Some Remarks on the Final State Interactions in B→πKB\to \pi K Decays

Careful discussions are made on some points which are met in studying B decay final state interactions, taking the $B^0\to \pi^+ K^-$ process as an example. We point out that $\pi$--exchange rescatterings are not important, whereas for $D^*$ and $D^{**}$ exchanges, since the $B^0\to D^+D_s^-$ decay has a large branching ratio their contributions may be large enough to enhance the $B\to \pi K$ branching ratio significantly. However our estimates fail to predict a large enhancement.Comment: 5 pages, use elsart.sty; The previous version is erroneous in explaining the "charm peguin" effects. No large enhancement to $B\to \pi K$ is found through $D^+D_s^-$ intermediate stat

Steady Bell state generation via magnon-photon coupling

We show that parity-time ($\mathcal{PT}$) symmetry can be spontaneously broken in the recently reported energy level attraction of magnons and cavity photons. In the $\mathcal{PT}$-broken phase, magnon and photon form a high-fidelity Bell state with maximum entanglement. This entanglement is steady and robust against the perturbation of environment, in contrast to the general wisdom that expects instability of the hybridized state when the symmetry is broken. This anomaly is further understood by the compete of non-Hermitian evolution and particle number conservation of the hybridized system. As a comparison, neither $\mathcal{PT}$-symmetry broken nor steady magnon-photon entanglement is observed inside the normal level repulsion case. Our results may open a novel window to utilize magnon-photon entanglement as a resource for quantum technologies.Comment: 5 pages, 4 figure

MIXGAN: Learning Concepts from Different Domains for Mixture Generation

In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new domain with learned concepts. In particular, we propose a mixture generative adversarial network (MIXGAN). MIXGAN learns concepts of content and style from two domains respectively, and thus can join them for mixture generation in a new domain, i.e., generating images with content from one domain and style from another. MIXGAN overcomes the limitation of current GAN-based models which either generate new images in the same domain as they observed in training stage, or require off-the-shelf content templates for transferring or translation. Extensive experimental results demonstrate the effectiveness of MIXGAN as compared to related state-of-the-art GAN-based models.Comment: Accepted by IJCAI-ECAI 2018, the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligenc

Effects of relative orientation of the molecules on electron transport in molecular devices

Effects of relative orientation of the molecules on electron transport in molecular devices are studied by non-equilibrium Green's function method based on density functional theory. In particular, two molecular devices, with the planer Au$_{7}$ and Ag$_{3}$ clusters sandwiched between the Al(100) electrodes are studied. In each device, two typical configurations with the clusters parallel and vertical to the electrodes are considered. It is found that the relative orientation affects the transport properties of these two devices completely differently. In the Al(100)-Au$_7$-Al(100) device, the conductance and the current of the parallel configuration are much larger than those in the vertical configuration, while in the Al(100)-Ag$_{3}$-Al(100) device, an opposite conclusion is obtained