Quantum phonon transport of molecular junctions amide-linked with carbon nanotubes: a first-principle study

Quantum phonon transport through benzene and alkane chains amide-linked with single wall carbon nanotubes (SWCNTs) is studied within the level of density functional theory. The force constant matrices are obtained from standard quantum chemistry software. The phonon transmission and thermal conductance are from the nonequilibrium Green's function and the mode-matching method. We find that the ballistic thermal conductance is not sensitive to the compression or stretching of the molecular junction. The terminating groups of the SWCNTs at the cutting edges only influence the thermal conductance quantitatively. The conductance of the benzene and alkane chains shows large difference. Analysis of the transmission spectrum shows that (i) the low temperature thermal conductance is mainly contributed by the SWCNT transverse acoustic modes, (ii) the degenerate phonon modes show different transmission probability due to the presence of molecular junction, (iii) the SWCNT twisting mode can hardly be transmitted by the alkane chain. As a result, the ballistic thermal conductance of alkane chains is larger than that of benzene chains below 38 K, while it is smaller at higher temperature.Comment: 5 pages, 5 figure

Double-Layer Bose-Einstein Condensates with Large Number of Vortices

In this paper we systematically study the double layer vortex lattice model, which is proposed to illustrate the interplay between the physics of a fast rotating Bose-Einstein condensate and the macroscopic quantum tunnelling. The phase diagram of the system is obtained. We find that under certain conditions the system will exhibit one novel phase transition, which is consequence of competition between inter-layer coherent hopping and inter-layer density-density interaction. In one phase the vortices in one layer coincide with those in the other layer. And in another phase two sets of vortex lattices are staggered, and as a result the quantum tunnelling between two layers is suppressed. To obtain the phase diagram we use two kinds of mean field theories which are quantum Hall mean field and Thomas-Fermi mean field. Two different criteria for the transition taking place are obtained respectively, which reveals some fundamental differences between these two mean field states. The sliding mode excitation is also discussed.Comment: 12 pages, 8 figure

Coupled electron and phonon transport in one-dimensional atomic junctions

Employing the nonequilibrium Green's function method, we develop a fully quantum mechanical model to study the coupled electron-phonon transport in one-dimensional atomic junctions in the presence of a weak electron-phonon interaction. This model enables us to study the electronic and phononic transport on an equal footing. We derive the electrical and energy currents of the coupled electron-phonon system and the energy exchange between them. As an application, we study the heat dissipation in current carrying atomic junctions within the self-consistent Born approximation, which guarantees energy current conservation. We find that the inclusion of phonon transport is important in determining the heat dissipation and temperature change of the atomic junctions.Comment: 10 pages, 7 figure

Link Prediction Based on Local Random Walk

The problem of missing link prediction in complex networks has attracted much attention recently. Two difficulties in link prediction are the sparsity and huge size of the target networks. Therefore, the design of an efficient and effective method is of both theoretical interests and practical significance. In this Letter, we proposed a method based on local random walk, which can give competitively good prediction or even better prediction than other random-walk-based methods while has a lower computational complexity.Comment: 6 pages, 2 figure

Study of color suppressed modes B0→Dˉ(∗)0η(′)B^0 \to \bar D^{(*)0} \eta^{(\prime)}

The color suppressed modes $B^0 \to \bar D^{(*)0} \eta^{(\prime)}$ are analyzed in perturbative QCD approach. We find that the dominant contribution is from the non-factorizable diagrams. The branching ratios calculated in our approach for $B^0 \to \bar D^{(*)0} \eta$ agree with current experiments. By neglecting the gluonic contribution, we predict the branching ratios of $B^0 \to \bar D^{(*)0} \eta'$ are at the comparable size of $B^0 \to \bar D^{(*)0} \pi^0$, but smaller than that of $B^0 \to \bar D^{(*)0} \eta$.Comment: revtex, 5 pages, axodraw.st

Supersymmetry of the Schrodinger and PP Wave Solutions in Einstein-Weyl Supergravities

We obtain the Schrodinger and general pp-wave solutions with or without the massive vector in Einstein-Weyl supergravity. The vector is an auxiliary field in the off-shell supermultiplet and it acquires a kinetic term in the Weyl-squared super invariant. We study the supersymmetry of these solutions and find that turning on the massive vector has a consequence of breaking all the supersymmetry. The Schrodinger and also the pp-wave solutions with the massive vector turned off on the other hand preserve 1/4 of the supersymmetry.Comment: 13 pages, no figur

Effective and Efficient Similarity Index for Link Prediction of Complex Networks

Predictions of missing links of incomplete networks like protein-protein interaction networks or very likely but not yet existent links in evolutionary networks like friendship networks in web society can be considered as a guideline for further experiments or valuable information for web users. In this paper, we introduce a local path index to estimate the likelihood of the existence of a link between two nodes. We propose a network model with controllable density and noise strength in generating links, as well as collect data of six real networks. Extensive numerical simulations on both modeled networks and real networks demonstrated the high effectiveness and efficiency of the local path index compared with two well-known and widely used indices, the common neighbors and the Katz index. Indeed, the local path index provides competitively accurate predictions as the Katz index while requires much less CPU time and memory space, which is therefore a strong candidate for potential practical applications in data mining of huge-size networks.Comment: 8 pages, 5 figures, 3 table