7,736 research outputs found

    Three body radiative decay Bs→ϕKˉ0γB_s\to \phi \bar K^0 \gamma in the PQCD approach

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    We study the three body radiative decay Bsβ†’Ο•KΛ‰0Ξ³B_s\to \phi \bar K^0 \gamma by introducing the Ο•K\phi K pair distribution amplitudes (DAs) in the perturbative QCD approach. This nonperturbative inputs, the two meson DAs, is very important to simplify the calculations. Besides the dominant electromagnetic penguin operator O7Ξ³O_{7\gamma}, the subleading contributions from chromomagnetic penguin operator O8gO_{8g}, quark-loop corrections and annihilation type amplitudes are also considered. We find that the branching ratio for the decay Bsβ†’Ο•KΛ‰0Ξ³B_s\to \phi \bar K^0 \gamma is about (9.26βˆ’1.61βˆ’3.86βˆ’0.49+1.79+3.12+0.64)Γ—10βˆ’8(9.26^{+1.79+3.12+0.64}_{-1.61-3.86-0.49})\times10^{-8}, which is much smaller compared with that for the decay B0β†’Ο•K0Ξ³B^0\to \phi K^0\gamma. It is mainly because that the former decay induces by bβ†’dΞ³b\to d\gamma with small CKM matrix element being proportional to Ξ»3\lambda^3. The prediction for the direct CP asymmetry is ACPdir(Bsβ†’Ο•KΛ‰0Ξ³)=(βˆ’4.1βˆ’0.6βˆ’1.2βˆ’0.1+0.4+1.7+0.2)%A^{dir}_{CP}(B_s\to \phi \bar K^0 \gamma)=(-4.1^{+0.4+1.7+0.2}_{-0.6-1.2-0.1})\%, which is well consistent with the result from the U-spin symmetry approach. we also predict the Bsβ†’Ο•KΛ‰0Ξ³B_s \to\phi \bar K^0\gamma decay spectrum, which exhibits a maximu at the Ο•K\phi K invariant masss around 1.95 GeV.Comment: 17 pages,6 figures, Accepted for publication in EPJ

    Study of the K1(1270)βˆ’K1(1400)K_1(1270)-K_1(1400) mixing in the decays Bβ†’J/Ξ¨K1(1270),J/Ξ¨K1(1400)B\to J/\Psi K_1(1270), J/\Psi K_1(1400)

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    We studied the B meson decays Bβ†’J/Ξ¨K1(1270,1400)B\to J/\Psi K_1(1270,1400) in the pQCD approach beyond the leading order. With the vertex corrections and the NLO Wilson coefficients included, the branching ratios of the considered decays are Br(B+β†’J/Ξ¨K1(1270)+)=1.76βˆ’0.69+0.65Γ—10βˆ’3,Br(B+β†’J/Ξ¨K1(1400)+)=7.03βˆ’2.52+2.70Γ—10βˆ’4Br(B^+\to J/\Psi K_1(1270)^+)=1.76^{+0.65}_{-0.69}\times10^{-3}, Br(B^+\to J/\Psi K_1(1400)^+)=7.03^{+2.70}_{-2.52}\times10^{-4}, and Br(B0β†’J/Ξ¨K1(1270)0)=(1.63βˆ’0.64+0.60)Γ—10βˆ’3Br(B^0\to J/\Psi K_1(1270)^0)=(1.63^{+0.60}_{-0.64})\times10^{-3} with the mixing angle ΞΈK1=33∘\theta_{K_1}=33^\circ, which can agree well with the data or the present experimental upper limit within errors. So we support the opinion that ΞΈK1∼33∘\theta_{K_1}\sim33^\circ is much more favored than 58∘58^{\circ}. Furthermore, we also give the predictions for the polarization fractions, direct CP violations from the different polarization components, the relative phase angles for the considered decays with the mixing angle ΞΈK1=33∘\theta_{K_1}=33^\circ and 58∘58^\circ, respectively. The direct CP violations of the two charged decays B+β†’J/Ξ¨K1(1270,1400)+B^+\to J/\Psi K_1(1270,1400)^+ are very small (10βˆ’4∼10βˆ’5)(10^{-4}\sim10^{-5}), because there is no weak phase until up to O(Ξ»4)\mathcal{O}(\lambda^4) with the Wolfenstein parameter Ξ»=0.22537\lambda=0.22537. These results can be tested at the running LHCb and forthcoming Super-B experiments.Comment: 14 pages,3 figures,to appear in EPJ

    ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

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    Deep neural networks are vulnerable to adversarial attacks. The literature is rich with algorithms that can easily craft successful adversarial examples. In contrast, the performance of defense techniques still lags behind. This paper proposes ME-Net, a defense method that leverages matrix estimation (ME). In ME-Net, images are preprocessed using two steps: first pixels are randomly dropped from the image; then, the image is reconstructed using ME. We show that this process destroys the adversarial structure of the noise, while re-enforcing the global structure in the original image. Since humans typically rely on such global structures in classifying images, the process makes the network mode compatible with human perception. We conduct comprehensive experiments on prevailing benchmarks such as MNIST, CIFAR-10, SVHN, and Tiny-ImageNet. Comparing ME-Net with state-of-the-art defense mechanisms shows that ME-Net consistently outperforms prior techniques, improving robustness against both black-box and white-box attacks.Comment: ICML 201
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