VcbV_{cb} from the semileptonic decay B→DℓνˉℓB\to D \ell \bar{\nu}_{\ell} and the properties of the DD meson distribution amplitude

The improved QCD light-cone sum rule (LCSR) provides an effective way to deal with the heavy-to-light transition form factors (TFFs). Firstly, we adopt the improved LCSR approach to deal with the $B\to D$ TFF $f^{+}(q^2)$ up to twist-4 accuracy. Due to the elimination of the most uncertain twist-3 contribution and the large suppression of the twist-4 contribution, the obtained LCSR shall provide us a good platform for testing the $D$-meson leading-twist DA. For the purpose, we suggest a new model for the $D$-meson leading-twist DA ($\phi_{3D}$), whose longitudinal behavior is dominantly determined by a parameter $B$. Moreover, we find its second Gegenbauer moment $a^D_2\sim B$. Varying $B$ within certain region, one can conveniently mimic the $D$-meson DA behavior suggested in the literature. Inversely, by comparing the estimations with the experimental data on the $D$-meson involved processes, one can get a possible range for the parameter $B$ and a determined behavior for the $D$-meson DA. Secondly, we discuss the $B\to D$ TFF at the maximum recoil region and present a detailed comparison of it with the pQCD estimation and the experimental measurements. Thirdly, by applying the LCSR on $f^{+}(q^2)$, we study the CKM matrix element \Vcb together with its uncertainties by adopting two types of processes, i.e. the $B^0/\bar{B}^0$-type and the $B^{\pm}$-type. It is noted that a smaller $B \precsim 0.20$ shows a better agreement with the experimental value on \Vcb. For example, for the case of $B=0.00$, we obtain $|V_{cb}|(B^0/\bar{B}^0-{\rm type})=(41.28 {^{+5.68}_{-4.82}} {^{+1.13}_{-1.16}}) \times 10^{-3}$ and $|V_{cb}|(B^{\pm}-{\rm type})=(40.44 {^{+5.56}_{-4.72}} {^{+0.98}_{-1.00}}) \times 10^{-3}$, whose first (second) uncertainty comes from the squared average of the mentioned theoretical (experimental) uncertainties.Comment: 13 pages, 10 figures. Reference updated and discussion improved. To be published in Nucl.Phys.

4-Meth­oxy­anilinium hexa­fluoro­phosphate monohydrate

In the structure of the title compound, C7H10NO+·PF6 −·H2O, the protonated 4-meth­oxy­anilinium cations and hexa­fluoro­phosphate anions are bridged by the water mol­ecule via N—H⋯O and O—H⋯F hydrogen bonds. The resulting zigzag chains extend along the c axis. In addition, C—H⋯π inter­actions are observed in the crystal packing

The ρ\rho-meson longitudinal leading-twist distribution amplitude

In the present paper, we suggest a convenient model for the vector $\rho$-meson longitudinal leading-twist distribution amplitude $\phi_{2;\rho}^\|$, whose distribution is controlled by a single parameter $B^\|_{2;\rho}$. By choosing proper chiral current in the correlator, we obtain new light-cone sum rules (LCSR) for the $B\to\rho$ TFFs $A_1$, $A_2$ and $V$, in which the $\delta^1$-order $\phi_{2;\rho}^\|$ provides dominant contributions. Then we make a detailed discussion on the $\phi_{2;\rho}^\|$ properties via those $B\to\rho$ TFFs. A proper choice of $B^\|_{2;\rho}$ can make all the TFFs agree with the lattice QCD predictions. A prediction of $|V_{\rm ub}|$ has also been presented by using the extrapolated TFFs, which indicates that a larger $B^{\|}_{2;\rho}$ leads to a larger $|V_{\rm ub}|$. To compare with the BABAR data on $|V_{\rm ub}|$, the longitudinal leading-twist DA $\phi_{2;\rho}^\|$ prefers a doubly-humped behavior.Comment: 7 pages, 3 figures. Discussions improved and references updated. To be published in Phys.Lett.

Nighttime Thermal Infrared Image Colorization with Feedback-based Object Appearance Learning

Stable imaging in adverse environments (e.g., total darkness) makes thermal infrared (TIR) cameras a prevalent option for night scene perception. However, the low contrast and lack of chromaticity of TIR images are detrimental to human interpretation and subsequent deployment of RGB-based vision algorithms. Therefore, it makes sense to colorize the nighttime TIR images by translating them into the corresponding daytime color images (NTIR2DC). Despite the impressive progress made in the NTIR2DC task, how to improve the translation performance of small object classes is under-explored. To address this problem, we propose a generative adversarial network incorporating feedback-based object appearance learning (FoalGAN). Specifically, an occlusion-aware mixup module and corresponding appearance consistency loss are proposed to reduce the context dependence of object translation. As a representative example of small objects in nighttime street scenes, we illustrate how to enhance the realism of traffic light by designing a traffic light appearance loss. To further improve the appearance learning of small objects, we devise a dual feedback learning strategy to selectively adjust the learning frequency of different samples. In addition, we provide pixel-level annotation for a subset of the Brno dataset, which can facilitate the research of NTIR image understanding under multiple weather conditions. Extensive experiments illustrate that the proposed FoalGAN is not only effective for appearance learning of small objects, but also outperforms other image translation methods in terms of semantic preservation and edge consistency for the NTIR2DC task.Comment: 14 pages, 14 figures. arXiv admin note: text overlap with arXiv:2208.0296