Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detec...Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.展开更多
Quantum mechanics provides a disembodied way to transfer quantum information from one quantum object to another.In theory,this quantum information transfer can occur between quantum objects of any dimension,yet the re...Quantum mechanics provides a disembodied way to transfer quantum information from one quantum object to another.In theory,this quantum information transfer can occur between quantum objects of any dimension,yet the reported experiments of quantum information transfer to date have mainly focused on the cases where the quantum objects have the same dimension.Here,we theoretically propose and experimentally demonstrate a scheme for quantum information transfer between quantum objects of different dimensions.By using an optical qubit-ququart entangling gate,we observe the transfer of quantum information between two photons with different dimensions,including the flow of quantum information from a four-dimensional photon to a twodimensional photon and vice versa.The fidelities of the quantum information transfer range from 0.700 to 0.917,all above the classical limit of 2/3.Our work sheds light on a new direction for quantum information transfer and demonstrates our ability to implement entangling operations beyond two-level quantum systems.展开更多
The Einstein–Podolsky–Rosen(EPR)paradox is one of the milestones in quantum foundations,arising from the lack of a local realistic description of quantum mechanics.The EPR paradox has stimulated an important concept...The Einstein–Podolsky–Rosen(EPR)paradox is one of the milestones in quantum foundations,arising from the lack of a local realistic description of quantum mechanics.The EPR paradox has stimulated an important concept of“quantum nonlocality,”which manifests itself in three types:quantum entanglement,quantum steering,and Bell’s nonlocality.Although Bell’s nonlocality is more often used to show“quantum nonlocality,”the original EPR paradox is essentially a steering paradox.In this work,we formulate the original EPR steering paradox into a contradiction equality,thus making it amenable to experimental verification.We perform an experimental test of the steering paradox in a two-qubit scenario.Furthermore,by starting from the steering paradox,we generate a generalized linear steering inequality and transform this inequality into a mathematically equivalent form,which is friendlier for experimental implementation,i.e.,one may measure the observables only in the x,y,or z axis of the Bloch sphere,rather than other arbitrary directions.We also perform experiments to demonstrate this scheme.Within the experimental errors,the experimental results coincide with theoretical predictions.Our results deepen the understanding of quantum foundations and provide an efficient way to detect the steerability of quantum states.展开更多
基金This study was supported by the National Natural Science Foundation of China(No.61861007)Guizhou ProvincialDepartment of Education Innovative Group Project(QianJiaohe KY[2021]012)Guizhou Science and Technology Plan Project(Guizhou Science Support[2023]General 412).
文摘Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.
基金National Natural Science Foundation of China(61974168)Special Project for Research and Development in Key Areas of Guangdong Province(2018B030329001,2018B030325001)National Key Research and Development Program of China(2017YFA0305200,2016YFA0301300)。
文摘Quantum mechanics provides a disembodied way to transfer quantum information from one quantum object to another.In theory,this quantum information transfer can occur between quantum objects of any dimension,yet the reported experiments of quantum information transfer to date have mainly focused on the cases where the quantum objects have the same dimension.Here,we theoretically propose and experimentally demonstrate a scheme for quantum information transfer between quantum objects of different dimensions.By using an optical qubit-ququart entangling gate,we observe the transfer of quantum information between two photons with different dimensions,including the flow of quantum information from a four-dimensional photon to a twodimensional photon and vice versa.The fidelities of the quantum information transfer range from 0.700 to 0.917,all above the classical limit of 2/3.Our work sheds light on a new direction for quantum information transfer and demonstrates our ability to implement entangling operations beyond two-level quantum systems.
基金National Key Research and Development Program of China(2017YFA0305200,2016YFA0301300)National Natural Science Foundation of China(11875167,12075001,12075245,61974168)+1 种基金Key R&D Program of Guangdong Province(2018B030325001,2018B030329001)Xiaoxiang Scholars Programme of Hunan Normal University.
文摘The Einstein–Podolsky–Rosen(EPR)paradox is one of the milestones in quantum foundations,arising from the lack of a local realistic description of quantum mechanics.The EPR paradox has stimulated an important concept of“quantum nonlocality,”which manifests itself in three types:quantum entanglement,quantum steering,and Bell’s nonlocality.Although Bell’s nonlocality is more often used to show“quantum nonlocality,”the original EPR paradox is essentially a steering paradox.In this work,we formulate the original EPR steering paradox into a contradiction equality,thus making it amenable to experimental verification.We perform an experimental test of the steering paradox in a two-qubit scenario.Furthermore,by starting from the steering paradox,we generate a generalized linear steering inequality and transform this inequality into a mathematically equivalent form,which is friendlier for experimental implementation,i.e.,one may measure the observables only in the x,y,or z axis of the Bloch sphere,rather than other arbitrary directions.We also perform experiments to demonstrate this scheme.Within the experimental errors,the experimental results coincide with theoretical predictions.Our results deepen the understanding of quantum foundations and provide an efficient way to detect the steerability of quantum states.