Demonstrating anyonic fractional statistics with a six-qubit quantum simulator

Anyons are exotic quasiparticles living in two dimensions that do not fit into the usual categories of fermions and bosons, but obey a new form of fractional statistics. Following a recent proposal [Phys. Rev. Lett. 98, 150404 (2007)], we present an experimental demonstration of the fractional statistics of anyons in the Kitaev spin lattice model using a photonic quantum simulator. We dynamically create the ground state and excited states (which are six-qubit graph states) of the Kitaev model Hamiltonian, and implement the anyonic braiding and fusion operations by single-qubit rotations. A phase shift of $\pi$ related to the anyon braiding is observed, confirming the prediction of the fractional statistics of Abelian 1/2-anyons.Comment: revised version 3, revTex, 4.3 pages, 4 figures, notes and reference adde

Greenberger-Horne-Zeilinger-type violation of local realism by mixed states

Cluster states are multi-particle entangled states with special entanglement properties particularly suitable for quantum computation. It has been shown that cluster states can exhibit Greenberger-Horne-Zeilinger (GHZ)-type non-locality even when some of their qubits have been lost. In the present work, we generated a four-photon mixed state, which is equivalent to the partial, qubit-loss state of an N-qubit cluster state up to some local transformations. By using this mixed state, we then realize a GHZ-type violation of local realism. Our results not only demonstrate a mixed state's GHZ-type non-locality but also exhibit the robustness of cluster states under qubit-loss conditions.Comment: four pages, five figures, revTe

Design and real-time implementation of data-driven adaptive wide-area damping controller for back-to-back VSC-HVDC

This paper proposes a data-driven adaptive wide-area damping controller (D-WADC) for back-to-back VSC-HVDC to suppress the low frequency oscillation in a large-scale interconnected power system. The proposed D-WADC adopts a dual-loop control structure to make full use of the active and reactive power control of VSC-HVDC to improve the damping of the power system. A data-driven algorithm named the goal representation heuristic dynamic programming is employed to design the proposed D-WADC, which means the design procedure only requires the input and output data rather than the mathematic model of the concerned power system. Thus, the D-WADC can adapt to the change of operating condition through online weight modification. Besides, the adaptive delay compensator (ADC) is added to effectively compensate the stochastic delay involved in the wide-area feedback signal. Case studies are conducted based on the simplified model of a practical power system and the 16-machine system with a back-to-back VSC-HVDC. Both the simulation and hardware-in-loop experiment results verify that the proposed D-WADC can effectively suppress the low-frequency oscillation under a wide range of operating conditions, disturbances, and stochastic communication delays

Characterization of blaOxA-23 gene regions in isolates of Acinetobacter baumannii

Background/purposeTo investigate the characterization of blaOxA-23 gene regions in isolates of Acinetobacter baumannii from Taizhou Municipal Hospital.MethodsFifty-nine non-repetitive, multiresistant (including imipenem-resistant) isolates of A. baumannii were recovered from clinical infections in hospitalized patients from January 2010 to August 2011 in Taizhou Municipal Hospital (affiliated with Taizhou University) in China. These isolates were genotyped using pulsed-field gel electrophoresis (PFGE). blaOxA-23 β-lactamase and associated genetic structures were analyzed using polymerase chain reaction (PCR), and recombination plasmids were analyzed by BamHI- or SacI- restriction enzyme digestion; predicted promoter structures of blaOxA-23 genes were determined and compared using protein-protein BLAST analysis.ResultsFifteen out of 59 isolates expressing imipenem-resistant A. baumannii clinical isolates acquired either a blaOxA-23 β-lactamase gene. A new gene cluster (ISAba1-blaOxA-23-AMP) with three previously identified transposons (Tn2006, Tn2007, and Tn2008) and one previously identified gene cluster (ISAba1- blaOxA-23) was found in the isolates. Recombination plasmids were analyzed by restriction enzyme digestion.ConclusionOur results indicate that pattern A was the most prevalent molecular type based on PFGE, and that different clones might be widespread with a majority of ISAba1-blaOxA-23 clonal lineages in the 15 PCR positive isolates of A. baumannii in the hospital

Efficient parallel solver for high-speed rarefied gas flow using GSIS

Recently, the general synthetic iterative scheme (GSIS) has been proposed to find the steady-state solution of the Boltzmann equation in the whole range of gas rarefaction, where its fast-converging and asymptotic-preserving properties lead to the significant reduction of iteration numbers and spatial cells in the near-continuum flow regime. However, the efficiency and accuracy of GSIS has only been demonstrated in two-dimensional problems with small numbers of spatial cell and discrete velocities. Here, a large-scale parallel computing strategy is designed to extend the GSIS to three-dimensional high-speed flow problems. Since the GSIS involves the calculation of the mesoscopic kinetic equation which is defined in six-dimensional phase-space, and the macroscopic high-temperature Navier-Stokes-Fourier equations in three-dimensional physical space, the proper partition of the spatial and velocity spaces, and the allocation of CPU cores to the mesoscopic and macroscopic solvers, are the keys to improving the overall computational efficiency. These factors are systematically tested to achieve optimal performance, up to 100 billion spatial and velocity grids. For hypersonic flows around the Apollo reentry capsule, the X38-like vehicle, and the space station, our parallel solver can get the converged solution within one hour

The Prevalence of and Factors Associated With Anxiety and Depression Among Working-Age Adults in Mainland China at the Early Remission Stage of the Coronavirus 2019 Pandemic

Background: The Coronavirus 2019 (COVID-19) outbreak has led to a considerable proportion of adverse psychological symptoms in different subpopulations. This study aimed to investigate the status of anxiety and depression and their associated factors in the adult, working-age population in Mainland China at the early remission stage of the COVID-19 pandemic. Methods: An online study was conducted among 1,863 participants in 29 provinces in Mainland China from March 23 to 31, 2020. Their mental health was evaluated by the generalized anxiety disorder scale (GAD-7) and the patient health questionnaire (PHQ-9). Descriptive analysis, Chi-square, and multiple logistic regressions were applied. Results: About 44.5% of the participants had anxiety, 49.2% had depression, and 37.9% showed a combination of depression and anxiety. Around 83.7% of the participants claimed that the pandemic had a negative impact on their medical needs, which was the primary predictor of mental health, the degree of impact being positively related to the prevalence of anxiety and depression. More chronic diseases, moderate to bad self-rated health, severe perceived infection risk, and younger age group were the common risk factors for anxiety and depression. Having no children, unemployment, and a college-level educational background were associated with higher anxiety prevalence, whereas unmarried participants were correlated with higher depression prevalence. Conclusion: The working-age population showed a relatively high risk of anxiety and depression in Mainland China at the early remission stage of the pandemic. To improve medical services capacity for routine and delayed medical service needs should be a part of policy-makers\u27 priority agenda during this period of crisis