Black Hole Entropy and Viscosity Bound in Horndeski Gravity

Horndeski gravities are theories of gravity coupled to a scalar field, in which the action contains an additional non-minimal quadratic coupling of the scalar, through its first derivative, to the Einstein tensor or the analogous higher-derivative tensors coming from the variation of Gauss-Bonnet or Lovelock terms. In this paper we study the thermodynamics of the static black hole solutions in $n$ dimensions, in the simplest case of a Horndeski coupling to the Einstein tensor. We apply the Wald formalism to calculate the entropy of the black holes, and show that there is an additional contribution over and above those that come from the standard Wald entropy formula. The extra contribution can be attributed to unusual features in the behaviour of the scalar field. We also show that a conventional regularisation to calculate the Euclidean action leads to an expression for the entropy that disagrees with the Wald results. This seems likely to be due to ambiguities in the subtraction procedure. We also calculate the viscosity in the dual CFT, and show that the viscosity/entropy ratio can violate the $\eta/S\ge 1/(4\pi)$ bound for appropriate choices of the parameters.Comment: 30 pages, no figure, minor revision

The D→ρD\to \rho semileptonic and radiative decays within the light-cone sum rules

The measured branching ratio of the $D$ meson semileptonic decay $D \to \rho e^+ \nu_e$, which is based on the $0.82~{\rm fb^{-1}}$ CLEO data taken at the peak of $\psi(3770)$ resonance, disagrees with the traditional SVZ sum rules analysis by about three times. In the paper, we show that this discrepancy can be eliminated by applying the QCD light-cone sum rules (LCSR) approach to calculate the $D\to \rho$ transition form factors $A_{1,2}(q^2)$ and $V(q^2)$. After extrapolating the LCSR predictions of these TFFs to whole $q^2$-region, we obtain $1/|V_{\rm cd}|^2 \times \Gamma(D \to \rho e \nu_e) =(55.45^{+13.34}_{-9.41})\times 10^{-15}~{\rm GeV}$. Using the CKM matrix element and the $D^0(D^+)$ lifetime from the Particle Data Group, we obtain ${\cal B} (D^0\to \rho^- e^+ \nu_e) = (1.749^{+0.421}_{-0.297}\pm 0.006)\times 10^{-3}$ and ${\cal B} (D^+ \to \rho^0 e^+ \nu_e) = (2.217^{+0.534}_{-0.376}\pm 0.015)\times 10^{-3}$, which agree with the CLEO measurements within errors. We also calculate the branching ratios of the two $D$ meson radiative processes and obtain ${\cal B}(D^0\to \rho^0 \gamma)= (1.744^{+0.598}_{-0.704})\times 10^{-5}$ and ${\cal B}(D^+ \to \rho^+ \gamma) = (5.034^{+0.939}_{-0.958})\times 10^{-5}$, which also agree with the Belle measurements within errors. Thus we think the LCSR approach is applicable for dealing with the $D$ meson decays.Comment: 12 pages, 7 figures, version to be published in EPJ

Annihilation Type Radiative Decays of BB Meson in Perturbative QCD Approach

With the perturbative QCD approach based on $k_T$ factorization, we study the pure annihilation type radiative decays $B^0 \to \phi\gamma$ and $B^0\to J/\psi \gamma$. We find that the branching ratio of $B^0 \to \phi\gamma$ is $(2.7^{+0.3+1.2}_{-0.6-0.6})\times10^{-11}$, which is too small to be measured in the current $B$ factories of BaBar and Belle. The branching ratio of $B^0\to J/\psi \gamma$ is $({4.5^{+0.6+0.7}_{-0.5-0.6}})\times10^{-7}$, which is just at the corner of being observable in the $B$ factories. A larger branching ratio $BR(B_s^0 \to J/\psi \gamma) \simeq 5 \times 10^{-6}$ is also predicted. These decay modes will help us testing the standard model and searching for new physics signals.Comment: 4 pages, revtex, with 1 eps figur

