217 research outputs found

    Topologically protected quantum bits from Josephson junction arrays

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    All physical implementations of quantum bits (qubits), carrying the information and computation in a putative quantum computer, have to meet the conflicting requirements of environmental decoupling while remaining manipulable through designed external signals. Proposals based on quantum optics naturally emphasize the aspect of optimal isolation, while those following the solid state route exploit the variability and scalability of modern nanoscale fabrication techniques. Recently, various designs using superconducting structures have been successfully tested for quantum coherent operation, however, the ultimate goal of reaching coherent evolution over thousands of elementary operations remains a formidable task. Protecting qubits from decoherence by exploiting topological stability, a qualitatively new proposal due to Kitaev, holds the promise for long decoherence times, but its practical physical implementation has remained unclear so far. Here, we show how strongly correlated systems developing an isolated two-fold degenerate quantum dimer liquid groundstate can be used in the construction of topologically stable qubits and discuss their implementation using Josephson junction arrays.Comment: 6 pages, 4 figure

    The sign problem in Monte Carlo simulations of frustrated quantum spin systems

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    We discuss the sign problem arising in Monte Carlo simulations of frustrated quantum spin systems. We show that for a class of ``semi-frustrated'' systems (Heisenberg models with ferromagnetic couplings Jz(r)<0J_z(r) < 0 along the zz-axis and antiferromagnetic couplings Jxy(r)=Jz(r)J_{xy}(r)=-J_z(r) in the xyxy-plane, for arbitrary distances rr) the sign problem present for algorithms operating in the zz-basis can be solved within a recent ``operator-loop'' formulation of the stochastic series expansion method (a cluster algorithm for sampling the diagonal matrix elements of the power series expansion of exp(βH){\rm exp}(-\beta H) to all orders). The solution relies on identification of operator-loops which change the configuration sign when updated (``merons'') and is similar to the meron-cluster algorithm recently proposed by Chandrasekharan and Wiese for solving the sign problem for a class of fermion models (Phys. Rev. Lett. {\bf 83}, 3116 (1999)). Some important expectation values, e.g., the internal energy, can be evaluated in the subspace with no merons, where the weight function is positive definite. Calculations of other expectation values require sampling of configurations with only a small number of merons (typically zero or two), with an accompanying sign problem which is not serious. We also discuss problems which arise in applying the meron concept to more general quantum spin models with frustrated interactions.Comment: 13 pages, 16 figure

    Self-adapting method for the localization of quantum critical points using Quantum Monte Carlo techniques

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    A generalization to the quantum case of a recently introduced algorithm (Y. Tomita and Y. Okabe, Phys. Rev. Lett. {\bf 86}, 572 (2001)) for the determination of the critical temperature of classical spin models is proposed. We describe a simple method to automatically locate critical points in (Quantum) Monte Carlo simulations. The algorithm assumes the existence of a finite correlation length in at least one of the two phases surrounding the quantum critical point. We illustrate these ideas on the example of the critical inter-chain coupling for which coupled antiferromagnetic S=1 spin chains order at T=0. Finite-size scaling relations are used to determine the exponents, ν=0.72(2)\nu=0.72(2) and η=0.038(3)\eta=0.038(3) in agreement with previous estimates.Comment: 5 pages, 3 figures, published versio

    Computational Complexity in Electronic Structure

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    In quantum chemistry, the price paid by all known efficient model chemistries is either the truncation of the Hilbert space or uncontrolled approximations. Theoretical computer science suggests that these restrictions are not mere shortcomings of the algorithm designers and programmers but could stem from the inherent difficulty of simulating quantum systems. Extensions of computer science and information processing exploiting quantum mechanics has led to new ways of understanding the ultimate limitations of computational power. Interestingly, this perspective helps us understand widely used model chemistries in a new light. In this article, the fundamentals of computational complexity will be reviewed and motivated from the vantage point of chemistry. Then recent results from the computational complexity literature regarding common model chemistries including Hartree-Fock and density functional theory are discussed.Comment: 14 pages, 2 figures, 1 table. Comments welcom

    Vaccine candidates derived from a novel infectious cDNA clone of an American genotype dengue virus type 2

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    BACKGROUND: A dengue virus type 2 (DEN-2 Tonga/74) isolated from a 1974 epidemic was characterized by mild illness and belongs to the American genotype of DEN-2 viruses. To prepare a vaccine candidate, a previously described 30 nucleotide deletion (Δ30) in the 3' untranslated region of DEN-4 has been engineered into the DEN-2 isolate. METHODS: A full-length cDNA clone was generated from the DEN-2 virus and used to produce recombinant DEN-2 (rDEN-2) and rDEN2Δ30. Viruses were evaluated for replication in SCID mice transplanted with human hepatoma cells (SCID-HuH-7 mice), in mosquitoes, and in rhesus monkeys. Neutralizing antibody induction and protective efficacy were also assessed in rhesus monkeys. RESULTS: The rDEN2Δ30 virus was ten-fold reduced in replication in SCID-HuH-7 mice when compared to the parent virus. The rDEN-2 viruses were not infectious for Aedes mosquitoes, but both readily infected Toxorynchites mosquitoes. In rhesus monkeys, rDEN2Δ30 appeared to be slightly attenuated when compared to the parent virus as measured by duration and peak of viremia and neutralizing antibody induction. A derivative of rDEN2Δ30, designated rDEN2Δ30-4995, was generated by incorporation of a point mutation previously identified in the NS3 gene of DEN-4 and was found to be more attenuated than rDEN2Δ30 in SCID-HuH-7 mice. CONCLUSIONS: The rDEN2Δ30 and rDEN2Δ30-4995 viruses can be considered for evaluation in humans and for inclusion in a tetravalent dengue vaccine

