes. This downscaling of the observed fluxes revealed a differing seasonality in the net uptake of bushes (−0.89 µmol m−2 s−1) and sedges (−0.38 µmol mm−2 s−1) in 2014. That discrepancy, which was concealed in the net signal, resulted from a comparatively warm spring in conjunction with an early snowmelt and a varying canopy structure. Thus, the representativeness of footprints may adversely be affected in response to prolonged unusual weather conditions. In 2015, when air temperatures on average corresponded to climatological means, both vegetation-class-specific flux rates were of similar magnitude (−0.69 µmol m−2 s−1). A comprehensive set of measures (e.g. phenocam) corroborated the reliability of the partitioned fluxes and hence confirmed the utility of flux decomposition for enhanced flux data analysis. This scrutiny encompassed insights into both the phenological dynamic of individual vegetation classes and their respective functional flux to flux driver relationships with the aid of ecophysiologically interpretable parameters. For comparison with other sites, the decomposed fluxes were employed in a vegetation class area-weighted upscaling that was based on a classified high-resolution orthomosaic of the flood plain. In this way, robust budgets that take the heterogeneous surface characteristics into account were estimated. In relation to the average sink strength of various Arctic flux sites, the flood plain constitutes a distinctly stronger carbon dioxide sink. Roughly 42 % of this net uptake, however, was on average offset by methane emissions lowering the sink strength for greenhouse gases. With growing concern about rising greenhouse gas emissions in high-latitude regions, providing robust carbon budgets from tundra ecosystems is critical in view of accelerating permafrost thaw, which can impact the global climate for centuries

Evolutionary descent of prion genes from a ZIP metal ion transport ancestor

In the more than 20 years since its discovery, both the phylogenetic origin and cellular function of the prion protein (PrP) have remained enigmatic. Insights into the function of PrP may be obtained through a characterization of its molecular neighborhood. Quantitative interactome data revealed the spatial proximity of a subset of metal ion transporters of the ZIP family to mammalian prion proteins. A subsequent bioinformatic analysis revealed the presence of a prion-like protein sequence within the N-terminal, extracellular domain of a phylogenetic branch of ZIPs. Additional structural threading and ortholog sequence alignment analyses consolidated the conclusion that the prion protein gene family is phylogenetically derived from a ZIP-like ancestor molecule. Our data explain structural and functional features found within mammalian prion proteins as elements of an ancient involvement in the transmembrane transport of divalent cations. The connection to ZIP proteins is expected to open new avenues to elucidate the biology of the prion protein in health and disease

From Heredity to Genetics: Political, Medical, and Agro-Industrial Contexts

Book Chapte

Localization of bosonic atoms by fermionic impurities in a 3d optical lattice

We observe a localized phase of ultracold bosonic quantum gases in a 3-dimensional optical lattice induced by a small contribution of fermionic atoms acting as impurities in a Fermi-Bose quantum gas mixture. In particular we study the dependence of this transition on the fermionic 40K impurity concentration by a comparison to the corresponding superfluid to Mott insulator transition in a pure bosonic 87Rb gas and find a significant shift in the transition parameter. The observed shift is larger than expected based on a mean-field argument, which is a strong indication that disorder-related effects play a significant role.Comment: 4 pages, 4 figure

Fermionic topological quantum states as tensor networks

Tensor network states, and in particular projected entangled pair states, play an important role in the description of strongly correlated quantum lattice systems. They do not only serve as variational states in numerical simulation methods, but also provide a framework for classifying phases of quantum matter and capture notions of topological order in a stringent and rigorous language. The rapid development in this field for spin models and bosonic systems has not yet been mirrored by an analogous development for fermionic models. In this work, we introduce a tensor network formalism capable of capturing notions of topological order for quantum systems with fermionic components. At the heart of the formalism are axioms of fermionic matrix-product operator injectivity, stable under concatenation. Building upon that, we formulate a Grassmann number tensor network ansatz for the ground state of fermionic twisted quantum double models. A specific focus is put on the paradigmatic example of the fermionic toric code. This work shows that the program of describing topologically ordered systems using tensor networks carries over to fermionic models

An ASP Approach for the Synthesis of CNOT Minimal Quantum Circuits

In the last year, physical working Quantum Computers have been built and made available for the end users. Such devices, working under the rules of Quantum Mechanics, can only apply a finite set of one/two qubit operations that form a universal set of gates. Single qubit gates are fault-tolerant, while the same cannot be said for two qubit gates. Hence, unitary matrices adopted in Quantum Algorithms must be synthesized in terms of this universal set of operations to obtain a quantum circuit. This synthesis procedure, however, is not constraint-free. In fact, we prefer circuits with minimum number of qubits and with minimum circuit depth. Clifford+T universal set is one of the most adopted in the literature for synthesis. In such set we have 3 single qubit gates and the CNOT, which is a two qubit gate. Many efforts have been directed to devise algorithms that synthesize general unitary matrices into Clifford+T circuits. These algorithms usually tend to optimize circuit depth or eventually the number of T gates. Since two qubit gates are not fault tolerant, in this work we propose an ASP based technique to minimize the number of CNOT gates inside a Clifford+T circuit. We start from a SAT encoding of the problem, and we translate it into an ASP model over a graph, by first working with a generic graph, and then by adopting the structure of a layered DAG. We provide experimental evidence of the scalability of our proposal

A unified diagrammatic approach to topological fixed point models

We introduce a systematic mathematical language for describing fixed point models and apply it to the study to topological phases of matter. The framework established is reminiscent to that of state-sum models and lattice topological quantum field theories, but is formalized and unified in terms of tensor networks. In contrast to existing tensor network ansatzes for the study of ground states of topologically ordered phases, the tensor networks in our formalism directly represent discrete path integrals in Euclidean space-time. This language is more immediately related to the Hamiltonian defining the model than other approaches, via a Trotterization of the respective imaginary time evolution. We illustrate our formalism at hand of simple examples, and demonstrate its full power by expressing known families of models in 2+1 dimensions in their most general form, namely string-net models and Kitaev quantum doubles based on weak Hopf algebras. To elucidate the versatility of our formalism, we also show how fermionic phases of matter can be described and provide a framework for topological fixed point models in 3+1 dimensions.Comment: 86 pages and many diagrams, small change