已有的跨句多元关系抽取工作将输入文本表示为集成句内和句间依赖关系的复杂文档图,但图中包含的噪声信息会影响关系抽取的效果。针对这种情况,该文利用Graph state LSTM获得上下文信息,再分别利用词级注意力机制或位置感知的注意力机制...已有的跨句多元关系抽取工作将输入文本表示为集成句内和句间依赖关系的复杂文档图,但图中包含的噪声信息会影响关系抽取的效果。针对这种情况,该文利用Graph state LSTM获得上下文信息,再分别利用词级注意力机制或位置感知的注意力机制,自动聚焦在对关系抽取起到决定性作用的关键词上,降低噪声信息的影响。并且比较了两种注意力机制对使用Graph state LSTM进行关系抽取的影响。通过在一个重要的精确医学数据集上进行实验,验证了该文所提出模型的有效性。展开更多
We propose feasible experimental schemes for preparing all five-photon graph states. Our schemes require only linear optical elements, photon detectors and post-selection, which are available in current experiment so ...We propose feasible experimental schemes for preparing all five-photon graph states. Our schemes require only linear optical elements, photon detectors and post-selection, which are available in current experiment so that these schemes are within the reach of the current technology.展开更多
In this paper, a scheme for generating various multiatom entangled graph states via resonant interactions is proposed. We investigate the generation of various four-atom graph states first in the ideal case and then i...In this paper, a scheme for generating various multiatom entangled graph states via resonant interactions is proposed. We investigate the generation of various four-atom graph states first in the ideal case and then in the case in which the cavity decay and atomic spontaneous emission are taken into consideration in the process of interaction. More importantly, we improve the possible distortion of the graph states coming from cavity decay and atomic spontaneous emission by performing appropriate unitary transforms on atoms. The generation of multiatom entangled graph states is very important for constructing quantum one-way computer in a fault-tolerant manner. The resonant interaction time is very short, which is important in the sense of decoherence. Our scheme is easy and feasible within the reach of current experimental technology.展开更多
We propose feasible schemes for preparation of all five-atom graph states by cavity quantum electrodynamics （QED）. Our schemes require only the atom-cavity interaction with a large detuning which is available in cur...We propose feasible schemes for preparation of all five-atom graph states by cavity quantum electrodynamics （QED）. Our schemes require only the atom-cavity interaction with a large detuning which is available in current experiment so that these schemes are within the reach of the current technology.展开更多
Graph states are special multipartite entangled states that have been proven useful in a variety of quantum information tasks. We address the issue of characterizing and quantifying the genuine multipartite entangleme...Graph states are special multipartite entangled states that have been proven useful in a variety of quantum information tasks. We address the issue of characterizing and quantifying the genuine multipartite entanglement of graph states up to eight qubits. The entanglement measures used are the geometric measure, the relative entropy of entanglement, and the logarithmic robustness, have been proved to be equal for the genuine entanglement of a graph state. We provide upper and lower bounds as well as an iterative algorithm to determine the genuine multipartite entanglement.展开更多
We study the spin squeezing property of weighted graph states,which can be used to improve sensitivity in interferometry.We study the time evolution of spin squeezing under local decoherence acting independently on ea...We study the spin squeezing property of weighted graph states,which can be used to improve sensitivity in interferometry.We study the time evolution of spin squeezing under local decoherence acting independently on each qubit.Based on the analysis,the spin squeezing of the weighted graph states is somehow robust in the presence of decoherence and the decoherence limit in the improvement of the interferometric sensitivity is still achievable.Furthermore,one can obtain the optimal improvement of sensitivity by tuning the weighted of each edges of the weighted graph state.展开更多
