It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily ...It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily volumes of sewage.The generation of sewage is the result of multiple factors from the whole social system.Characterized by strong process abstraction ability,data mining techniques have been viewed as promising prediction methods to realize intelligent STP management.However,existing data mining-based methods for this purpose just focus on a single factor such as an economical or meteorological factor and ignore their collaborative effects.To address this challenge,a deep learning-based intelligent management mechanism for STPs is proposed,to predict business volume.Specifically,the grey relation algorithm(GRA) and gated recursive unit network(GRU) are combined into a prediction model(GRAGRU).The GRA is utilized to select the factors that have a significant impact on the sewage business volume,and the GRU is set up to output the prediction results.We conducted a large number of experiments to verify the efficiency of the proposed GRA-GRU model.展开更多
Using cluster state and single qubit measurement one can perform the one-way quantum computation. Here we give a detailed scheme for realizing a modified Grover search algorithm using measurements on cluster state. We...Using cluster state and single qubit measurement one can perform the one-way quantum computation. Here we give a detailed scheme for realizing a modified Grover search algorithm using measurements on cluster state. We give the measurement pattern for the cluster-state realization of the algorithm and estimated the number of measurement needed for its implementation. It is found that O（2^3n/^2n^2） number of single qubit measurements is required for its realization in a cluster-state quantum computer.展开更多
Based on superconducting quantum interference devices （SQUIDs） coupled to a cavity, we propose a scheme for implementing a quantum controlled-phase gate （QPG） and Deutsch-Jozsa （D J） algorithm by a controllable ...Based on superconducting quantum interference devices （SQUIDs） coupled to a cavity, we propose a scheme for implementing a quantum controlled-phase gate （QPG） and Deutsch-Jozsa （D J） algorithm by a controllable interaction. In the present scheme, the SQUID works in the charge regime, and the cavity field is ultilized as quantum data-bus, which is sequentially coupled to only one qubit at a time. The interaction between the selected qubit and the data bus, such as resonant and dispersive interaction, can be realized by turning the gate capacitance of each SQUID. Especially, the bus is not excited and thus the cavity decay is suppressed during the implementation of DJ algorithm. For the QPG operation, the mode of the bus is unchanged in the end of the operation, although its mode is really excited during the operations. Finally, for typical experiment data, we analyze simply the experimental feasibility of the proposed scheme. Based on the simple operation, our scheme may be realized in this solid-state system, and our idea may be realized in other systems.展开更多
基金Project(KJZD-M202000801) supported by the Major Project of Chongqing Municipal Education Commission,ChinaProject(2016YFE0205600) supported by the National Key Research&Development Program of China+1 种基金Project(CXQT19023) supported by the Chongqing University Innovation Group Project,ChinaProjects(KFJJ2018069,1853061,1856033) supported by the Key Platform Opening Project of Chongqing Technology and Business University,China。
文摘It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily volumes of sewage.The generation of sewage is the result of multiple factors from the whole social system.Characterized by strong process abstraction ability,data mining techniques have been viewed as promising prediction methods to realize intelligent STP management.However,existing data mining-based methods for this purpose just focus on a single factor such as an economical or meteorological factor and ignore their collaborative effects.To address this challenge,a deep learning-based intelligent management mechanism for STPs is proposed,to predict business volume.Specifically,the grey relation algorithm(GRA) and gated recursive unit network(GRU) are combined into a prediction model(GRAGRU).The GRA is utilized to select the factors that have a significant impact on the sewage business volume,and the GRU is set up to output the prediction results.We conducted a large number of experiments to verify the efficiency of the proposed GRA-GRU model.
基金the National Fundamental Research Program under Grant No.2006CBOL0106National Natural Science Foundation of China under Grant Nos.10325521 and 60433050+1 种基金the Key Grant Project of the Ministry of Education under Grant No.306020the SRFDP Program of the Ministry of Education
文摘Using cluster state and single qubit measurement one can perform the one-way quantum computation. Here we give a detailed scheme for realizing a modified Grover search algorithm using measurements on cluster state. We give the measurement pattern for the cluster-state realization of the algorithm and estimated the number of measurement needed for its implementation. It is found that O（2^3n/^2n^2） number of single qubit measurements is required for its realization in a cluster-state quantum computer.
基金The project supported by the Natural Science Foundation of Hunan Province under Grant No. 06jj50014, Key Project Foundation of the Education Commission of Hunan Province under Grant No. 06A055 and National Natural Science Foundation of China under Grant No. 10574126
文摘Based on superconducting quantum interference devices （SQUIDs） coupled to a cavity, we propose a scheme for implementing a quantum controlled-phase gate （QPG） and Deutsch-Jozsa （D J） algorithm by a controllable interaction. In the present scheme, the SQUID works in the charge regime, and the cavity field is ultilized as quantum data-bus, which is sequentially coupled to only one qubit at a time. The interaction between the selected qubit and the data bus, such as resonant and dispersive interaction, can be realized by turning the gate capacitance of each SQUID. Especially, the bus is not excited and thus the cavity decay is suppressed during the implementation of DJ algorithm. For the QPG operation, the mode of the bus is unchanged in the end of the operation, although its mode is really excited during the operations. Finally, for typical experiment data, we analyze simply the experimental feasibility of the proposed scheme. Based on the simple operation, our scheme may be realized in this solid-state system, and our idea may be realized in other systems.
