Metal-Free Flat Lens Using Negative Refraction by Nonlinear Four-wave Mixing

A perfect lens with unlimited resolution has always posed a challenge to both theoretical and experimental physicists. Recent developments in optical meta-materials promise an attractive approach towards perfect lenses using negative refraction to overcome the diffraction limit, improving resolution. However, those artificially engineered meta-materials usually company by high losses from metals and are extremely difficult to fabricate. An alternative proposal using negative refraction by four-wave mixing has attracted much interests recently, though most of existing experiments still require metals and none of them has been implemented for an optical lens. Here we experimentally demonstrate a metal-free flat lens for the first time using negative refraction by degenerate four-wave mixing with a thin glass slide. We realize optical lensing effect utilizing a nonlinear refraction law, which may have potential applications in microscopy

Multi-Document Summarization via Discriminative Summary Reranking

Existing multi-document summarization systems usually rely on a specific summarization model (i.e., a summarization method with a specific parameter setting) to extract summaries for different document sets with different topics. However, according to our quantitative analysis, none of the existing summarization models can always produce high-quality summaries for different document sets, and even a summarization model with good overall performance may produce low-quality summaries for some document sets. On the contrary, a baseline summarization model may produce high-quality summaries for some document sets. Based on the above observations, we treat the summaries produced by different summarization models as candidate summaries, and then explore discriminative reranking techniques to identify high-quality summaries from the candidates for difference document sets. We propose to extract a set of candidate summaries for each document set based on an ILP framework, and then leverage Ranking SVM for summary reranking. Various useful features have been developed for the reranking process, including word-level features, sentence-level features and summary-level features. Evaluation results on the benchmark DUC datasets validate the efficacy and robustness of our proposed approach

Pair Production of a 125 GeV Higgs Boson in MSSM and NMSSM at the LHC

In light of the recent LHC Higgs search data, we investigate the pair production of a SM-like Higgs boson around 125 GeV in the MSSM and NMSSM. We first scan the parameter space of each model by considering various experimental constraints, and then calculate the Higgs pair production rate in the allowed parameter space. We find that in most cases the dominant contribution to the Higgs pair production comes from the gluon fusion process and the production rate can be greatly enhanced, maximally 10 times larger than the SM prediction (even for a TeV-scale stop the production rate can still be enhanced by a factor of 1.3). We also calculate the chi-square value with the current Higgs data and find that in the most favored parameter region the production rate is enhanced by a factor of 1.45 in the MSSM, while in the NMSSM the production rate can be enhanced or suppressed (\sigma_{SUSY}/\sigma_{SM} varies from 0.7 to 2.4).Comment: 15 pages, 5 figure