We propose a scheme for generating multi-ion graph states using many trapped ions in thermal motion.Our generation scheme is insensitive to external state since the interaction between ions and laser fields does not i...We propose a scheme for generating multi-ion graph states using many trapped ions in thermal motion.Our generation scheme is insensitive to external state since the interaction between ions and laser fields does not involvethe external degree of freedom.The scheme can be well realized within the current experimental technique.展开更多
The numbers of local complimentary inequivalent graph states for 9, 10 and 11 qubit systems are 440, 3132, 40457, respectively. We calculate the entanglement, the lower and upper bounds of the entanglement and obtain ...The numbers of local complimentary inequivalent graph states for 9, 10 and 11 qubit systems are 440, 3132, 40457, respectively. We calculate the entanglement, the lower and upper bounds of the entanglement and obtain the closest product states for all these graph states. New patterns of closest product states are analyzed.展开更多
We exactly evaluate the entanglement of a six vertex and a nine vertex graph states which correspond to non ＂two-colorable＂ graphs. The upper bound of entanglement for five vertex ring graph state is improved to 2.9...We exactly evaluate the entanglement of a six vertex and a nine vertex graph states which correspond to non ＂two-colorable＂ graphs. The upper bound of entanglement for five vertex ring graph state is improved to 2.9275, less than the upper bound determined by local operations and classical communication. An upper bound of entanglement is proposed based on the definition of graph state.展开更多
Quantum many-body problem(QMBP)has become a hot topic in high energy physics and condensed matter physics.With the exponential increasing of the dimension of the Hilbert space,it becomes a big challenge to solve the Q...Quantum many-body problem(QMBP)has become a hot topic in high energy physics and condensed matter physics.With the exponential increasing of the dimension of the Hilbert space,it becomes a big challenge to solve the QMBP even with the most powerful computers.With the rapid development of machine learning,artificial neural networks provide a powerful tool to represent or approximate quantum many-body states.In this paper,we aim to construct explicitly the neural network representations of graph states,without stochastic optimization of the network parameters.Our method shows constructively that all graph states can be represented precisely by proper neural networks originated from[Science,355,602(2017)]and formulated in[Sci.China-Phys.Mech.Astron.,63,210312(2020)].展开更多
Equipment has dual nature: physical objects existing in nature, and artificial objects designed by human. The decision on the configuration and structural parameters of equipment is made by engineers based on technica...Equipment has dual nature: physical objects existing in nature, and artificial objects designed by human. The decision on the configuration and structural parameters of equipment is made by engineers based on technical-physical effects which control the behavioral parameters of the equipment. Sensors are mounted on the equipment to monitor the equipment state. Current methods for state monitoring and diagnosis mostly use mathematics and artificial intelligence technology to construct evaluation methods. This paper presents an integrated design and state maintenance method, in which graph and dual graph are used for recording design data and sensor arrangement and for mapping method from signals to substructures and connection pairs. An example of state maintenance of hydro power generating equipment is illustrated.展开更多
