The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate be...The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.展开更多
Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment thr...Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.展开更多
It is important to specify the occurrence and cause of failure of machines without stopping the machines because of increased use of various complex industrial systems. In this study, two new diagnosis methods based o...It is important to specify the occurrence and cause of failure of machines without stopping the machines because of increased use of various complex industrial systems. In this study, two new diagnosis methods based on the correlation information between sound and vibration emitted from the machine are derived. First, a diagnostic method which can detect the part of machine with fault among the assumed several faults is proposed by measuring simultaneously the time series data on sound and vibration. Next, a diagnosis method based on the estimation of the changing information of correlation between sound and vibration is considered by using prior information in only normal situation. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.展开更多
We investigate the information exclusion principle for multiple measurements with assistance of multiple quantum memories that are well bounded by the upper and lower bounds.The lower bound depends on the observables&...We investigate the information exclusion principle for multiple measurements with assistance of multiple quantum memories that are well bounded by the upper and lower bounds.The lower bound depends on the observables'complementarity and the complementarity of uncertainty whilst the upper bound includes the complementarity of the observables,quantum discord,and quantum condition entropy.In quantum measurement processing,there exists a relationship between the complementarity of uncertainty and the complementarity of information.In addition,based on the information exclusion principle the complementarity of uncertainty and the shareability of quantum discord can exist as an essential factor to enhance the bounds of each other in the presence of quantum memory.展开更多
In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an ada...In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an adaptive temporal-spatial information fusion model is proposed.Firstly,an adaptive evaluation correction mechanism is constructed by the evidence distance and Deng entropy,which realizes the credibility discrimination and adaptive correction of the spatial evidence.Secondly,the credibility decay operator is introduced to obtain the dynamic credibility of temporal evidence.Finally,the sequential combination of temporal-spatial evidences is achieved by Shafer’s discount criterion and Dempster’s combination rule.The simulation results show that the proposed method not only considers the dynamic and sequential characteristics of the temporal-spatial evidences com-bination,but also has a strong conflict information processing capability,which provides a new refer-ence for the field of temporal-spatial information fusion.展开更多
A strong and stable correlation in quantum information is of high quality for quantum information processing.We define two quantities,selective average correlation and ripple coefficient,to evaluate the quality of cor...A strong and stable correlation in quantum information is of high quality for quantum information processing.We define two quantities,selective average correlation and ripple coefficient,to evaluate the quality of correlation in quantum information in a time interval.As a new communication channel,Heisenberg spin chains are widely investigated.We select a two-qubit Heisenberg XXZs pin chain with Dzyaloshinskii-Moriya interaction in an inhomogeneous magnetic field as an example,and use the two quantities to evaluate the qualities of the correlation in quantum information with different measures.The result shows that,if the time evolutions are similar,there needs only evaluating one of them to know when the correlation has high quality for quantum information processing.展开更多
Smart city is the development of digital city; as its main supporting technology, the digital city geo-spatial framework has to be upgraded to the temporal-spatial information infrastructure (TSII). first, this paper ...Smart city is the development of digital city; as its main supporting technology, the digital city geo-spatial framework has to be upgraded to the temporal-spatial information infrastructure (TSII). first, this paper proposes the concept and basic framework of smart city and defines the concept of TSII - processes, integration, mining analysis, and share time-stamps geographic data - and the related policy, regulations and standards, technology, facilities, mechanism, and human resources. The framework has four components: the benchmark of time and space, temporal-spatial big data, the cloud service platform and the related supporting environment. Second, the temporal-spatial big data and cloud service platform are elaborated. finally, an application of TSII constructed by the Xicheng District Planning Bureau in Beijing is introduced, which provides a useful reference for the construction of smart city.展开更多
The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree...The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.展开更多
