Experimental observation of topological Fermi arcs in type-II Weyl semimetal MoTe2

Weyl semimetal is a new quantum state of matter [1-12] hosting the condensed matter physics counterpart of relativisticWeyl fermion [13] originally introduced in high energy physics. The Weyl semimetal realized in the TaAs class features multiple Fermi arcs arising from topological surface states [10, 11, 14-16] and exhibits novel quantum phenomena, e.g., chiral anomaly induced negative mag-netoresistance [17-19] and possibly emergent supersymmetry [20]. Recently it was proposed theoretically that a new type (type-II) of Weyl fermion [21], which does not have counterpart in high energy physics due to the breaking of Lorentz invariance, can emerge as topologically-protected touching between electron and hole pockets. Here, we report direct spectroscopic evidence of topological Fermi arcs in the predicted type-II Weyl semimetal MoTe2 [22-24]. The topological surface states are confirmed by directly observing the surface states using bulk-and surface-sensitive angle-resolved photoemission spectroscopy (ARPES), and the quasi-particle interference (QPI) pattern between the two putative Fermi arcs in scanning tunneling microscopy (STM). Our work establishes MoTe2 as the first experimental realization of type-II Weyl semimetal, and opens up new opportunities for probing novel phenomena such as exotic magneto-transport [21] in type-II Weyl semimetals.Comment: submitted on 01/29/2016. Nature Physics, in press. Spectroscopic evidence of the Fermi arcs from two complementary surface sensitive probes - ARPES and STS. A comparison of the calculated band structure for T_d and 1T' phase to identify the topological Fermi arcs in the T_d phase is also included in the supplementary informatio

Multiplexed five-color molecular imaging of cancer cells and tumor tissues with carbon nanotube Raman tags in the near-infrared

Single-walled carbon nanotubes (SWNTs) with five different C13/C12 isotope compositions and well-separated Raman peaks have been synthesized and conjugated to five targeting ligands in order to impart molecular specificity. Multiplexed Raman imaging of live cells has been carried out by highly specific staining of cells with a five-color mixture of SWNTs. Ex vivo multiplexed Raman imaging of tumor samples uncovers a surprising up-regulation of epidermal growth factor receptor (EGFR) on LS174T colon cancer cells from cell culture to in vivo tumor growth. This is the first time five-color multiplexed molecular imaging has been performed in the near-infrared (NIR) region under a single laser excitation. Near zero interfering background of imaging is achieved due to the sharp Raman peaks unique to nanotubes over the low, smooth autofluorescence background of biological species.Comment: Published in Nano Researc

Research on Target Tracking Based on Unscented Kalman Filter

Aiming at the multi-source heterogeneous of target tracking system information. On the basis of "current" statistical model, this paper researches the unscented Kalman filter information fusion method and analyzes its mathematical model. According to the mathematic model researching of optimal estimation real time tracking algorithm, it be able to describe and process the sensor information of uncertainty characteristics by using fuzzy theory, making an adaptive adjustment of the measurement parameters of the Kalman filter, so as to achieve the system error calibration and measurement error adaptive function. In line with the model of functional parameters, carrying on the simulation of the single sensor filtering error and multiple sensor filter error, by comparing the trajectory and actual motion analysis shows, this method can effectively improve tracking precision and stability. It can avoid external interference; accelerate the convergence speed of response and adapting active period of target tracking measurement requirements

Application and Research on Data Association in Target R

In order to solve the problem of target recognition in the complex environment of the multi-source detection, a kind of D-S evidence reasoning method based on data association is put forward. This paper analyzes the condition and method of data associated and evidence reasoning, also establishes the D-S evidential reasoning algorithm for target recognition based on data association. It uses four sensors on three target data correlation analysis and uses the model identification algorithm on the calculation of system detection capacity. Through the calculation of model establishment and contrast calculation, it proves that D-S evidence reasoning method based on data associated is more reliable than the traditional evidence reasoning method, and the recognition ability is higher. The results verify the effectiveness of the method

Study on the Applications of Cross-Layer Information Fusion in Target Recognition

In order to improve target identification capability of the compound detection platform, the system information have been shared by using the cross-layer information fusion, the feature of the environment or the characteristics have been received by different detection platform, and using the characteristics by data link for the detection parameters of wireless sensor networks modified adjusted to improve the performance of the entire detection system by comprehensive utilization of information resources. This article have explored the combined method of the cross-layer information sharing and target identification information and proposed a cross-layer information target recognition fusion algorithm for multi-institutional, multi-layered compound network based on the combination of anti-jamming technology and evidential reasoning. The results of experiment and simulation show that the method not only expand the functionality of the system based on the original detection systems, but also more substantial the target recognition capability of the wireless sensor network, thus improving the detection performance of the compound detection system