From Majorana Fermions to Topological Order

We consider a system consisting of a 2D network of links between Majorana fermions on superconducting islands. We show that the fermionic Hamiltonian modeling this system is topologically-ordered in a region of parameter space. In particular we show that Kitaev's toric code emerges in fourth-order perturbation theory. By using a Jordan-Wigner transformation we can map the model onto a family of signed 2D Ising models in a transverse field where the signs (FM or AFM) are determined by additional gauge bits. Our mapping allows an understanding of the non-perturbative regime and the phase transition to a non-topological phase. We discuss the physics behind a possible implementation of this model and argue how it can be used for topological quantum computation by adiabatic changes in the Hamiltonian.Comment: 4+4 pages, 5 figures. v2 has a new reference and a few new comments. In v3: yet another new reference and Supplementary Material is renamed Appendix. In v4: several typos are corrected, to appear in Phys. Rev. Let

Dessins, their delta-matroids and partial duals

Given a map $\mathcal M$ on a connected and closed orientable surface, the delta-matroid of $\mathcal M$ is a combinatorial object associated to $\mathcal M$ which captures some topological information of the embedding. We explore how delta-matroids associated to dessins d'enfants behave under the action of the absolute Galois group. Twists of delta-matroids are considered as well; they correspond to the recently introduced operation of partial duality of maps. Furthermore, we prove that every map has a partial dual defined over its field of moduli. A relationship between dessins, partial duals and tropical curves arising from the cartography groups of dessins is observed as well.Comment: 34 pages, 20 figures. Accepted for publication in the SIGMAP14 Conference Proceeding

What is known about the health and living conditions of the indigenous people of northern Scandinavia, the Sami?

The Sami are the indigenous ethnic population of northern Scandinavia. Their health condition is poorly known, although the knowledge has improved over the last decade.The aim was to review the current information on mortality, diseases, and risk factor exposure in the Swedish Sami population.Health-related research on Sami cohorts published in scientific journals and anthologies was used to compare the health condition among the Sami and the majority non-Sami population. When relevant, data from the Sami populations in Swedish were compared with corresponding data from Norwegian and Finnish Sami populations.Life expectancy and mortality patterns of the Sami are similar to those of the majority population. Small differences in incidences of cancer and cardiovascular diseases have been reported. The traditional Sami lifestyle seems to contain elements that reduce the risk to develop cancer and cardiovascular diseases, e.g. physical activity, diet rich in antioxidants and unsaturated fatty acids, and a strong cultural identity. Reindeer herding is an important cultural activity among the Sami and is associated with high risks for accidents. Pain in the lower back, neck, shoulders, elbows, and hands are frequent among both men and women in reindeer-herding families. For men, these symptoms are related to high exposure to terrain vehicles, particularly snowmobile, whereas for women psychosocial risk factors seem to more important, e.g. poor social support, high effort, low reward, and high economical responsibilities.Although the health condition of the Sami population appears to be rather similar to that of the general Swedish population, a number of specific health problems have been identified, especially among the reindeer-herding Sami. Most of these problems have their origin in marginalization and poor knowledge of the reindeer husbandry and the Sami culture in the majority population. It is suggested that the most sustainable measure to improve the health among the reindeer-herding Sami would be to improve the conditions of the reindeer husbandry and the Sami culture

The impact of iron limitation on the physiology of the Antarctic diatom Chaetoceros simplex

Iron availability strongly governs the growth of Southern Ocean phytoplankton. To investigate how iron limitation affects photosynthesis as well as the uptake of carbon and iron in the Antarctic diatom Chaetoceros simplex, a combination of chlorophyll a fluorescence measurements and radiotracer incubations in the presence and absence of chemical inhibitors was conducted. Iron limitation in C. simplex led to a decline in growth rates, photochemical efficiency and structural changes in photosystem II (PSII), including a reorganisation of photosynthetic units in PSII and an increase in size of the functional absorption cross section of PSII. Iron-limited cells further exhibited a reduced plastoquinone pool and decreased photosynthetic electron transport rate, while non-photochemical quenching and relative xanthophyll pigment content were strongly increased, suggesting a photoprotective response. Additionally, iron limitation resulted in a strong decline in carbon fixation and thus the particulate organic carbon quotas. Inhibitor studies demonstrated that, independent of the iron supply, carbon fixation was dependent on internal, but not on extracellular carbonic anhydrase activity. Orthovanadate more strongly inhibited iron uptake in iron-limited cells, indicating that P-type ATPase transporters are involved in iron uptake. The stronger reduction in iron uptake by ascorbate in iron-limited cells suggests that the re-oxidation of iron is required before it can be taken up and further supports the presence of a high-affinity iron transport pathway. The measured changes to photosystem architecture and shifts in carbon and iron uptake strategies in C. simplex as a result of iron limitation provide evidence for a complex interaction of these processes to balance the iron requirements for photosynthesis and carbon demand for sustained growth in iron-limited waters. © 2014 The Author(s)