From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each other.Therefore,all these leads report different aspects of an arrhythmia.Their difference...From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each other.Therefore,all these leads report different aspects of an arrhythmia.Their differences lie in the level of highlighting and displaying information about that arrhythmia.For example,although all leads show traces of atrial excitation,this function is more evident in lead II than in any other lead.In this article,a new model was proposed using ECG functional and structural dependencies between heart leads.In the prescreening stage,the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed manner.The mutual information indices were used to assess the relationship between leads.In order to calculate mutual information,the correlation between the 12 ECG leads has been calculated.The output of this step is a matrix containing all mutual information.Furthermore,to calculate the structural information of ECG signals,a capsule neural network was implemented to aid physicians in the automatic classification of cardiac arrhythmias.The architecture of this capsule neural network has been modified to perform the classification task.In the experimental results section,the proposed model was used to classify arrhythmias in ECG signals from the Chapman dataset.Numerical evaluations showed that this model has a precision of 97.02%,recall of 96.13%,F1-score of 96.57%and accuracy of 97.38%,indicating acceptable performance compared to other state-of-the-art methods.The proposed method shows an average accuracy of 2%superiority over similar works.展开更多
To address the limitation of single acceleration sensor signals in effectively reflecting the health status of rolling bearings,a rolling bearing fault diagnosis method based on the fusion of data-level and feature-le...To address the limitation of single acceleration sensor signals in effectively reflecting the health status of rolling bearings,a rolling bearing fault diagnosis method based on the fusion of data-level and feature-level information was proposed.First,according to the impact characteristics of rolling bearing faults,correlation kurtosis rules were designed to guide the weight distribution of multi-sensor signals.These rules were then combined with a weighted fusion method to obtain high-quality data-level fusion signals.Subsequently,a feature-fusion convolutional neural network(FFCNN)that merges the one-dimensional(1D)features extracted from the fused signal with the two-dimensional(2D)features extracted from the wavelet time-frequency spectrum was designed to obtain a comprehensive representation of the health status of rolling bearings.Finally,the fused features were fed into a Softmax classifier to complete the fault diagnosis.The results show that the proposed method exhibits an average test accuracy of over 99.00%on the two rolling bearing fault datasets,outperforming other comparison methods.Thus,the method can be effectively utilized for diagnosing rolling bearing faults.展开更多
To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be rob...To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be robust to imperfect CSI.A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed.The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI.Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance.In addition,the effect of spatial correlation on the performance of the proposed algorithm is also simulated.展开更多
Wave mixing and the intricate optical interactions therein have traditionally been regarded as hallmarks of nonlinear optics.A quintessential example of wave mixing lies in the nonlocal triple correlation between the ...Wave mixing and the intricate optical interactions therein have traditionally been regarded as hallmarks of nonlinear optics.A quintessential example of wave mixing lies in the nonlocal triple correlation between the pump beam and the generated twin photons via spontaneous parametric down-conversion(SPDC).However,the SPDC process typically requires intense laser pumping and suffers from inherently low conversion efficiencies,necessitating single-photon detection.In this work,we establish that analogous triple correlations can be effectively produced using low-power continuous-wave illumination,achieved through a commercially available spatial light modulator(SLM)in a linear optical configuration.Specifically,we show how to spatially manipulate and customize this triple correlation and further investigate the applicability across diverse domains,including pattern recognition,intelligent nonlocal image processing,and sensitivity-enhanced optical metrology.Our findings establish,to our knowledge,a novel framework for classical,linear emulation of quantum and nonlinear optical information processing paradigms rooted in multi-wave mixing.展开更多
