A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this work.Each parameter of PQCs is encoded as a binary string,named as a gene,...A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this work.Each parameter of PQCs is encoded as a binary string,named as a gene,and a genetic-based method is adopted to select the offsprings.The individuals in the offspring are decoded in Gray code way to keep Hamming distance,and then are evaluated to obtain the best one with the lowest cost value in each iteration.The algorithm is performed iteratively for all parameters one by one until the cost value satisfies the stop condition or the number of iterations is reached.The GCO algorithm is demonstrated for classification tasks in Iris and MNIST datasets,and their performance are compared by those with the Bayesian optimization algorithm and binary code based optimization algorithm.The simulation results show that the GCO algorithm can reach high accuracies steadily for quantum classification tasks.Importantly,the GCO algorithm has a robust performance in the noise environment.展开更多
Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple compleme...Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.展开更多
Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unk...Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unknown gray nodes, and the second the evolution gray nodes. The relevant definitions are also given. Further- more, grayness degree in complex networks is described and divided into two forms--the relative grayness degree （RGD） and the absolute grayness degree （AGD）, which are proved respectively.展开更多
Objective To investigate cerebral structural signatures of the bulbar-and spinal-onset amyotrophic lateral sclerosis(ALS) using voxel-based morphometry on magnetic resonance imaging.Methods The MR structural images of...Objective To investigate cerebral structural signatures of the bulbar-and spinal-onset amyotrophic lateral sclerosis(ALS) using voxel-based morphometry on magnetic resonance imaging.Methods The MR structural images of the brain were obtained from 65 ALS patients(15 bulbar-onset, 50 spinalonset) and 65 normal controls(NC) on a 3.0 T MRI system. Gray matter(GM) volume changes were investigated by voxel-based morphometry, and the distribution of the brain regions with volume changes was compared between ALS and normal controls, as well as between bulbar-onset and spinal-onset ALS based on Neuromorphometrics atlas.Results On voxel-level the decreased volume of brain regions in ALS patients was located in the right precentral gyrus(r Prc Gy) and right middle frontal gyrus compared with that in NC. The bulbar-onset ALS presented extramotor cortex atrophy(fronto-temporal pattern), including left medial orbital gyrus, left inferior temporal gyrus and right middle temporal gyrus; the spinal-onset ALS suffered from motor cortex atrophy(r Prc Gy dominance) and extra-motor cortex atrophy(fronto-temporal and extra-fronto-temporal pattern) compared with NC. The spinal-onset ALS featured by GM volume loss of left postcentral gyrus and bulbar-onset ALS featured by GM volume loss of left middle temporal gyrus compared with each other. Conclusions The asymmetric GM atrophy of the motor cortex and extra-motor cortex represents the common MRI structural signatures of spinal-onset ALS, and sole extra-motor cortex atrophy represents the structural signatures of bulbar-onset ALS. The present study also demonstrated that the pattern of GM damage is likely to distribute wider in spinal-onset ALS than in bulbar-onset ALS.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.61871234 and 62375140)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX190900).
文摘A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this work.Each parameter of PQCs is encoded as a binary string,named as a gene,and a genetic-based method is adopted to select the offsprings.The individuals in the offspring are decoded in Gray code way to keep Hamming distance,and then are evaluated to obtain the best one with the lowest cost value in each iteration.The algorithm is performed iteratively for all parameters one by one until the cost value satisfies the stop condition or the number of iterations is reached.The GCO algorithm is demonstrated for classification tasks in Iris and MNIST datasets,and their performance are compared by those with the Bayesian optimization algorithm and binary code based optimization algorithm.The simulation results show that the GCO algorithm can reach high accuracies steadily for quantum classification tasks.Importantly,the GCO algorithm has a robust performance in the noise environment.
基金supported by the National Natural Science Foundation of China under Grant 51567002 and Grant 50767001.
文摘Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.
基金Supported by the National Natural Science Foundation of China(71110307023)~~
文摘Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unknown gray nodes, and the second the evolution gray nodes. The relevant definitions are also given. Further- more, grayness degree in complex networks is described and divided into two forms--the relative grayness degree （RGD） and the absolute grayness degree （AGD）, which are proved respectively.
基金Supported by the grant of the National Natural Sciences Foundation of China(30470512)
文摘Objective To investigate cerebral structural signatures of the bulbar-and spinal-onset amyotrophic lateral sclerosis(ALS) using voxel-based morphometry on magnetic resonance imaging.Methods The MR structural images of the brain were obtained from 65 ALS patients(15 bulbar-onset, 50 spinalonset) and 65 normal controls(NC) on a 3.0 T MRI system. Gray matter(GM) volume changes were investigated by voxel-based morphometry, and the distribution of the brain regions with volume changes was compared between ALS and normal controls, as well as between bulbar-onset and spinal-onset ALS based on Neuromorphometrics atlas.Results On voxel-level the decreased volume of brain regions in ALS patients was located in the right precentral gyrus(r Prc Gy) and right middle frontal gyrus compared with that in NC. The bulbar-onset ALS presented extramotor cortex atrophy(fronto-temporal pattern), including left medial orbital gyrus, left inferior temporal gyrus and right middle temporal gyrus; the spinal-onset ALS suffered from motor cortex atrophy(r Prc Gy dominance) and extra-motor cortex atrophy(fronto-temporal and extra-fronto-temporal pattern) compared with NC. The spinal-onset ALS featured by GM volume loss of left postcentral gyrus and bulbar-onset ALS featured by GM volume loss of left middle temporal gyrus compared with each other. Conclusions The asymmetric GM atrophy of the motor cortex and extra-motor cortex represents the common MRI structural signatures of spinal-onset ALS, and sole extra-motor cortex atrophy represents the structural signatures of bulbar-onset ALS. The present study also demonstrated that the pattern of GM damage is likely to distribute wider in spinal-onset ALS than in bulbar-onset ALS.