针对高比例新能源并网下光伏集群功率预测面临的复杂空间关联量化建模、功率波动空间传播及技术异质性表征等挑战,该文提出一种基于图状态空间模型(graph state space model,GSSM)的短期同预测方法。首先,通过可学习权重自适应融合光伏...针对高比例新能源并网下光伏集群功率预测面临的复杂空间关联量化建模、功率波动空间传播及技术异质性表征等挑战,该文提出一种基于图状态空间模型(graph state space model,GSSM)的短期同预测方法。首先,通过可学习权重自适应融合光伏电站的地理邻近性、技术相似性与电气耦合性构建多尺度图,精准量化电站间动态关联;其次,建立连续时间状态空间方程,显式引入图扩散项,以物理驱动方式刻画气象扰动在集群中的连续传播过程;最后,利用选择性扫描机制,依据气象特征与电站元数据动态调整模型参数,增强对瞬态气象事件的响应能力,并通过多步预测器完成光伏集群的短期协同预测。基于公开数据集PVOD的实验与算例分析表明,GSSM方法在训练效率、预测精度及稳定性上均显著优于长短时记忆(long short-term memory,LSTM)网络、时空图卷积网络(spatio-temporal graph convolutional networks,STGCN)等基线模型方法,并能有效适应异质性光伏集群场景。该研究可为电网调度提供有力技术支持,助力高比例新能源系统安全运行。展开更多
现有复杂网络关键节点识别方法中缺少对节点本身特征的研究,存在网络拓扑信息提取不全面、特征冗余、泛化性低等问题.为了解决上述问题,本文提出一种基于图结构学习的复杂网络关键节点识别方法.首先,针对网络拓扑信息提取不全面问题,结...现有复杂网络关键节点识别方法中缺少对节点本身特征的研究,存在网络拓扑信息提取不全面、特征冗余、泛化性低等问题.为了解决上述问题,本文提出一种基于图结构学习的复杂网络关键节点识别方法.首先,针对网络拓扑信息提取不全面问题,结合复杂网络微观结构和宏观结构构造节点特征;其次,针对特征冗余问题,提出一个融合选择性状态空间模型(State Space Models)和自监督学习的节点特征提取方法;最后,针对泛化性低问题,利用图结构学习在模型训练层面优化损失函数提高分类精度.利用4个公开数据集上进行了广泛实验,本文方法优于次优方法4.66%,节点分辨率保持稳定.实验表明,所提出方法能有效的识别不同网络的关键节点.展开更多
随着分布式新能源、可控资源等新型元素接入配电网,传统状态估计模型面临量测信息不全、配电网拓扑变化频繁和负荷时序性波动等新问题,模型估计精度降低。针对该问题,文中提出一种融合改进生成对抗与图注意力网络的配电网状态估计方法...随着分布式新能源、可控资源等新型元素接入配电网,传统状态估计模型面临量测信息不全、配电网拓扑变化频繁和负荷时序性波动等新问题,模型估计精度降低。针对该问题,文中提出一种融合改进生成对抗与图注意力网络的配电网状态估计方法。首先,选取不同的历史时间断面,利用拓扑参数和量测信息生成数据集,通过将双向长短期记忆网络引入生成对抗网络填补数据中的缺失量测信息;其次,利用图注意力网络自适应地捕捉节点间的空间动态关系,利用双向长短期记忆(bidirectional long short-term memory,BiLSTM)网络充分挖掘不同时间断面序列信息的时间耦合关系,拼接形成关于量测量到状态量的时空特征表达,得到改进图神经网络状态估计模型;最后,在IEEE 118节点系统中进行仿真实验,并与卷积神经网络、图注意力网络等算法进行对比。结果表明,文中所提算法在数据缺失和拓扑时变情况下具有更优的估计效果。展开更多
First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computat...First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computational effort(its computing time complexity is O(en_l),where e is the number of edges and n_l is the number of leaves)and shorter resulting expression.Second,based on it an exact decomposition algorithm for finding communication network overallreliability is presented by applying the hypergraph theory.If we use it to carry out the m-timedecomposition of a network graph,the communication network scale which can be analyzed by acomputer can be extended to m-fold.展开更多
文摘已有的跨句多元关系抽取工作将输入文本表示为集成句内和句间依赖关系的复杂文档图,但图中包含的噪声信息会影响关系抽取的效果。针对这种情况,该文利用Graph state LSTM获得上下文信息,再分别利用词级注意力机制或位置感知的注意力机制,自动聚焦在对关系抽取起到决定性作用的关键词上,降低噪声信息的影响。并且比较了两种注意力机制对使用Graph state LSTM进行关系抽取的影响。通过在一个重要的精确医学数据集上进行实验,验证了该文所提出模型的有效性。
文摘We propose feasible experimental schemes for preparing all five-photon graph states. Our schemes require only linear optical elements, photon detectors and post-selection, which are available in current experiment so that these schemes are within the reach of the current technology.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 60678022 and 10704001)the Specialized Research Fund for the Doctoral Program of Higher Education, China (Grant No 20060357008)+2 种基金Anhui Provincial Natural Science Foundation, China (Grant No 070412060)the Key Program of the Education Department of Anhui Province, China (Grant Nos KJ2008A28ZC, KJ2008B83ZC, KJ2008B265 and KJ2007B082)the Talent Foundation of Anhui University, China,and the Anhui Key Laboratory of Information Materials and Devices (Anhui University), China
文摘In this paper, a scheme for generating various multiatom entangled graph states via resonant interactions is proposed. We investigate the generation of various four-atom graph states first in the ideal case and then in the case in which the cavity decay and atomic spontaneous emission are taken into consideration in the process of interaction. More importantly, we improve the possible distortion of the graph states coming from cavity decay and atomic spontaneous emission by performing appropriate unitary transforms on atoms. The generation of multiatom entangled graph states is very important for constructing quantum one-way computer in a fault-tolerant manner. The resonant interaction time is very short, which is important in the sense of decoherence. Our scheme is easy and feasible within the reach of current experimental technology.