On the basis of information theory and statistical methods, we use mutual information, n- tuple entropy and conditional entropy, combined with biological characteristics, to analyze the long range correlation and shor...On the basis of information theory and statistical methods, we use mutual information, n- tuple entropy and conditional entropy, combined with biological characteristics, to analyze the long range correlation and short range correlation in human Y chromosome palindromes. The magnitude distribution of the long range correlation which can be reflected by the mutual information is PS〉PSa〉PSb （P5a and P5b are the sequences that replace solely Alu repeats and all interspersed repeats with random uneorrelated sequences in human Y chromosome palindrome 5, respectively）; and the magnitude distribution of the short range correlation which can be reflected by the n-tuple entropy and the conditional entropy is PS〉P5a〉PSb〉random uncorrelated sequence. In other words, when the Alu repeats and all interspersed repeats replace with random uneorrelated sequence, the long range and short range correlation decrease gradually. However, the random nncorrelated sequence has no correlation. This research indicates that more repeat sequences result in stronger correlation between bases in human Y chromosome. The analyses may be helpful to understand the special structures of human Y chromosome palindromes profoundly.展开更多
We derive explicit expressions for quantum discord and classical correlation for an X structure density matrix. Based on the characteristics of the expressions, the quantum discord and the classical correlation are ea...We derive explicit expressions for quantum discord and classical correlation for an X structure density matrix. Based on the characteristics of the expressions, the quantum discord and the classical correlation are easily obtained and compared under different initial conditions using a novel analytical method. We explain the relationships among quantum discord, classical correlation, and entanglement, and further find that the quantum discord is not always larger than the entanglement measured by concurrence in a general two-qubit X state. The new method, which is different from previous approaches, has certain guiding significance for analysing quantum discord and classical correlation of a two-qubit X state, such as a mixed state.展开更多
By establishing the Markov model for a long-range correlated time series （LRCS） and analysing its evolutionary characteristics, this paper defines a physical effective correlation length （ECL） T, which reflects th...By establishing the Markov model for a long-range correlated time series （LRCS） and analysing its evolutionary characteristics, this paper defines a physical effective correlation length （ECL） T, which reflects the predictability of the LRCS. It also finds that the ECL has a better power law relation with the long-range correlated exponent γ of the LRCS： T = Kexp（-γ/0.3） ＋ Y, （0 〈 γ〈 1） the predictability of the LRCS decays exponentially with the increase of γ It is then applied to a daily maximum temperature series （DMTS） recorded at 740 stations in China between the years 1960-2005 and calculates the ECL of the DMTS. The results show the remarkable regional distributive feature that the ECL is about 10-14 days in west, northwest and northern China, and about 5-10 days in east, southeast and southern China. Namely, the predictability of the DMTS is higher in central-west China than in east and southeast China. In addition, the ECL is reduced by 1-8 days in most areas of China after subtracting the seasonal oscillation signal of the DMTS from its original DMTS; however, it is only slightly altered when the decadal linear trend is removed from the original DMTS. Therefore, it is shown that seasonal oscillation is a significant component of daily maximum temperature evolution and may provide a basis for predicting daily maximum temperatures. Seasonal oscillation is also significant for guiding general weather predictions, as well as seasonal weather predictions.展开更多
Coronavirus disease 2019(COVID-19)is continuing to spread globally and still poses a great threat to human health.Since its outbreak,it has had catastrophic effects on human society.A visual method of analyzing COVID-...Coronavirus disease 2019(COVID-19)is continuing to spread globally and still poses a great threat to human health.Since its outbreak,it has had catastrophic effects on human society.A visual method of analyzing COVID-19 case information using spatio-temporal objects with multi-granularity is proposed based on the officially provided case information.This analysis reveals the spread of the epidemic,from the perspective of spatio-temporal objects,to provide references for related research and the formulation of epidemic prevention and control measures.The case information is abstracted,descripted,represented,and analyzed in the form of spatio-temporal objects through the construction of spatio-temporal case objects,multi-level visual expressions,and spatial correlation analysis.The rationality of the method is verified through visualization scenarios of case information statistics for China,Henan cases,and cases related to Shulan.The results show that the proposed method is helpful in the research and judgment of the development trend of the epidemic,the discovery of the transmission law,and the spatial traceability of the cases.It has a good portability and good expansion performance,so it can be used for the visual analysis of case information for other regions and can help users quickly discover the potential knowledge this information contains.展开更多
文摘The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.
基金partially supported by the National Key Research and Development Project under Grant 2020YFB1806805Science and Technology on Communication Networks Laboratorysupported by China Scholarship Council.
