LIU Tianle, XU Xiao, FU Bowei, XU Jiaxin, LIU Jingyang, ZHOU Xingyu, WANG Qin
The parameter configuration of Quantum Key Distribution (QKD) has a great impact on the communication effect, and in the practical application of the QKD network in the future, it is necessary to quickly realize the parameter configuration optimization of the asymmetric channel Measurement-Device-Independent QKD according to the communication state, so as to ensure the good communication effect of the mobile users, which is an inevitable requirement for real-time quantum communication. Aiming at the problem that the traditional QKD parameter optimization configuration scheme cannot guarantee real-time, this paper proposes to apply the supervised machine learning algorithm to the QKD parameter optimization configuration, and predict the optimal parameters of TF-QKD and MDI-QKD under different conditions through the machine learning model. First, we delineated the range of system parameters and evenly spaced (linear or logarithmic) values through experimental experience. Then, use the traditional Local Search Algorithm(LSA) to obtain the optimal parameters and take them as the optimal parameters in this paper. Finally, we train various machine learning models based on the above data and compare their performance. We compare the supervised regression learning models such as Neural Network, KNeighbors, Random Forest, Gradient Tree Boosting and Classification And Regression Tree (CART), and the results show that the CART decision tree model has the best performance on the regression evaluation index, and the average value of the key rate (of the prediction parameters) and the optimal key rate ratio is about 0.995, which can meet the communication needs in the actual environment. At the same time, the CART decision tree model shows good environmental robustness in the residual analysis of asymmetric QKD protocol. In addition, compared with the traditional scheme, the new scheme based on CART decision tree has greatly improved the real-time performance of computing, shortening the single prediction time of the optimal parameters of different environments to the order of microseconds, which well meets the real-time communication needs of the communicator in the mobile state. This paper mainly focuses on the parameter optimization of Discrete Variable QKD (DV QKD). In recent years, the development of Continuous Variable QKD (CV QKD) is also rapid. At the end of the paper, we briefly introduce the academic attempts to apply machine learning to the parameter optimization of CV QKD system. And discusses the applicability of the scheme in this paper to the CV QKD system.
{"title":"Parameter optimization of Measurement-Device-Independent Quantum Key Distribution based on regression decision tree","authors":"LIU Tianle, XU Xiao, FU Bowei, XU Jiaxin, LIU Jingyang, ZHOU Xingyu, WANG Qin","doi":"10.7498/aps.72.20230160","DOIUrl":"https://doi.org/10.7498/aps.72.20230160","url":null,"abstract":"The parameter configuration of Quantum Key Distribution (QKD) has a great impact on the communication effect, and in the practical application of the QKD network in the future, it is necessary to quickly realize the parameter configuration optimization of the asymmetric channel Measurement-Device-Independent QKD according to the communication state, so as to ensure the good communication effect of the mobile users, which is an inevitable requirement for real-time quantum communication. Aiming at the problem that the traditional QKD parameter optimization configuration scheme cannot guarantee real-time, this paper proposes to apply the supervised machine learning algorithm to the QKD parameter optimization configuration, and predict the optimal parameters of TF-QKD and MDI-QKD under different conditions through the machine learning model. First, we delineated the range of system parameters and evenly spaced (linear or logarithmic) values through experimental experience. Then, use the traditional Local Search Algorithm(LSA) to obtain the optimal parameters and take them as the optimal parameters in this paper. Finally, we train various machine learning models based on the above data and compare their performance. We compare the supervised regression learning models such as Neural Network, KNeighbors, Random Forest, Gradient Tree Boosting and Classification And Regression Tree (CART), and the results show that the CART decision tree model has the best performance on the regression evaluation index, and the average value of the key rate (of the prediction parameters) and the optimal key rate ratio is about 0.995, which can meet the communication needs in the actual environment. At the same time, the CART decision tree model shows good environmental robustness in the residual analysis of asymmetric QKD protocol. In addition, compared with the traditional scheme, the new scheme based on CART decision tree has greatly improved the real-time performance of computing, shortening the single prediction time of the optimal parameters of different environments to the order of microseconds, which well meets the real-time communication needs of the communicator in the mobile state. This paper mainly focuses on the parameter optimization of Discrete Variable QKD (DV QKD). In recent years, the development of Continuous Variable QKD (CV QKD) is also rapid. At the end of the paper, we briefly introduce the academic attempts to apply machine learning to the parameter optimization of CV QKD system. And discusses the applicability of the scheme in this paper to the CV QKD system.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83529590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Qi, Dai Yue, Li Fei-Yan, Zhang Biao, Li Hao-Chen, Tan Jing-Rou, Wang Xiao-Han, He Guang-Long, Fei Yue, Wang Hao, Zhang La-Bao, Kang Lin, Chen Jian, Wu Pei-heng
