Updating B --> PP, VP decays in the framework of flavor symmetry

Current data of charmless B meson decays to two pseudoscalar mesons (PP) and one vector and one pseudoscalar mesons (VP) are analyzed within the framework of flavor SU(3) symmetry, a working principle that we have tested by allowing symmetry breaking factors in the decay amplitudes and found to be a good approximate symmetry. In the PP sector, the color-suppressed tree amplitude is found to be larger than previously known and has a strong phase of ~ -70^o relative to the color-favored tree amplitude. We have extracted for the first time the W-exchange and penguin-annihilation amplitudes. The former has a size of about the QCD-penguin amplitude and a phase opposite to that of the color-favored tree amplitude, while the latter is suppressed in magnitude but gives the dominant contribution to the $B_s^0 \to \pi^+ \pi^-$ and $\pi^0 \pi^0$ decays. In the VP sector, one striking feature is that the color-suppressed tree amplitude with the spectator quark ending up in the vector meson has a large size and a strong phase of ~ -90^o relative to the color-favored tree amplitudes. The associated electroweak penguin amplitude also has a similar strong phase and a magnitude comparable to the corresponding QCD penguin amplitude. This leads to a large branching fraction of order 10^{-6} for $B_s^0 \to \phi \pi^0$. In contrast, the color-suppressed tree, QCD penguin, and electroweak penguin amplitudes with the spectator quark ending up in the pseudoscalar meson have magnitudes more consistent with naive expectations. Besides, current data are not sufficiently precise for us to fix the W-exchange amplitudes. For both the PP and VP sectors, predictions of all the decay modes are made based upon our preferred fit results and compared with data and those made by perturbative approaches. We have identified a few observables to be determined experimentally in order to discriminate among theory calculations.Comment: 34 pages, 19 tables; references update

Giant Magnetoresistance in Hubbard Chains

We use numerically unbiased methods to show that the one-dimensional Hubbard model with periodically distributed on-site interactions already contains the minimal ingredients to display the phenomenon of magnetoresistance; i.e., by applying an external magnetic field, a dramatic enhancement on the charge transport is achieved. We reach this conclusion based on the computation of the Drude weight and of the single-particle density of states, applying twisted boundary condition averaging to reduce finite-size effects. The known picture that describes the giant magnetoresistance, by interpreting the scattering amplitudes of parallel or antiparallel polarized currents with local magnetizations, is obtained without having to resort to different entities; itinerant and localized charges are indistinguishable.Comment: 6+4 pages 5+5 figures, as publishe

Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack

In recent years, deep neural networks demonstrated state-of-the-art performance in a large variety of tasks and therefore have been adopted in many applications. On the other hand, the latest studies revealed that neural networks are vulnerable to adversarial examples obtained by carefully adding small perturbation to legitimate samples. Based upon the observation, many attack methods were proposed. Among them, the optimization-based CW attack is the most powerful as the produced adversarial samples present much less distortion compared to other methods. The better attacking effect, however, comes at the cost of running more iterations and thus longer computation time to reach desirable results. In this work, we propose to leverage the information of gradients as a guidance during the search of adversaries. More specifically, directly incorporating the gradients into the perturbation can be regarded as a constraint added to the optimization process. We intuitively and empirically prove the rationality of our method in reducing the search space. Our experiments show that compared to the original CW attack, the proposed method requires fewer iterations towards adversarial samples, obtaining a higher success rate and resulting in smaller $\ell_2$ distortion

Unbiased Correction Relations for Galaxy Cluster properties Derived from Chandra and XMM-Newton

We use a sample of 62 clusters of galaxies to investigate the discrepancies of gas temperature and total mass within r500 between XMM-Newton and Chandra data. Comparisons of the properties show that: (1) Both the de-projected and projected temperatures determined by Chandra are higher than those of XMM-Newton and there is a good linear relation for the de-projected temperature. (2) The Chandra mass is much higher than XMM-Newton mass with a bias of 0.15. To explore the reasons for the discrepancy in mass, we recalculate the Chandra mass (expressed as M_c) by modifying its temperature with the de-projected temperature relation. The results show that M_c is more close to the XMM-Newton mass with the bias reducing to 0.02. Moreover, M_c are corrected with the r500 measured by XMM-Newton and the intrinsic scatter is significantly improved with the value reducing from 0.20 to 0.12. These mean that the temperature bias may be the main factor causing the mass bias. At last, we find that M_c is consistent with the corresponding XMM-Newton mass derived directly from our mass relation at a given Chandra mass. Thus, the de-projected temperature and mass relations can provide unbiased corrections for galaxy cluster properties derived from Chandra and XMM-Newton.Comment: accepted for publication in Ap

LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning

Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time. In this paper, we focus on decentralized distributed deep learning systems and aim to achieve differential privacy with good convergence rate and low communication cost. To achieve this goal, we propose a new learning algorithm LEASGD (Leader-Follower Elastic Averaging Stochastic Gradient Descent), which is driven by a novel Leader-Follower topology and a differential privacy model.We provide a theoretical analysis of the convergence rate and the trade-off between the performance and privacy in the private setting.The experimental results show that LEASGD outperforms state-of-the-art decentralized learning algorithm DPSGD by achieving steadily lower loss within the same iterations and by reducing the communication cost by 30%. In addition, LEASGD spends less differential privacy budget and has higher final accuracy result than DPSGD under private setting