文摘We propose feasible schemes for preparation of all five-atom graph states by cavity quantum electrodynamics （QED）. Our schemes require only the atom-cavity interaction with a large detuning which is available in current experiment so that these schemes are within the reach of the current technology.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.60972071 and 11375152)
文摘Graph states are special multipartite entangled states that have been proven useful in a variety of quantum information tasks. We address the issue of characterizing and quantifying the genuine multipartite entanglement of graph states up to eight qubits. The entanglement measures used are the geometric measure, the relative entropy of entanglement, and the logarithmic robustness, have been proved to be equal for the genuine entanglement of a graph state. We provide upper and lower bounds as well as an iterative algorithm to determine the genuine multipartite entanglement.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11004029 and 11174052)the Natural Science Foundation of Jiangsu Province of China (Grant No. BK2010422)+2 种基金the Ph. D. Program of the Ministry of Education of Chinathe Excellent Young Teachers Program of Southeast Universitythe National Basic Research Development Program of China(Grant No. 2011CB921203)
文摘We study the spin squeezing property of weighted graph states,which can be used to improve sensitivity in interferometry.We study the time evolution of spin squeezing under local decoherence acting independently on each qubit.Based on the analysis,the spin squeezing of the weighted graph states is somehow robust in the presence of decoherence and the decoherence limit in the improvement of the interferometric sensitivity is still achievable.Furthermore,one can obtain the optimal improvement of sensitivity by tuning the weighted of each edges of the weighted graph state.
基金National Natural Science Foundation of China under Grant Nos.60678022 and 10704001the Specialized Research Fund for the Doctoral Program of Higher Education of Anhui Province under Grant No.20060357008+2 种基金Natural Science Foundation of Anhui Province under Grant No.070412060the Talent Foundation of Anhui UniversityAnhui Key Laboratory of Information Materials and Devices (Anhui University)
文摘We propose a scheme for generating multi-ion graph states using many trapped ions in thermal motion.Our generation scheme is insensitive to external state since the interaction between ions and laser fields does not involvethe external degree of freedom.The scheme can be well realized within the current experimental technique.
文摘The numbers of local complimentary inequivalent graph states for 9, 10 and 11 qubit systems are 440, 3132, 40457, respectively. We calculate the entanglement, the lower and upper bounds of the entanglement and obtain the closest product states for all these graph states. New patterns of closest product states are analyzed.
文摘We exactly evaluate the entanglement of a six vertex and a nine vertex graph states which correspond to non ＂two-colorable＂ graphs. The upper bound of entanglement for five vertex ring graph state is improved to 2.9275, less than the upper bound determined by local operations and classical communication. An upper bound of entanglement is proposed based on the definition of graph state.
基金Supported by the National Natural Science Foundation of China (Grant Nos.12001480,11871318)Applied Basic Research Program of Shanxi Province (Grant No.201901D211461)+2 种基金Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi (Grant No.2020L0554)Excellent Doctoral Research Pro ject of Shanxi Province (Grant No.QZX-2020001)PhD Start-up Pro ject of Yuncheng University (Grant No.YQ-2019021)。
文摘Quantum many-body problem(QMBP)has become a hot topic in high energy physics and condensed matter physics.With the exponential increasing of the dimension of the Hilbert space,it becomes a big challenge to solve the QMBP even with the most powerful computers.With the rapid development of machine learning,artificial neural networks provide a powerful tool to represent or approximate quantum many-body states.In this paper,we aim to construct explicitly the neural network representations of graph states,without stochastic optimization of the network parameters.Our method shows constructively that all graph states can be represented precisely by proper neural networks originated from[Science,355,602(2017)]and formulated in[Sci.China-Phys.Mech.Astron.,63,210312(2020)].
