Quantum Robot: Structure, Algorithms and Applications

A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms including quantum searching algorithm and quantum reinforcement learning are presented for quantum robot. The theoretic results show that quantum robot can reduce the complexity of O(N^2) in traditional robot to O(N^(3/2)) using quantum searching algorithm, and the simulation results demonstrate that quantum robot is also superior to traditional robot in efficient learning by novel quantum reinforcement learning algorithm. Considering the advantages of quantum robot, its some potential important applications are also analyzed and prospected.Comment: 19 pages, 4 figures, 2 table

Investigation of electrical contact resistance for nonconductive film functionalized with Π -conjugated self-assembled molecules

©2007 American Institute of Physics. The electronic version of this article is the complete one and can be found online at: http://link.aip.org/link/?APPLAB/90/092102/1DOI:10.1063/1.2709638Nonconductive adhesive/nonconductive film (NCA/NCF) bonding technology has attracted increasing research interests as lead-free interconnect. During bonding, heat and pressure are applied and the direct physical contacts between the two surfaces of integrated circuit bump and substrate bond pad can be achieved. The electrical contact resistance of a NCA/NCF joint is controlled by the pressure, roughness and NCA/NCF material properties. An accurate prediction of contact resistance can help guide experiment setup towards improving the electrical performance of NCA/NCF. In this study, a model is developed and correlated to experiments. The effects of NCA/NCF material properties on electrical contact resistance are investigated

Sectional normalization and recognization on the PV-Diagram of reciprocating compressor

The shortcomings of familiar normalization method on the PV-Diagram of reciprocating compressor are analyzed in the paper. A sectional normalization method of the PV-Diagram was put forward, and a recognizing technique of fault characteristics based on support vector machines for cylinder and piston system in reciprocating compressor is introduced. Four sections of curve in the PV-Diagram indicate four stages of a gas compression cycle. After the PV-Diagram is normalized with the new method, the curvilinear curvatures are unchanged in comparison with the original diagram. The contour and shape relations between normal and fault state character curves are retained. The pressure signals collected from cylinder are normalized and treated as characteristic vectors, and the vectors are inputted into a multi-class classifier composed of many support vector machines in order to classify fault modes. The experimental results show that the method can identify faults of the cylinder and piston system more correctly

Constraining the cosmological parameters using gravitational wave observations of massive black hole binaries and statistical redshift information

Space-borne gravitational wave detectors like TianQin are expected to detect GW signals emitted by the mergers of massive black hole binaries. Luminosity distance information can be obtained from GW observations, and one can perform cosmological inference if redshift information can also be extracted, which would be straightforward if an electromagnetic counterpart exists. In this paper, we concentrate on the conservative scenario where the EM counterparts are not available, and comprehensively study if cosmological parameters can be inferred through a statistical approach, utilizing the non-uniform distribution of galaxies as well as the black hole mass-host galaxy bulge luminosity relationship. By adopting different massive black hole binary merger models, and assuming different detector configurations, we conclude that the statistical inference of cosmological parameters is indeed possible. TianQin is expected to constrain the Hubble constant to a relative error of about 4%-7%, depending on the underlying model. The multidetector network of TianQin and LISA can significantly improve the precision of cosmological parameters. In the most favorable model, it is possible to achieve a level of 1.7% with a network of TianQin and LISA. We find that without EM counterparts, constraints on all other parameters need a larger number of events or more precise sky localization of GW sources, which can be achieved by the multidetector network or under a favorable model for massive black hole mergers. However, in the optimistic case, where EM counterparts are available, one can obtain useful constraints on all cosmological parameters in the Lambda-CDM cosmology, regardless of the population model. Moreover, we can also constrain the equation of state of the dark energy without the EM counterparts, and it is even possible to study the evolution of EoS of the DE when the EM counterparts are observed.Comment: 34 pages, 17 figures, update to match published versio

Control of non-controllable quantum systems: A quantum control algorithm based on Grover iteration

A new notion of controllability, eigenstate controllability, is defined for finite-dimensional bilinear quantum mechanical systems which are neither strongly completely controllably nor completely controllable. And a quantum control algorithm based on Grover iteration is designed to perform a quantum control task of steering a system, which is eigenstate controllable but may not be (strongly) completely controllable, from an arbitrary state to a target state.Comment: 7 pages, no figures, submitte