7,712 research outputs found

    Flavor-twisted boundary condition for simulations of quantum many-body systems

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    We present an approximative simulation method for quantum many-body systems based on coarse graining the space of the momentum transferred between interacting particles, which leads to effective Hamiltonians of reduced size with the flavor-twisted boundary condition. A rapid, accurate, and fast convergent computation of the ground-state energy is demonstrated on the spin-1/2 quantum antiferromagnet of any dimension by employing only two sites. The method is expected to be useful for future simulations and quick estimates on other strongly correlated systems.Comment: 6 pages, 2 figure

    Edge Guided Reconstruction for Compressive Imaging

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    We propose EdgeCS—an edge guided compressive sensing reconstruction approach—to recover images of higher quality from fewer measurements than the current methods. Edges are important image features that are used in various ways in image recovery, analysis, and understanding. In compressive sensing, the sparsity of image edges has been successfully utilized to recover images. However, edge detectors have not been used on compressive sensing measurements to improve the edge recovery and subsequently the image recovery. This motivates us to propose EdgeCS, which alternatively performs edge detection and image reconstruction in a mutually beneficial way. The edge detector of EdgeCS is designed to faithfully return partial edges from intermediate image reconstructions even though these reconstructions may still have noise and artifacts. For complex-valued images, it incorporates joint sparsity between the real and imaginary components. EdgeCS has been implemented with both isotropic and anisotropic discretizations of total variation and tested on incomplete k-space (spectral Fourier) samples. It applies to other types of measurements as well. Experimental results on large-scale real/complex-valued phantom and magnetic resonance (MR) images show that EdgeCS is fast and returns high-quality images. For example, it exactly recovers the 256×256 Shepp–Logan phantom from merely 7 radial lines (3.03% k-space), which is impossible for most existing algorithms. It is able to accurately reconstruct a 512 × 512 MR image with 0.05 white noise from 20.87% radial samples. On complex-valued MR images, it obtains recoveries with faithful phases, which are important in many medical applications. Each of these tests took around 30 seconds on a standard PC. Finally, the algorithm is GPU friendly

    Molecular characters and recombinant expression of the carboxylesterase gene of the meadow moth Loxostege sticticalis L. (Lepidoptera: Pyralidae)

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    Insect carboxylesterases are enzymes that catalyze the hydrolysis of ester and amide moieties, which play important roles in insecticide resistance, specifically allelochemical tolerance and developmental regulation. We obtained the cDNA encoding carboxylesterase gene of Loxostege sticticalis (LstiCarE) by a cDNA library screen. The full cDNA of LstiCarE is 1,980 bp in length, containing an open reading frame (ORF) of 1,875 bp, which encodes a preprotein of 625 amino acid residues. The LstiCarE contains the catalytic triad (Ser-His-Glu), the pentapeptide GxSxG motif and GxxHxxD/E motif, which are typical characteristic of esterases. The GxSxG and GxxHxxD/E motifs of LstiCarE are modified as GCSAG and GxxHxxQ, respectively. The 3-D model structure of LstiCarE showed that Ser197, His440 and Glu321 are aggregated together, which form the catalytic triad. The recombinant LstiCarE were successfully expressed in BL21 cells using recombinant plasmid DNA, and showed high carboxylesterase activity. However, the biochemical and physiological functions of carboxylesterase gene in L. sticticalis requires further investigation.Key words: Carboxylesterase gene, Loxostege sticticalis, recombinant expression

    Spectral functions of the Falicov-Kimball model with electronic ferroelectricity

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    We calculate the angular resolved photoemission spectrum of the Falicov-Kimball model with electronic ferroelectricity where dd- and ff-electrons have different hoppings. In mix-valence regimes, the presence of strong scattering processes between dd-ff excitons and a hole, created by emission of an electron, leads to the formation of pseudospin polarons and novel electronic structures with bandwidth scaling with that of dd-ff excitons. Especially, in the two-dimensional case, we find that flat regions exist near the bottom of the quasiparticle band in a wide range of the dd- and ff-level energy difference.Comment: 5 pages, 5 figure

    Under-water molecular signalling : a hidden transmitter and absent receivers problem

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    Wave-based signals have been successful in reliably and efficiently transferring data between two or more well defined points (e.g., known location area). However, it is challenged when the transmitter is hidden and the receivers are absent. Essentially, the transmitter and the receivers have no location knowledge of each other. We demonstrate that unlike wave-based transmissions, the total molecular energy doesn’t monotonically degrade as a function of time. This paper uses a bio-inspired method of communicating data from a hidden transmitter to a group of absent receivers. A specialized molecular communication system is designed, including how to embed vital location information in the structure of a heterogeneous biochemical molecule. Like message in a bottle, there is a growing probability of receiving the location message over a period of several years. The only caveat is that there is an initial delay of a few hours to days, depending on the proximity of the rescue team to the crash site. This will provide an attractive alternative to current wave-based communications for delay-tolerant crash recovery

    Exceptional high Seebeck Coefficient and Gas-Flow-Induced Voltage in Multilayer Graphene

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    Monolayer graphene shows Seebeck coefficient several times and gas-flow-induced voltage twenty times higher than that of bulk graphite. Here we find that the Seebeck coefficient of multilayer graphene increases monotonically with increasing layer and reaches its peak value at hexa-layer ~77% higher than for monolayer and then decreases, although the electric resistance decreases monotonically with increasing layer. The flow-induced voltage is significantly higher in 2, 4, 5, 6, 7 layered graphene than in 1, 3, 8 layered one, against the prevailing view that it should be proportional to Seebeck coefficient. These thickness effects are also in sharp contrast to that in continuous aluminum nanofilms.Comment: 5 figures,20pages,conferenc
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