High-performance mid-wave and long-wave infrared single-photon detectors not only have significant research value in the fields of infrared astronomy and defense technology, but are also challenging to be realized in the field of single-photon detection technology. Superconducting nanowire single-photon detectors (SNSPDs) have shown excellent performance in the near-infrared band. However, how to further improve the cutoff wavelength λc is a topic of widespread concern. In this paper, the method for improving λc by applying the regulation of the superconducting disorder is discussed, and a detector with an operating wavelength band of 5 - 10 μm is designed and fabricated. Studies have shown that the multiplication and diffusion behaviors of the quasiparticles always occur during the photon detection events, although the microscopic photodetection mechanism of SNSPD still lacks a perfect theoretical explanation. Therefore, the theoretical analysis mainly considers the influence of the quasiparticles in this paper, and the mathematical formula of the detection cutoff wavelength λc can be obtained based on the phenomenological quasiparticle diffusion model. Furthermore, the disorder-dependent superconducting phase transition temperature Tc, superconducting energy gap D, and electron thermalization time τth are also considered, in order to get more precise results.Theoretical analysis suggests that the increase in the sheet resistance Rs, which evaluates the disorder strength, will help to increase λc. For example, when the nanowire width is kept at 30 nm and Rs > 380 Ω/□, it can be deduced that λc is larger than 10 μm.Experimentally, the active area of the device consists of a straight superconducting nanowire with a length of 10 μm and a width of 30 nm, so that it can effectively reduce the probability of the defects on the nanowire and avoid the current crowding effect. We have fabricated a 30 nm-wide Mo0.8Si0.2 mid infrared SNSPD, which has a cutoff wavelength λc no more than 5 μm, the effective strength of the disorder - the film sheet resistance Rs = 248.6 Ω/□. As a comparison, the sheet resistance, which is controlled by the film thickness, is increased to about 320 Ω/□ in this experiment.It is demonstrated that the Mo0.8Si0.2 detector with Rs ~320 Ω/□ can achieve saturated quantum efficiency at a wavelength of 6 μm. Furthermore, 53% quantum efficiency at the wavelength of 10.2 μm can be obtained when the detector works at a bias current of 0.9 ISW (ISW is the superconducting transition current), and it can theoretically reach a maximum value of 92% if the compression of switching current is excluded. Therefore, it can be predicted that the disorder regulation may become another efficient approach for designing high-performance mid-wave and long-wave infrared SNSPDs, in addition to the optimization of the superconducting energy gap and the cross section of superconducting nanowire.However, the continuous increase in the disorder will cause a d
{"title":"Design and fabrication of the superconducting single-photon detector operating at the 5 - 10 micrometer wavelength band","authors":"Chen Qi, Dai Yue, Li Fei-Yan, Zhang Biao, Li Hao-Chen, Tan Jing-Rou, Wang Xiao-Han, He Guang-Long, Fei Yue, Wang Hao, Zhang La-Bao, Kang Lin, Chen Jian, Wu Pei-heng","doi":"10.7498/aps.72.20221594","DOIUrl":"https://doi.org/10.7498/aps.72.20221594","url":null,"abstract":"High-performance mid-wave and long-wave infrared single-photon detectors not only have significant research value in the fields of infrared astronomy and defense technology, but are also challenging to be realized in the field of single-photon detection technology. Superconducting nanowire single-photon detectors (SNSPDs) have shown excellent performance in the near-infrared band. However, how to further improve the cutoff wavelength λc is a topic of widespread concern. In this paper, the method for improving λc by applying the regulation of the superconducting disorder is discussed, and a detector with an operating wavelength band of 5 - 10 μm is designed and fabricated. Studies have shown that the multiplication and diffusion behaviors of the quasiparticles always occur during the photon detection events, although the microscopic photodetection mechanism of SNSPD still lacks a perfect theoretical explanation. Therefore, the theoretical analysis mainly considers the influence of the quasiparticles in this paper, and the mathematical formula of the detection cutoff wavelength λc can be obtained based on the phenomenological quasiparticle diffusion model. Furthermore, the disorder-dependent superconducting phase transition temperature Tc, superconducting energy gap D, and electron thermalization time τth are also considered, in order to get more precise results.Theoretical analysis suggests that the increase in the sheet resistance Rs, which evaluates the disorder strength, will help to increase λc. For example, when the nanowire width is kept at 30 nm and Rs > 380 Ω/□, it can be deduced that λc is larger than 10 μm.Experimentally, the