The transfer of the quantum correlation from two-mode nonclassical state field to the supercurrents in two distant SQUID rings

We have considered two distant mesoscopic superconducting quantum interference device （SQUID） rings A and B in the presence of two-mode nonclassical state fields and investigated the correlation of the supercurrents in the two rings using the normalized correlation function CAB. We show that when the parameter c~ is very small for the separable state with the density matrix ρ = {│α,-α） （α,-α│ ＋ │-α, α） （-α, α│}/2 and entangled coherent state {（ECS） [u） = N1（│α, -α） ＋ │-α, α）} fields, the dynamic behaviours of the normalized correlation function CAB are similar, but it is quite different for the entangled coherent state │u＇） = N2（│α,-α） - │-α, α）} field. When the parameter α is very large, the dynamic behaviours of CAB are almost the same for the separable state, entangled coherent state │u） and [u＇〉 fields. For the two-mode squeezed vacuum state field the maximum of CAB increases monotonically with the squeezing parameter γ, and as γ→ ∞ , CAB→ 1. This means that the supercurrents in the two rings A and B are quantum mechanically correlated perfectly. It is concluded that not all the quantum correlations in the two-mode nonclassical state field can be transferred to the supercurrents; and the transfer depends on the state of the two-mode nonclassical state field prepared.

A Method of Calculating the 3D Coordinates on a Micro Object in a Virtual Micro-Operation System

A simple method for calculating the 3D coordinates of points on a micro object in a multi camera system is proposed. It simplifies the algorithms used in traditional computer vision system by eliminating the calculation of the CCD (charge coupled device) camera parameters and the relative position between cameras, and using solid geometry in the calculation procedures instead of the calculation of the complex matrixes. The algorithm was used in the research of generating a virtual magnified 3D image of a micro object to be operated in a micro operation system, and the satisfactory results were obtained. The application in a virtual tele operation system for a dexterous mechanical gripper is under test.

Super-resolution microscopy based on parallel detection

Image scanning microscopy based on pixel reassignment can improve the confocal resolution limit without losing the image signal-to-noise ratio(SNR)greatly[C.J.R.Sheppard,"Super resolution in confocal imaging,"Optik 80(2)53-54(1988).C.B.Miller,E.Jorg,"Image scanning microscopy,"Phys.Reu.Lett.104(19)198101(2010).C.J.R.Sheppard,s.B.Mehta,R Heintzmann,"Superresolution by image scanning microscopy using pixel reassignment,"Opt.Lett.38(15)28892892(2013)].Here,we use a tailor-made optical fiber and 19 avalanche pho-todiodes(APDs)as parallel detectors to upgrade our existing confocal microscopy,termed as parallel-detection super resolution(PDSR)microscopy.In order to obtain the correct shift value,we use the normalized 2D cross correlation to calculate the shifting value of each image.We characterized our system performance by imaging fuorescence beads and applied this system to observing the 3D structure of biological specimen.

Adaptive Radial Based Sampling for Reliability and Reliability Sensitivity Analysis Involving Truncated Correlated Normal Variables

The reliability and reliability sensitivity （ RS ） models are presented for the engineering problem involving truncated correlated normal variables （CNV）, and in the case an adaptive radial based sampling is used to analyze the reliability and the RS. In the presented models, the truncated CNV is transformed to general CNV, and the value domains of the truncated CNV are treated as multiple failure modes, then the reliability and the RS with the truncated CNV are transformed to the general cases, on which an e^cient radial based sampling is used to analyze the trans- formed reliability and RS. An adaptive strategy is employed to search for the optimal radial in the sampling, by which the robustness of the method is improved. After the model concepts and the detailed implementation are given, several examples are presented to demonstrate the feasibility of the model and the efficiency of the solutions.

Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching

In order to improve the low positioning accuracy and execution efficiency of the robot binocular vision,a binocular vision positioning method based on coarse-fine stereo matching is proposed to achieve object positioning.The random fern is used in the coarse matching to identify objects in the left and right images,and the pixel coordinates of the object center points in the two images are calculated to complete the center matching.In the fine matching,the right center point is viewed as an estimated value to set the search range of the right image,in which the region matching is implemented to find the best matched point of the left center point.Then,the similar triangle principle of the binocular vision model is used to calculate the 3D coordinates of the center point,achieving fast and accurate object positioning.Finally,the proposed method is applied to the object scene images and the robotic arm grasping platform.The experimental results show that the average absolute positioning error and average relative positioning error of the proposed method are 8.22 mm and 1.96%respectively when the object's depth distance is within 600 mm,the time consumption is less than 1.029s.The method can meet the needs of the robot grasping system,and has better accuracy and robustness.