文摘Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.
文摘It is important to specify the occurrence and cause of failure of machines without stopping the machines because of increased use of various complex industrial systems. In this study, two new diagnosis methods based on the correlation information between sound and vibration emitted from the machine are derived. First, a diagnostic method which can detect the part of machine with fault among the assumed several faults is proposed by measuring simultaneously the time series data on sound and vibration. Next, a diagnosis method based on the estimation of the changing information of correlation between sound and vibration is considered by using prior information in only normal situation. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.
基金the National Natural Science Foundation of China(Grant Nos.12271394,11775040,12011530014)the Natural Science Foundation of Shanxi Province+3 种基金China(Grant Nos.201801D221032 and 201801D121016)the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2019L0178)the Key Research and Development Program of Shanxi Province(Grant No.202102010101004)the China Scholarship Council。
文摘We investigate the information exclusion principle for multiple measurements with assistance of multiple quantum memories that are well bounded by the upper and lower bounds.The lower bound depends on the observables'complementarity and the complementarity of uncertainty whilst the upper bound includes the complementarity of the observables,quantum discord,and quantum condition entropy.In quantum measurement processing,there exists a relationship between the complementarity of uncertainty and the complementarity of information.In addition,based on the information exclusion principle the complementarity of uncertainty and the shareability of quantum discord can exist as an essential factor to enhance the bounds of each other in the presence of quantum memory.
基金the National Natural Science Foundation of China(No.61976080)the Key Project on Research and Practice of Henan University Graduate Education and Teaching Reform(YJSJG2023XJ006)+1 种基金the Key Research and Development Projects of Henan Province(231111212500)the Henan University Graduate Education Innovation and Quality Improvement Program(SYLKC2023016).
文摘In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an adaptive temporal-spatial information fusion model is proposed.Firstly,an adaptive evaluation correction mechanism is constructed by the evidence distance and Deng entropy,which realizes the credibility discrimination and adaptive correction of the spatial evidence.Secondly,the credibility decay operator is introduced to obtain the dynamic credibility of temporal evidence.Finally,the sequential combination of temporal-spatial evidences is achieved by Shafer’s discount criterion and Dempster’s combination rule.The simulation results show that the proposed method not only considers the dynamic and sequential characteristics of the temporal-spatial evidences com-bination,but also has a strong conflict information processing capability,which provides a new refer-ence for the field of temporal-spatial information fusion.
基金Supported by the National Natural Science Foundation of China(11075013,11375025)
文摘A strong and stable correlation in quantum information is of high quality for quantum information processing.We define two quantities,selective average correlation and ripple coefficient,to evaluate the quality of correlation in quantum information in a time interval.As a new communication channel,Heisenberg spin chains are widely investigated.We select a two-qubit Heisenberg XXZs pin chain with Dzyaloshinskii-Moriya interaction in an inhomogeneous magnetic field as an example,and use the two quantities to evaluate the qualities of the correlation in quantum information with different measures.The result shows that,if the time evolutions are similar,there needs only evaluating one of them to know when the correlation has high quality for quantum information processing.
文摘Smart city is the development of digital city; as its main supporting technology, the digital city geo-spatial framework has to be upgraded to the temporal-spatial information infrastructure (TSII). first, this paper proposes the concept and basic framework of smart city and defines the concept of TSII - processes, integration, mining analysis, and share time-stamps geographic data - and the related policy, regulations and standards, technology, facilities, mechanism, and human resources. The framework has four components: the benchmark of time and space, temporal-spatial big data, the cloud service platform and the related supporting environment. Second, the temporal-spatial big data and cloud service platform are elaborated. finally, an application of TSII constructed by the Xicheng District Planning Bureau in Beijing is introduced, which provides a useful reference for the construction of smart city.
基金supported by the National Natural Science Foundation of China(NSFC) under Grant No. 50775083 and Grant No.50721005
文摘The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.
