Quantum Computing with Atomic Josephson Junction Arrays

We present a quantum computing scheme with atomic Josephson junction arrays. The system consists of a small number of atoms with three internal states and trapped in a far-off resonant optical lattice. Raman lasers provide the "Josephson" tunneling, and the collision interaction between atoms represent the "capacitive" couplings between the modes. The qubit states are collective states of the atoms with opposite persistent currents. This system is closely analogous to the superconducting flux qubit. Single qubit quantum logic gates are performed by modulating the Raman couplings, while two-qubit gates result from a tunnel coupling between neighboring wells. Readout is achieved by tuning the Raman coupling adiabatically between the Josephson regime to the Rabi regime, followed by a detection of atoms in internal electronic states. Decoherence mechanisms are studied in detail promising a high ratio between the decoherence time and the gate operation time.Comment: 7 figure

Single and double qubit gates by manipulating degeneracy

A novel mechanism is proposed for single and double qubit state manipulations in quantum computation with four-fold degenerate energy levels. The principle is based on starting with a four fold degeneracy, lifting it stepwise adiabatically by a set of control parameters and performing the quantum gate operations on non-degenerate states. A particular realization of the proposed mechanism is suggested by using inductively coupled rf-squid loops in the macroscopic quantum tunnelling regime where the energy eigen levels are directly connected with the measurable flux states. The one qubit and two qubit controlled operations are demonstrated explicitly. The appearance of the flux states also allows precise read-in and read-out operations by the measurement of flux.Comment: 6 pages + 5 figures (separately included

Reduced tubulin tyrosination as an early marker of mercury toxicity in differentiating N2a cells

The aims of this work were to compare the effects of methyl mercury chloride and Thimerosal on neurite/process outgrowth and microtubule proteins in differentiating mouse N2a neuroblastoma and rat C6 glioma cells. Exposure for 4 h to sublethal concentrations of both compounds inhibited neurite outgrowth to a similar extent in both cells lines compared to controls. In the case of N2a cells, this inhibitory effect by both compounds was associated with a fall in the reactivity of western blots of cell extracts with monoclonal antibody T1A2, which recognises C-terminally tyrosinated α-tubulin. By contrast, reactivity with monoclonal antibody B512 (which recognises total α-tubulin) was unaffected at the same time point. These findings suggest that decreased tubulin tyrosination represents a neuron-specific early marker of mercury toxicity associated with impaired neurite outgrowth

Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong

We applied cartographic and geostatistical methods in analyzing the patterns of disease spread during the 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong using geographic information system (GIS) technology. We analyzed an integrated database that contained clinical and personal details on all 1,755 patients confirmed to have SARS from 15 February to 22 June 2003. Elementary mapping of disease occurrences in space and time simultaneously revealed the geographic extent of spread throughout the territory. Statistical surfaces created by the kernel method confirmed that SARS cases were highly clustered and identified distinct disease “hot spots.” Contextual analysis of mean and standard deviation of different density classes indicated that the period from day 1 (18 February) through day 16 (6 March) was the prodrome of the epidemic, whereas days 86 (15 May) to 106 (4 June) marked the declining phase of the outbreak. Origin-and-destination plots showed the directional bias and radius of spread of superspreading events. Integration of GIS technology into routine field epidemiologic surveillance can offer a real-time quantitative method for identifying and tracking the geospatial spread of infectious diseases, as our experience with SARS has demonstrated

Modelling basin-wide variations in Amazon forest productivity - Part 1: Model calibration, evaluation and upscaling functions for canopy photosynthesis

No abstract available

Emergence of influential spreaders in modified rumor models

The burst in the use of online social networks over the last decade has provided evidence that current rumor spreading models miss some fundamental ingredients in order to reproduce how information is disseminated. In particular, recent literature has revealed that these models fail to reproduce the fact that some nodes in a network have an influential role when it comes to spread a piece of information. In this work, we introduce two mechanisms with the aim of filling the gap between theoretical and experimental results. The first model introduces the assumption that spreaders are not always active whereas the second model considers the possibility that an ignorant is not interested in spreading the rumor. In both cases, results from numerical simulations show a higher adhesion to real data than classical rumor spreading models. Our results shed some light on the mechanisms underlying the spreading of information and ideas in large social systems and pave the way for more realistic diffusion models.Comment: 14 Pages, 6 figures, accepted for publication in Journal of Statistical Physic