Correlation functions are often employed to quantify the relationships among interdependent variables or sets of data.Recently,a new class of correlation functions,called FORRELATION,has been introduced by Aaronson an...Correlation functions are often employed to quantify the relationships among interdependent variables or sets of data.Recently,a new class of correlation functions,called FORRELATION,has been introduced by Aaronson and Ambainis for studying the query complexity of quantum devices.It was found that there exists a quantum query algorithm solving 2-fold FORRELATION problems with an exponential quantum speedup over all possible classical means,which represents essentially the largest possible separation between quantum and classical query complexities.Here we report an experimental study probing the2-fold and 3-fold FORRELATIONS encoded in nuclear spins.The major experimental challenge is to control the spin fluctuation to within a threshold value,which is achieved by developing a set of optimized GRAPE pulse sequences.Overall,our small-scale implementation indicates that the quantum query algorithm is capable of determining the values of FORRELATIONS within an acceptable accuracy required for demonstrating quantum supremacy,given the current technology and in the presence of experimental noise.展开更多
As weapon system effectiveness is affected by many factors,its evaluation is essentially a multi-criterion decision making problem for its complexity.The evaluation model of the effectiveness is established on the bas...As weapon system effectiveness is affected by many factors,its evaluation is essentially a multi-criterion decision making problem for its complexity.The evaluation model of the effectiveness is established on the basis of metrics architecture of the effectiveness.The Bayesian network,which is used to evaluate the effectiveness,is established based on the metrics architecture and the evaluation models.For getting the weights of the metrics by Bayesian network,subjective initial values of the weights are given,gradient ascent algorithm is adopted,and the reasonable values of the weights are achieved.And then the effectiveness of every weapon system project is gained.The weapon system,whose effectiveness is relative maximum,is the optimization system.The research result shows that this method can solve the problem of AHP method which evaluation results are not compatible to the practice results and overcome the shortcoming of neural network in multilayer and multi-criterion decision.The method offers a new approach for evaluating the effectiveness.展开更多
基金supported by the National Natural Science Foundation of China(11175094,91221205,and 11405093)the National Basic Research Program of China(2015CB921002)
文摘Correlation functions are often employed to quantify the relationships among interdependent variables or sets of data.Recently,a new class of correlation functions,called FORRELATION,has been introduced by Aaronson and Ambainis for studying the query complexity of quantum devices.It was found that there exists a quantum query algorithm solving 2-fold FORRELATION problems with an exponential quantum speedup over all possible classical means,which represents essentially the largest possible separation between quantum and classical query complexities.Here we report an experimental study probing the2-fold and 3-fold FORRELATIONS encoded in nuclear spins.The major experimental challenge is to control the spin fluctuation to within a threshold value,which is achieved by developing a set of optimized GRAPE pulse sequences.Overall,our small-scale implementation indicates that the quantum query algorithm is capable of determining the values of FORRELATIONS within an acceptable accuracy required for demonstrating quantum supremacy,given the current technology and in the presence of experimental noise.
文摘As weapon system effectiveness is affected by many factors,its evaluation is essentially a multi-criterion decision making problem for its complexity.The evaluation model of the effectiveness is established on the basis of metrics architecture of the effectiveness.The Bayesian network,which is used to evaluate the effectiveness,is established based on the metrics architecture and the evaluation models.For getting the weights of the metrics by Bayesian network,subjective initial values of the weights are given,gradient ascent algorithm is adopted,and the reasonable values of the weights are achieved.And then the effectiveness of every weapon system project is gained.The weapon system,whose effectiveness is relative maximum,is the optimization system.The research result shows that this method can solve the problem of AHP method which evaluation results are not compatible to the practice results and overcome the shortcoming of neural network in multilayer and multi-criterion decision.The method offers a new approach for evaluating the effectiveness.