文摘From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each other.Therefore,all these leads report different aspects of an arrhythmia.Their differences lie in the level of highlighting and displaying information about that arrhythmia.For example,although all leads show traces of atrial excitation,this function is more evident in lead II than in any other lead.In this article,a new model was proposed using ECG functional and structural dependencies between heart leads.In the prescreening stage,the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed manner.The mutual information indices were used to assess the relationship between leads.In order to calculate mutual information,the correlation between the 12 ECG leads has been calculated.The output of this step is a matrix containing all mutual information.Furthermore,to calculate the structural information of ECG signals,a capsule neural network was implemented to aid physicians in the automatic classification of cardiac arrhythmias.The architecture of this capsule neural network has been modified to perform the classification task.In the experimental results section,the proposed model was used to classify arrhythmias in ECG signals from the Chapman dataset.Numerical evaluations showed that this model has a precision of 97.02%,recall of 96.13%,F1-score of 96.57%and accuracy of 97.38%,indicating acceptable performance compared to other state-of-the-art methods.The proposed method shows an average accuracy of 2%superiority over similar works.
基金The National Natural Science Foundation of China(No.U22A20178)National Key Research and Development Program of China(No.2022YFB3404800)Jiangsu Province Science and Technology Achievement Transformation Special Fund Program(No.BA2023019).
文摘To address the limitation of single acceleration sensor signals in effectively reflecting the health status of rolling bearings,a rolling bearing fault diagnosis method based on the fusion of data-level and feature-level information was proposed.First,according to the impact characteristics of rolling bearing faults,correlation kurtosis rules were designed to guide the weight distribution of multi-sensor signals.These rules were then combined with a weighted fusion method to obtain high-quality data-level fusion signals.Subsequently,a feature-fusion convolutional neural network(FFCNN)that merges the one-dimensional(1D)features extracted from the fused signal with the two-dimensional(2D)features extracted from the wavelet time-frequency spectrum was designed to obtain a comprehensive representation of the health status of rolling bearings.Finally,the fused features were fed into a Softmax classifier to complete the fault diagnosis.The results show that the proposed method exhibits an average test accuracy of over 99.00%on the two rolling bearing fault datasets,outperforming other comparison methods.Thus,the method can be effectively utilized for diagnosing rolling bearing faults.
基金the National Natural Science Foundationof China(No.60572156)
文摘To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be robust to imperfect CSI.A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed.The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI.Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance.In addition,the effect of spatial correlation on the performance of the proposed algorithm is also simulated.
基金National Natural Science Foundation of China(12274037,11735005,11654003,61675028)Science and Technology Development Fund from Macao SAR(FDCT)(0105/2023/RIA2)Interdiscipline Research Funds of Beijing Normal University。
文摘Wave mixing and the intricate optical interactions therein have traditionally been regarded as hallmarks of nonlinear optics.A quintessential example of wave mixing lies in the nonlocal triple correlation between the pump beam and the generated twin photons via spontaneous parametric down-conversion(SPDC).However,the SPDC process typically requires intense laser pumping and suffers from inherently low conversion efficiencies,necessitating single-photon detection.In this work,we establish that analogous triple correlations can be effectively produced using low-power continuous-wave illumination,achieved through a commercially available spatial light modulator(SLM)in a linear optical configuration.Specifically,we show how to spatially manipulate and customize this triple correlation and further investigate the applicability across diverse domains,including pattern recognition,intelligent nonlocal image processing,and sensitivity-enhanced optical metrology.Our findings establish,to our knowledge,a novel framework for classical,linear emulation of quantum and nonlinear optical information processing paradigms rooted in multi-wave mixing.
基金This work was supported by the National Natu- ral Science Foundation of China （No.20173023 and No.90203012） and the Specialized Research Fund for the Doctoral Program of Higher Education of China （No.20020730006）.