基金the National Natural Science Foundation of China(No.51175284)
文摘Equipment has dual nature: physical objects existing in nature, and artificial objects designed by human. The decision on the configuration and structural parameters of equipment is made by engineers based on technical-physical effects which control the behavioral parameters of the equipment. Sensors are mounted on the equipment to monitor the equipment state. Current methods for state monitoring and diagnosis mostly use mathematics and artificial intelligence technology to construct evaluation methods. This paper presents an integrated design and state maintenance method, in which graph and dual graph are used for recording design data and sensor arrangement and for mapping method from signals to substructures and connection pairs. An example of state maintenance of hydro power generating equipment is illustrated.
文摘针对高比例新能源并网下光伏集群功率预测面临的复杂空间关联量化建模、功率波动空间传播及技术异质性表征等挑战,该文提出一种基于图状态空间模型(graph state space model,GSSM)的短期同预测方法。首先,通过可学习权重自适应融合光伏电站的地理邻近性、技术相似性与电气耦合性构建多尺度图,精准量化电站间动态关联;其次,建立连续时间状态空间方程,显式引入图扩散项,以物理驱动方式刻画气象扰动在集群中的连续传播过程;最后,利用选择性扫描机制,依据气象特征与电站元数据动态调整模型参数,增强对瞬态气象事件的响应能力,并通过多步预测器完成光伏集群的短期协同预测。基于公开数据集PVOD的实验与算例分析表明,GSSM方法在训练效率、预测精度及稳定性上均显著优于长短时记忆(long short-term memory,LSTM)网络、时空图卷积网络(spatio-temporal graph convolutional networks,STGCN)等基线模型方法,并能有效适应异质性光伏集群场景。该研究可为电网调度提供有力技术支持,助力高比例新能源系统安全运行。
文摘现有复杂网络关键节点识别方法中缺少对节点本身特征的研究,存在网络拓扑信息提取不全面、特征冗余、泛化性低等问题.为了解决上述问题,本文提出一种基于图结构学习的复杂网络关键节点识别方法.首先,针对网络拓扑信息提取不全面问题,结合复杂网络微观结构和宏观结构构造节点特征;其次,针对特征冗余问题,提出一个融合选择性状态空间模型(State Space Models)和自监督学习的节点特征提取方法;最后,针对泛化性低问题,利用图结构学习在模型训练层面优化损失函数提高分类精度.利用4个公开数据集上进行了广泛实验,本文方法优于次优方法4.66%,节点分辨率保持稳定.实验表明,所提出方法能有效的识别不同网络的关键节点.
文摘随着分布式新能源、可控资源等新型元素接入配电网,传统状态估计模型面临量测信息不全、配电网拓扑变化频繁和负荷时序性波动等新问题,模型估计精度降低。针对该问题,文中提出一种融合改进生成对抗与图注意力网络的配电网状态估计方法。首先,选取不同的历史时间断面,利用拓扑参数和量测信息生成数据集,通过将双向长短期记忆网络引入生成对抗网络填补数据中的缺失量测信息;其次,利用图注意力网络自适应地捕捉节点间的空间动态关系,利用双向长短期记忆(bidirectional long short-term memory,BiLSTM)网络充分挖掘不同时间断面序列信息的时间耦合关系,拼接形成关于量测量到状态量的时空特征表达,得到改进图神经网络状态估计模型;最后,在IEEE 118节点系统中进行仿真实验,并与卷积神经网络、图注意力网络等算法进行对比。结果表明,文中所提算法在数据缺失和拓扑时变情况下具有更优的估计效果。
文摘First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computational effort(its computing time complexity is O(en_l),where e is the number of edges and n_l is the number of leaves)and shorter resulting expression.Second,based on it an exact decomposition algorithm for finding communication network overallreliability is presented by applying the hypergraph theory.If we use it to carry out the m-timedecomposition of a network graph,the communication network scale which can be analyzed by acomputer can be extended to m-fold.