    Computed Tomography Measurement of Rib Cage Morphometry in Emphysema

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    Background: Factors determining the shape of the human rib cage are not completely understood. We aimed to quantify the contribution of anthropometric and COPD-related changes to rib cage variability in adult cigarette smokers. Methods: Rib cage diameters and areas (calculated from the inner surface of the rib cage) in 816 smokers with or without COPD, were evaluated at three anatomical levels using computed tomography (CT). CTs were analyzed with software, which allows quantification of total emphysema (emphysema%). The relationship between rib cage measurements and anthropometric factors, lung function indices, and %emphysema were tested using linear regression models. Results: A model that included gender, age, BMI, emphysema%, forced expiratory volume in one second (FEV1)%, and forced vital capacity (FVC)% fit best with the rib cage measurements (R2  = 64% for the rib cage area variation at the lower anatomical level). Gender had the biggest impact on rib cage diameter and area (105.3 cm2; 95% CI: 111.7 to 98.8 for male lower area). Emphysema% was responsible for an increase in size of upper and middle CT areas (up to 5.4 cm2; 95% CI: 3.0 to 7.8 for an emphysema increase of 5%). Lower rib cage areas decreased as FVC% decreased (5.1 cm2; 95% CI: 2.5 to 7.6 for 10 percentage points of FVC variation). Conclusions: This study demonstrates that simple CT measurements can predict rib cage morphometric variability and also highlight relationships between rib cage morphometry and emphysema

    Maintenance of the pectoralis muscle during hibernation in the big brown bat, Eptesicus fuscus

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    The relationship between pectoralis muscle mass and body mass is examined throughout the annual body mass cycle in Eptesicus fuscus in order to evaluate muscle maintenance during hibernation. E. fuscus undergoes large fluctuations in body mass during the year due to pregnancy, parturition, prehibernation fattening, and hibernation (Table 1). Parallel changes occur in pectoralis muscle mass and total pectoralis protein mass (Table 2). The strong correlation between log pectoralis mass and log body mass (Fig. 3) and the lack of correlation between pectoralis mass and forearm length (Fig. 1, 2) suggest that the seasonal variation in pectoralis muscle mass represents a compensatory response to changing body mass. In active bats this relationship closely resembles the compensatory response predicted by flight theory.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47128/1/360_2004_Article_BF00689733.pd

    Detecting Subtle Changes in Visuospatial Executive Function and Learning in the Amnestic Variant of Mild Cognitive Impairment

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    BACKGROUND AND PURPOSE: Amnestic mild cognitive impairment (aMCI) is a putative prodromal stage of Alzheimer's disease (AD) characterized by deficits in episodic verbal memory. Our goal in the present study was to determine whether executive dysfunction may also be detectable in individuals diagnosed with aMCI. METHODS: This study used a hidden maze learning test to characterize component processes of visuospatial executive function and learning in a sample of 62 individuals with aMCI compared with 94 healthy controls. RESULTS: Relative to controls, individuals with aMCI made more exploratory/learning errors (Cohen's d = .41). Comparison of learning curves revealed that the slope between the first two of five learning trials was four times as steep for controls than for individuals with aMCI (Cohen's d = .64). Individuals with aMCI also made a significantly greater number of rule-break/error monitoring errors across learning trials (Cohen's d = .21). CONCLUSIONS: These results suggest that performance on a task of complex visuospatial executive function is compromised in individuals with aMCI, and likely explained by reductions in initial strategy formulation during early visual learning and "on-line" maintenance of task rules

    Using Dynamic Stochastic Modelling to Estimate Population Risk Factors in Infectious Disease: The Example of FIV in 15 Cat Populations

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    BACKGROUND:In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS:To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION:Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease

    Apc Mutation Enhances PyMT-Induced Mammary Tumorigenesis

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    The Adenomatous Polyposis Coli (APC) tumor suppressor gene is silenced by hypermethylation or mutated in up to 70% of human breast cancers. In mouse models, Apc mutation disrupts normal mammary development and predisposes to mammary tumor formation; however, the cooperation between APC and other mutations in breast tumorigenesis has not been studied. To test the hypothesis that loss of one copy of APC promotes oncogene-mediated mammary tumorigenesis, ApcMin/+ mice were crossed with the mouse mammary tumor virus (MMTV)-Polyoma virus middle T antigen (PyMT) or MMTV-c-Neu transgenic mice. In the PyMT tumor model, the ApcMin/+ mutation significantly decreased survival and tumor latency, promoted a squamous adenocarcinoma phenotype, and enhanced tumor cell proliferation. In tumor-derived cell lines, the proliferative advantage was a result of increased FAK, Src and JNK signaling. These effects were specific to the PyMT model, as no changes were observed in MMTV-c-Neu mice carrying the ApcMin/+ mutation. Our data indicate that heterozygosity of Apc enhances tumor development in an oncogene-specific manner, providing evidence that APC-dependent pathways may be valuable therapeutic targets in breast cancer. Moreover, these preclinical model systems offer a platform for dissection of the molecular mechanisms by which APC mutation enhances breast carcinogenesis, such as altered FAK/Src/JNK signaling
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