文摘On the basis of information theory and statistical methods, we use mutual information, n- tuple entropy and conditional entropy, combined with biological characteristics, to analyze the long range correlation and short range correlation in human Y chromosome palindromes. The magnitude distribution of the long range correlation which can be reflected by the mutual information is PS〉PSa〉PSb （P5a and P5b are the sequences that replace solely Alu repeats and all interspersed repeats with random uneorrelated sequences in human Y chromosome palindrome 5, respectively）; and the magnitude distribution of the short range correlation which can be reflected by the n-tuple entropy and the conditional entropy is PS〉P5a〉PSb〉random uncorrelated sequence. In other words, when the Alu repeats and all interspersed repeats replace with random uneorrelated sequence, the long range and short range correlation decrease gradually. However, the random nncorrelated sequence has no correlation. This research indicates that more repeat sequences result in stronger correlation between bases in human Y chromosome. The analyses may be helpful to understand the special structures of human Y chromosome palindromes profoundly.
基金supported by the Natural Science Foundation of Hunan Province of China (Grant No. 09JJ6011)the Natural Science Foundation of Education Department of Hunan Province, China (Grant Nos. 08A055 and 07C528)
文摘We derive explicit expressions for quantum discord and classical correlation for an X structure density matrix. Based on the characteristics of the expressions, the quantum discord and the classical correlation are easily obtained and compared under different initial conditions using a novel analytical method. We explain the relationships among quantum discord, classical correlation, and entanglement, and further find that the quantum discord is not always larger than the entanglement measured by concurrence in a general two-qubit X state. The new method, which is different from previous approaches, has certain guiding significance for analysing quantum discord and classical correlation of a two-qubit X state, such as a mixed state.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.40930952,40875040,and 41005043)the Special Project for Public Welfare Enterprises(Grant No.GYHY200806005)the National Science/Technology Support Program of China(Grant Nos.2007BAC29B01 and 2009BAC51B04)
文摘By establishing the Markov model for a long-range correlated time series （LRCS） and analysing its evolutionary characteristics, this paper defines a physical effective correlation length （ECL） T, which reflects the predictability of the LRCS. It also finds that the ECL has a better power law relation with the long-range correlated exponent γ of the LRCS： T = Kexp（-γ/0.3） ＋ Y, （0 〈 γ〈 1） the predictability of the LRCS decays exponentially with the increase of γ It is then applied to a daily maximum temperature series （DMTS） recorded at 740 stations in China between the years 1960-2005 and calculates the ECL of the DMTS. The results show the remarkable regional distributive feature that the ECL is about 10-14 days in west, northwest and northern China, and about 5-10 days in east, southeast and southern China. Namely, the predictability of the DMTS is higher in central-west China than in east and southeast China. In addition, the ECL is reduced by 1-8 days in most areas of China after subtracting the seasonal oscillation signal of the DMTS from its original DMTS; however, it is only slightly altered when the decadal linear trend is removed from the original DMTS. Therefore, it is shown that seasonal oscillation is a significant component of daily maximum temperature evolution and may provide a basis for predicting daily maximum temperatures. Seasonal oscillation is also significant for guiding general weather predictions, as well as seasonal weather predictions.
基金National Key Research and Development Program of China,No.2016YFB0502300。
文摘Coronavirus disease 2019(COVID-19)is continuing to spread globally and still poses a great threat to human health.Since its outbreak,it has had catastrophic effects on human society.A visual method of analyzing COVID-19 case information using spatio-temporal objects with multi-granularity is proposed based on the officially provided case information.This analysis reveals the spread of the epidemic,from the perspective of spatio-temporal objects,to provide references for related research and the formulation of epidemic prevention and control measures.The case information is abstracted,descripted,represented,and analyzed in the form of spatio-temporal objects through the construction of spatio-temporal case objects,multi-level visual expressions,and spatial correlation analysis.The rationality of the method is verified through visualization scenarios of case information statistics for China,Henan cases,and cases related to Shulan.The results show that the proposed method is helpful in the research and judgment of the development trend of the epidemic,the discovery of the transmission law,and the spatial traceability of the cases.It has a good portability and good expansion performance,so it can be used for the visual analysis of case information for other regions and can help users quickly discover the potential knowledge this information contains.