An Urban Traffic Flow Fusion Network Based on a Causal Spatiotemporal Graph Convolution Network

Traffic flow prediction is an important part of intelligent transportation systems. In recent years, most methods have considered only the feature relationships of spatial dimensions of traffic flow data, and ignored the feature fusion of spatial and temporal aspects. Traffic flow has the features of periodicity, nonlinearity and complexity. There are many relatively isolated points in the nodes of traffic flow, resulting in the features usually being accompanied by high-frequency noise. The previous methods directly used the graph convolution network for feature extraction. A polynomial approximation graph convolution network is essentially a convolution operation to enhance the weight of high-frequency signals, which lead to excessive high-frequency noise and reduce prediction accuracy to a certain extent. In this paper, a deep learning framework is proposed for a causal gated low-pass graph convolution neural network (CGLGCN) for traffic flow prediction. The full convolution structure adopted by the causal convolution gated linear unit (C-GLU) extracts the time features of traffic flow to avoid the problem of long running time associated with recursive networks. The reduction of running parameters and running time greatly improved the efficiency of the model. The new graph convolution neural network with self-designed low-pass filter was able to extract spatial features, enhance the weight of low-frequency signal features, suppress the influence of high-frequency noise, extract the spatial features of each node more comprehensively, and improve the prediction accuracy of the framework. Several experiments were carried out on two real-world real data sets. Compared with the existing models, our model achieved better results for short-term and long-term prediction.© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

3D Object Detection Algorithm Based on the Reconstruction of Sparse Point Clouds in the Viewing Frustum

In response to the problem that the detection precision of the current 3D object detection algorithm is low when the object is severely occluded, this study proposes an object detection algorithm based on the reconstruction of sparse point clouds in the viewing frustum. The algorithm obtains more local feature information of the sparse point clouds in the viewing frustum through dimensional expansion, performs the fusion of local and global feature information of the point cloud data to obtain point cloud data with more complete semantic information, and then applies the obtained data to the 3D object detection task. The experimental results show that the precision of object detection in both 3D view and BEV (Bird’s Eye View) can be improved effectively through the algorithm, especially object detection of moderate and hard levels when the object is severely occluded. In the 3D view, the average precision of the 3D detection of cars, pedestrians, and cyclists at a moderate level can be increased by 7.1p.p., 16.39p.p., and 5.42p.p., respectively; in BEV, the average precision of the 3D detection of car, pedestrians, and cyclists at hard level can be increased by 6.51p.p., 16.57p.p., and 7.18p.p., respectively, thus indicating the effectiveness of the algorithm.© 2022 Xing Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

The progenitor and central engine of a peculiar GRB 230307A

Recently, a lack of supernova-associated long-duration gamma-ray burst (GRB 230307A) at such a low redshift $z=0.065$, but associated with a possible kilonova emission, has attracted great attention. Its heavy element nucleosynthesis and the characteristic of soft X-ray emission suggests that the central engine of GRB 230307A is magnetar which is originated from a binary compact star merger. The calculated lower value of $\varepsilon \sim 0.05$ suggests that the GRB 230307A seems to be with ambiguous progenitor. The lower value of $f_{\rm eff}=1.23$ implies that the GRB 230307A is not likely to be from the effect of "tip of iceberg". We adopt the magnetar central engine model to fit the observed soft X-ray emission with a varying efficiency and find that the parameters constraints of magnetar fall into a reasonable range, i.e., $B<9.4\times10^{15}$ G and $P<2.5$ ms for $\Gamma_{\rm sat} = 10^3$, and $B<3.6\times10^{15}$ G and $P<1.05$ ms for $\Gamma_{\rm sat} = 10^4$. Whether the progenitor of GBR 230307A is from the mergers of neutron star - white dwarf (NS - WD) or neutron star - neutron star (NS - NS) remains unknown.Comment: 7 pages, 1 table, 4 figures. Accepted for publication in ApJ Letters, 962:L27, 202