A Numerical Analysis to the {π\pi} and {K} Coupled--Channel Scalar Form-factor

A numerical analysis to the scalar form-factor in the $\pi\pi$ and KK coupled--channel system is made by solving the coupled-channel dispersive integral equations, using the iteration method. The solutions are found not unique. Physical application to the $\pi\pi$ central production in the $pp\to pp\pi\pi$ process is discussed based upon the numerical solutions we found.Comment: 8 pages, Latex, 3 figures. Minor changes and one reference adde

DREAMWALKER: Mental Planning for Continuous Vision-Language Navigation

VLN-CE is a recently released embodied task, where AI agents need to navigate a freely traversable environment to reach a distant target location, given language instructions. It poses great challenges due to the huge space of possible strategies. Driven by the belief that the ability to anticipate the consequences of future actions is crucial for the emergence of intelligent and interpretable planning behavior, we propose DREAMWALKER -- a world model based VLN-CE agent. The world model is built to summarize the visual, topological, and dynamic properties of the complicated continuous environment into a discrete, structured, and compact representation. DREAMWALKER can simulate and evaluate possible plans entirely in such internal abstract world, before executing costly actions. As opposed to existing model-free VLN-CE agents simply making greedy decisions in the real world, which easily results in shortsighted behaviors, DREAMWALKER is able to make strategic planning through large amounts of ``mental experiments.'' Moreover, the imagined future scenarios reflect our agent's intention, making its decision-making process more transparent. Extensive experiments and ablation studies on VLN-CE dataset confirm the effectiveness of the proposed approach and outline fruitful directions for future work.Comment: Accepted at ICCV 2023; Project page: https://github.com/hanqingwangai/Dreamwalke

Aligning Linguistic Words and Visual Semantic Units for Image Captioning

Image captioning attempts to generate a sentence composed of several linguistic words, which are used to describe objects, attributes, and interactions in an image, denoted as visual semantic units in this paper. Based on this view, we propose to explicitly model the object interactions in semantics and geometry based on Graph Convolutional Networks (GCNs), and fully exploit the alignment between linguistic words and visual semantic units for image captioning. Particularly, we construct a semantic graph and a geometry graph, where each node corresponds to a visual semantic unit, i.e., an object, an attribute, or a semantic (geometrical) interaction between two objects. Accordingly, the semantic (geometrical) context-aware embeddings for each unit are obtained through the corresponding GCN learning processers. At each time step, a context gated attention module takes as inputs the embeddings of the visual semantic units and hierarchically align the current word with these units by first deciding which type of visual semantic unit (object, attribute, or interaction) the current word is about, and then finding the most correlated visual semantic units under this type. Extensive experiments are conducted on the challenging MS-COCO image captioning dataset, and superior results are reported when comparing to state-of-the-art approaches.Comment: 8 pages, 5 figures. Accepted by ACM MM 201

On the Long Distance Contribution to the Bs→γγB_s\to \gamma\gamma Decay in the Effective Lagrangian Approach

We re-estimate the decay branching ratio of $B_s\to 2\gamma$ through $D_s^+D_s^-$ and $D_s^{*+}D_s^{*-}$ intermediate states, in the effective Lagrangian approach. We find that the branching ratio does not exceed a few times $10^{-7}$, contrary to the result recently claimed in the literature.Comment: 7 page

Electronic Resonant Stimulated Raman Scattering Micro-Spectroscopy

Recently we have reported electronic pre-resonance stimulated Raman scattering (epr-SRS) microscopy as a powerful technique for super-multiplex imaging (Wei, L.; Nature 2017, 544, 465−470). However, under rigorous electronic resonance, background signal, which mainly originates from pump–probe process, overwhelms the desired vibrational signature of the chromophores. Here we demonstrate electronic resonant stimulated Raman scattering (er-SRS) microspectroscopy and imaging through suppression of electronic background and subsequent retrieval of vibrational peaks. We observed a change of the vibrational band shapes from normal Lorentzian, through dispersive shapes, to inverted Lorentzian as the electronic resonance was approached, in agreement with theoretical prediction. In addition, resonant Raman cross sections have been determined after power-dependence study as well as Raman excitation profile calculation. As large as 10^(–23) cm^2 of resonance Raman cross section is estimated in er-SRS, which is about 100 times higher than previously reported in epr-SRS. These results of er-SRS microspectroscopy pave the way for the single-molecule Raman detection and ultrasensitive biological imaging

Electronic Resonant Stimulated Raman Scattering Micro-Spectroscopy

Recently we have reported electronic pre-resonance stimulated Raman scattering (epr-SRS) microscopy as a powerful technique for super-multiplex imaging (Wei, L.; Nature 2017, 544, 465−470). However, under rigorous electronic resonance, background signal, which mainly originates from pump–probe process, overwhelms the desired vibrational signature of the chromophores. Here we demonstrate electronic resonant stimulated Raman scattering (er-SRS) microspectroscopy and imaging through suppression of electronic background and subsequent retrieval of vibrational peaks. We observed a change of the vibrational band shapes from normal Lorentzian, through dispersive shapes, to inverted Lorentzian as the electronic resonance was approached, in agreement with theoretical prediction. In addition, resonant Raman cross sections have been determined after power-dependence study as well as Raman excitation profile calculation. As large as 10^(–23) cm^2 of resonance Raman cross section is estimated in er-SRS, which is about 100 times higher than previously reported in epr-SRS. These results of er-SRS microspectroscopy pave the way for the single-molecule Raman detection and ultrasensitive biological imaging