Decoherence of quantum gates based on Aharonov-Anandan phases in a multistep scheme

We study quantum decoherence of single-qubit and two-qubit Aharonov-Anandan (AA) geometric phase gates realized in a multistep scheme. Each AA gate is also compared with the dynamical phase gate performing the same unitary transformation within the same time period and coupled with the same environment, which is modeled as harmonic oscillators. It is found that the fidelities and the entanglement protection of the AA phase gates are enhanced by the states being superpositions of different eigenstates of the environmental coupling, and the noncommutativity between the qubit interaction and the environmental coupling.Comment: 7 pages, published in EP

The Realization of a Stochastic Optimization Model for the Empty Container Inventory Based on EDI Information

This paper explores the feasibility of realizing the optimization of the empty container inventory based on EDI information. Firstly the basic structure of the stochastic optimization model for the empty container inventory has been described and two models including the infinite and finite horizon model were constructed. Then several statistical test have been taken and the distribution of the inland turnover time of the empty container, the empty containers\u27 supply and demand identified. Finally we adopt PB to develop the DSS for the stochastic optimization of container inventory based on the shipping EDI information

A Study on the RAPD and SCAR Molecular Markers of Piper Species

In order to compare the genetic relationships among Kava, Pepper and it’s wild relatives and to distinguish Kava from Pepper and it’s wild relatives, we conducted research on Kava by using RAPD and SCAR molecular markers. 20 random primers selected from 80 random primers were used for RAPD amplification to identify the genetic relationships among Kava, Pepper and it’s wild relatives. Total 170 bands were amplified by 20 random primers, in which 20 bands were polymorphic (12%). Cluster analysis grouped the 28 accessions into six groups at similarity coefficient of 0.36, where 6 materials of Kava formed a group, indicating that Kava was distantly relation to Pepper and its wild relatives. Kava had 562 bp and 355 bp specific fragments amplified by primers OPQ- 02 and OPQ-03, respectively, were recycled for cloning and sequencing analysis, and then converted to SCAR markers. Two pairs of specific SCAR primers for Kava, P4.1 and P4.2, P8.1 and P8.2 were designed. PCR amplification of 28 test materials were performed using the two pairs of the specific primers respectively, the specific bands of 562 bp and 355 bp with expected sizes were amplified in 6 Kava materials but not in other materials. The results showed that primers P4.1 and P4.2, P8.1 and P8.2 might be used as specific SCAR primers for Kava germplasm resources identification. This research provided the basis for selecting rootstocks, molecular identification and the fingerprint construction of Kava

Carrier-phase based real-time static and kinematic precise point positioning Using GPS and GALILEO

Over the last few years, there has been a rising demand for sub-metre accuracy (and higher) for navigation and surveying using signals from Global Navigation Satellite Systems (GNSS). To meet this rising demand, many precise positioning techniques and algorithms using the carrier-phase observable have been developed. Currently, high accuracy Real-Time Kinematic (RTK) positioning is possible using relative or differential techniques which require one GNSS user receiver and at least one other as the reference (known) station within a certain distance from the user. Unlike these conventional differential positioning techniques, Precise Point Positioning (PPP) is based on processing carrier phase observations from only one GNSS receiver. This is more cost-effective as it removes the need for reference receivers and therefore, is not limited by baseline length. However, errors mitigated by ‘differencing’ in conventional methods must be modelled accurately and reliably for PPP. This thesis develops a PPP software platform in Matlab code and uses it to investigate the state-of-the-art PPP algorithms and develop enhancements. Specifically, it is well documented that conventional PPP algorithms suffer from long convergence periods ranging from thirty minutes (for static users) to hours (for dynamic users). Therefore, to achieve fast convergence, two approaches are developed in this thesis. Firstly, a combination of the state-of-the-art GNSS error models and new algorithms for measurement weighting, management of receiver clock jumps and assignment of a dynamic covariance factor, are exploited. Secondly, based on the results of the analysis of the quantitative relationships between the PPP convergence and each of the residual measurement noise level and satellite geometry, a strategy for the selection of satellites (GPS and GALILEO) for PPP is developed and exploited. Tests using 24 hours of real data show that the two developments above contribute to the realisation of static PPP positioning accuracies of 40 cm (3D, 100%) within a convergence time of 20 minutes. Furthermore, based on simulated data, the same accuracy is achieved in kinematic mode but within a convergence time of one hour. These levels of performance represent significant improvements over the state-of-the-art (i.e. convergence time of twenty minutes instead of thirty for static users and one hour instead of hours for dynamic users). The potential of the use of multiple frequencies from modernised GPS and GALILEO on float ambiguity PPP is demonstrated with simulated data, and shown to have the potential to offer significant improvement in the availability of PPP in difficult user environments such as urban areas. Finally, the thesis addresses the potential application of PPP for mission (e.g. safety critical) applications and the need for integrity monitoring. An existing Carrier-phase Receiver Autonomous Integrity Monitoring (CRAIM) algorithm is implemented and shown to have the potential to protect PPP users against abnormally large errors