Full counting statistics for noninteracting fermions: Joint probability distributions

The joint probability distribution in the full counting statistics (FCS) for noninteracting electrons is discussed for an arbitrary number of initially separate subsystems which are connected at t=0 and separated at a later time. A simple method to obtain the leading order long time contribution to the logarithm of the characteristic function is presented which simplifies earlier approaches. New explicit results for the determinant involving the scattering matrices are found. The joint probability distribution for two leads is discussed for Y-junctions and dots connected to four leads.Comment: 17 pages, 3 figure

Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates

Sap flow encodes information about how plants regulate the opening and closing of stomata in response to varying soil water supply and atmospheric water demand. This study leverages this valuable information with model–data integration and deep learning to estimate canopy conductance in a hybrid catchment-scale model for more accurate hydrological simulations. Using data from three consecutive growing seasons, we first highlight that integrating canopy conductance inferred from sap flow data in a hydrological model leads to more realistic soil moisture estimates than using the conventional Jarvis–Stewart equation, particularly during drought conditions. The applicability of this first approach is, however, limited to the period where sap flow data are available. To overcome this limitation, we subsequently train a recurrent neural network (RNN) to predict catchment-averaged sap velocities based on standard hourly meteorological data. These simulated velocities are then used to estimate canopy conductance, allowing simulations for periods without sap flow data. We show that the hybrid model, which uses the canopy conductance from the machine learning (ML) approach, matches soil moisture and transpiration equally as well as model runs using observed sap flow data and has good potential for extrapolation beyond the study site. We conclude that such hybrid approaches open promising avenues for parametrizations of complex water–plant dynamics by improving our ability to incorporate novel or untypical data sets into hydrological models

Full counting statistics for noninteracting fermions: Exact finite temperature results and generalized long time approximation

Exact numerical results for the full counting statistics (FCS) of a one-dimensional tight-binding model of noninteracting electrons are presented at finite temperatures using an identity recently presented by Abanov and Ivanov. A similar idea is used to derive a new expression for the cumulant generating function for a system consisting of two quasi-one-dimensional leads connected by a quantum dot in the long time limit. This provides a generalization of the Levitov-Lesovik formula for such systems.Comment: 17 pages, 6 figures, extended introduction, additional comment

Estimates of tree root water uptake from soil moisture profile dynamics

Root water uptake (RWU), as an important process in the terrestrial water cycle, can help us to better understand the interactions in the soil–plant–atmosphere continuum. We conducted a field study monitoring soil moisture profiles in the rhizosphere of beech trees at two sites with different soil conditions. We present an algorithm to infer RWU from step-shaped, diurnal changes in soil moisture. While this approach is a feasible, easily implemented method for moderately moist and homogeneously textured soil conditions, limitations were identified during drier states and for more heterogeneous soil settings. A comparison with the time series of xylem sap velocity underlines that RWU and sap flow (SF) are complementary measures in the transpiration process. The high correlation between the SF time series of the two sites, but lower correlation between the RWU time series, suggests that soil characteristics affect RWU of the trees but not SF

Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates

Sap flow encodes information about how plants regulate the opening and closing of stomata in response to varying soil water supply and atmospheric water demand. This study leverages this valuable information with model- data integration and deep learning to estimate canopy conductance in a hybrid catchment-scale model for more accurate hydrological simulations. Using data from three consecutive growing seasons, we first highlight that integrating canopy conductance inferred from sap flow data in a hydrological model leads to more realistic soil moisture estimates than using the conventional Jarvis-Stewart equation, particularly during drought conditions. The applicability of this first approach is, however, limited to the period where sap flow data are available. To overcome this limitation, we subsequently train a recurrent neural network (RNN) to predict catchment-averaged sap velocities based on standard hourly meteorological data. These simulated velocities are then used to estimate canopy conductance, allowing simulations for periods without sap flow data. We show that the hybrid model, which uses the canopy conductance from the machine learning (ML) approach, matches soil moisture and transpiration equally as well as model runs using observed sap flow data and has good potential for extrapolation beyond the study site. We conclude that such hybrid approaches open promising avenues for parametrizations of complex water-plant dynamics by improving our ability to incorporate novel or untypical data sets into hydrological models