active area of the device consists of a straight superconducting nanowire with a length of 10 μm and a width of 30 nm, so that it can effectively reduce the probability of the defects on the nanowire and avoid the current crowding effect. We have fabricated a 30 nm-wide Mo0.8Si0.2 mid infrared SNSPD, which has a cutoff wavelength λc no more than 5 μm, the effective strength of the disorder - the film sheet resistance Rs = 248.6 Ω/□. As a comparison, the sheet resistance, which is controlled by the film thickness, is increased to about 320 Ω/□ in this experiment.It is demonstrated that the Mo0.8Si0.2 detector with Rs ~320 Ω/□ can achieve saturated quantum efficiency at a wavelength of 6 μm. Furthermore, 53% quantum efficiency at the wavelength of 10.2 μm can be obtained when the detector works at a bias current of 0.9 ISW (ISW is the superconducting transition current), and it can theoretically reach a maximum value of 92% if the compression of switching current is excluded. Therefore, it can be predicted that the disorder regulation may become another efficient approach for designing high-performance mid-wave and long-wave infrared SNSPDs, in addition to the optimization of the superconducting energy gap and the cross section of superconducting nanowire.However, the continuous increase in the disorder will cause a d","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90589201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhang Pu-Du, Wang Wei-Quan, Li Zhe-Min, Zhang Zi-Xuan, Wang Ye-Chen, Zhou Hong-Yu, Yin Yan
Laser-driven ion acceleration has potential applications in high energy density matter, ion beam-driven fast ignition, beam target neutron source and warm dense matter heating and etc. Ultrashort relativistic lasers interacting with solid targets can generate ion beams with energies up to several hundreds of MeV, and the quality of the ion beams strongly depends on the interaction parameters of the laser and the targets. Developments in deep learning can provide new methods in the analysis of relationship between parameters in physics systems, which can significantly reduce the computational and experimental cost. In this paper, a continuous mapping model of ion peak and cutoff energies is developed based on a fully connected neural network(FCNN). In the model, the dataset is composed of nearly 400 sets of particle simulations of laser-driven solid targets, and the input parameters are laser intensity, target density, target thickness and ion mass. The model obtains the parameter analysis results in a large range of values with sparser parameter taking values, which greatly reduces the computational effort of sweeping the parameters in a large range of multi-dimensional parameters. Based on the results of this model mapping, the correction formula for the ion peak energy over ion mass is obtained. Furthermore, the ratio of ion cutoff energy and peak energy of each set of particle simulation is calculated. Repeating the same training process of ion peak energy and cutoff energy, the continuous mapping model of energy ratio is developed. According to the energy ratio model mapping results, the quantitative description of the relationship between ion cutoff energy and peak energy is realized, and the fitting formula for the cutoff energy of the Hole-Boring Radiation Pressure Acceleration (HB-RPA) mechanism is obtained, which can provide an important reference for the laser-driven ion acceleration experiments design.
{"title":"Deep Learning-Based Hole-Boring Radiation Pressure Ion Acceleration Modeling","authors":"Zhang Pu-Du, Wang Wei-Quan, Li Zhe-Min, Zhang Zi-Xuan, Wang Ye-Chen, Zhou Hong-Yu, Yin Yan","doi":"10.7498/aps.72.20230702","DOIUrl":"https://doi.org/10.7498/aps.72.20230702","url":null,"abstract":"Laser-driven ion acceleration has potential applications in high energy density matter, ion beam-driven fast ignition, beam target neutron source and warm dense matter heating and etc. Ultrashort relativistic lasers interacting with solid targets can generate ion beams with energies up to several hundreds of MeV, and the quality of the ion beams strongly depends on the interaction parameters of the laser and the targets. Developments in deep learning can provide new methods in the analysis of relationship between parameters in physics systems, which can significantly reduce the computational and experimental cost. In this paper, a continuous mapping model of ion peak and cutoff energies is developed based on a fully connected neural network(FCNN). In the model, the dataset is composed of nearly 400 sets of particle simulations of laser-driven solid targets, and the input parameters are laser intensity, target density, target thickness and ion mass. The model obtains the parameter analysis results in a large range of values with sparser parameter taking values, which greatly reduces the computational effort of sweeping the parameters in a large range of multi-dimensional parameters. Based on the results of this model mapping, the correction formula for the ion peak energy over ion mass is obtained. Furthermore, the ratio of ion cutoff energy and peak energy of each set of particle simulation is calculated. Repeating the same training process of ion peak energy and cutoff energy, the continuous mapping model of energy ratio is developed. According to the energy ratio model mapping results, the quantitative description of the relationship between ion cutoff energy and peak energy is realized, and the fitting formula for the cutoff energy of the Hole-Boring Radiation Pressure Acceleration (HB-RPA) mechanism is obtained, which can provide an important reference for the laser-driven ion acceleration experiments design.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90636821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tao Chen-Yu, Lei Jian-Ting, Yu Xuan, Luo Yan, Ma Xin-wen, Zhang Shao-Feng