Tunneling Field-Effect Junctions with WS2_2 barrier

Transition metal dichalcogenides (TMDCs), with their two-dimensional structures and sizable bandgaps, are good candidates for barrier materials in tunneling field-effect transistor (TFET) formed from atomic precision vertical stacks of graphene and insulating crystals of a few atomic layers in thickness. We report first-principles study of the electronic properties of the Graphene/WS$_2$/Graphene sandwich structure revealing strong interface effects on dielectric properties and predicting a high ON/OFF ratio with an appropriate WS$_2$ thickness and a suitable range of the gate voltage. Both the band spin-orbit coupling splitting and the dielectric constant of the WS$_2$ layer depend on its thickness when in contact with the graphene electrodes, indicating strong influence from graphene across the interfaces. The dielectric constant is significantly reduced from the bulk WS$_2$ value. The effective barrier height varies with WS$_2$ thickness and can be tuned by a gate voltage. These results are critical for future nanoelectronic device designs.Comment: 18 pages, 5 figure

Study of the isospin breaking decay Y(2175)→ϕf0(980)→ϕηπ0\mathbf{\boldsymbol{Y(2175)\rightarrow\phi f_0(980)\rightarrow\phi\eta{\pi}^0}} at BESIII

Using measured branching fraction of the decay $J/\psi \rightarrow\eta Y(2175))\rightarrow\eta\phi f_0(980)\rightarrow\eta\phi\pi^+\pi^{-}$ from the BESIII experiment, we estimate branching fraction of $J/\psi \rightarrow\eta Y(2175))\rightarrow\eta\phi f_0(980)\rightarrow\eta\phi\eta\pi^{0}$ decay, which proceeds via the $f_0(980)$-$a_0^0(980)$ mixing and the $\pi^0$-$\eta$ mixing. The branching fraction is predicted to be about $O(10^{-6})$, which can be accessed with $10^{10}$ $J/\psi$ events collected at the BESIII. The decay is dominated by the contribution from $f_0(980)$-$a_0^0(980)$ mixing. We find that the interference between the amplitudes due to $f_0(980)$-$a_0^0(980)$ mixing and that due to $\pi^0$-$\eta$ mixing is destructive. The branching fraction can be decreased by about $10\%$ owing to the interference effect. We also study the $\eta\pi^0$ mass squared spectrum, and find that a narrow peak due to the $f_0(980)$-$a_0^0(980)$ mixing in the $\eta\pi^0$ mass squared spectrum should be observed. The observation of this decay in experiment will be helpful to determine the $f_0(980)$-$a_0^0(980)$ mixing intensity and get information about the structures of the light scalar mesons.Comment: 16 pages, 3 figure

Electronic band gaps and transport properties in aperiodic bilayer graphene superlattices of Thue-Morse sequence

We investigate electronic band structure and transport properties in bilayer graphene superlattices of Thue-Morse sequence. It is interesting to find that the zero-$\bar{k}$ gap center is sensitive to interlayer coupling $t'$, and the centers of all gaps shift versus $t'$ at a linear way. Extra Dirac points may emerge at $k_{y}\ne$0, and when the extra Dirac points are generated in pairs, the electronic conductance obeys a diffusive law, and the Fano factor tends to be 1/3 as the order of Thue-Morse sequence increases. Our results provide a flexible and effective way to control the transport properties in graphene.Comment: 5 pages, 6 figures. Accepted for publication in Applied Physics Letter

Data based reconstruction of complex multiplex networks

It has been recognized that many complex dynamical systems in the real world require a description in terms of multiplex networks, where a set of common, mutually connected nodes belong to distinct network layers and play a different role in each layer. In spite of recent progress towards data based inference of single-layer networks, to reconstruct complex systems with a multiplex structure remains largely open. We articulate a mean-field based maximum likelihood estimation framework to solve this outstanding and challenging problem. We demonstrate the power of the reconstruction framework and characterize its performance using binary time series from a class of prototypical duplex network systems that host two distinct types of spreading dynamics. In addition to validating the framework using synthetic and real-world multiplex networks, we carry out a detailed analysis to elucidate the impacts of structural and dynamical parameters as well as noise on the reconstruction accuracy and robustness.Comment: One main context and a supplementary informatio

A good mass proxy for galaxy clusters with XMM-Newton

We use a sample of 39 galaxy clusters at redshift z < 0.1 observed by XMM-Newton to investigate the relations between X-ray observables and total mass. Based on central cooling time and central temperature drop, the clusters in this sample are divided into two groups: 25 cool core clusters and 14 non-cool core clusters, respectively. We study the scaling relations of Lbol-M500, M500-T, M500-Mg and M500-YX, and also the influences of cool core on these relations. The results show that the M500-YX relation has a slope close to the standard self-similar value, has the smallest scatter and does not vary with the cluster sample. Moreover, the M500-YX relation is not affected by the cool core. Thus, the parameter of YX may be the best mass indicator.Comment: ApJ Accepted, 25 pages, 7 figure