In the past two decades,the development of laser technology has made attosecond science become a cutting-edge research field,providing various novel perspectives for the study of quantum few-body ultrafast evolution.The attosecond pulses prepared in the current laboratory are widely used in experimental research in the form of isolated pulses or pulse trains.The ultrafast changing light field allows people to control and track the motion of electrons at the atomic-scale,and realizes real-time tracking of electron dynamics on the sub-femtosecond time-scale.This review focuses on the progress in the study of ultrafast dynamics of atoms and molecules,which is an important part of attosecond science.Firstly,the generation and development of attosecond pulses are reviewed,mainly including the principle of high-order harmonic and the separation method of single-attosecond pulses.Then the applications of attosecond pulses are systematically introduced,including photo-ionization time delay,attosecond charge migration,non-adiabatic molecular dynamics and so on.Finally,the summary and outlook of the application of attosecond pulses are presented.
{"title":"Development of Attosecond Pulse and Application in Ultrafast Dynamics of Atoms and Molecules","authors":"Tao Chen-Yu, Lei Jian-Ting, Yu Xuan, Luo Yan, Ma Xin-wen, Zhang Shao-Feng","doi":"10.7498/aps.72.20222436","DOIUrl":"https://doi.org/10.7498/aps.72.20222436","url":null,"abstract":"In the past two decades,the development of laser technology has made attosecond science become a cutting-edge research field,providing various novel perspectives for the study of quantum few-body ultrafast evolution.The attosecond pulses prepared in the current laboratory are widely used in experimental research in the form of isolated pulses or pulse trains.The ultrafast changing light field allows people to control and track the motion of electrons at the atomic-scale,and realizes real-time tracking of electron dynamics on the sub-femtosecond time-scale.This review focuses on the progress in the study of ultrafast dynamics of atoms and molecules,which is an important part of attosecond science.Firstly,the generation and development of attosecond pulses are reviewed,mainly including the principle of high-order harmonic and the separation method of single-attosecond pulses.Then the applications of attosecond pulses are systematically introduced,including photo-ionization time delay,attosecond charge migration,non-adiabatic molecular dynamics and so on.Finally,the summary and outlook of the application of attosecond pulses are presented.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88169816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The band gap is a key physical quantity in material design. First-principles calculations based on density functional theory can approximately predict the band gap, which often require significant computational resources and time. Deep learning models have the advantages of good fitting ability and automatic feature extraction from the data, and are gradually being applied to predict the band gap. In this paper, aiming at the problem of quickly obtaining the band gap value of perovskite materials, a feature fusion neural network model named CGCrabNet is established, and the transfer learning strategy is used to predict the band gap of perovskite materials. CGCrabNet extracts features from both chemical equation and crystal structure of materials, and fits the mapping between features and band gaps. It is an end-to-end neural network model. Based on the pre-training data obtained from the Open Quantum Materials Database (OQMD dataset), the CGCrabNet parameters can be fine-tuned by using only 175 perovskite material data to improve the robustness of the model.The numerical experimental results show that the prediction error of the CGCrabNet model for band gap prediciton based on the OQMD dataset is 0.014eV, which is lower than that obtained from the prediction based on Compositionally restricted attention-based network (CrabNet). The mean absolute error of the model developed in this paper for the prediction of perovskite materials is 0.374eV, which is lower 0.304eV, 0.441eV and 0.194eV than that obtained from random forest regression, support vector machine regression and gradient boosting regression, respectively. The mean absolute error of the test set of CGCrabNet trained only using perovskite data is 0.536 eV, and the mean absolute error of the pre-trained CGCrabNet has decreased by 0.162 eV, which indicates that the transfer learning strategy has significant role in improving the prediction accuracy of small data sets (perovskite material data sets). The difference between the predicted band gap of some perovskite materials such as SrHfO3and RbPaO3 by the model and the band gap calculated by first-principles is less than 0.05eV, which indicates that the CGCrabNet can quickly and accurately predict the properties of new materials and accelerate the development process of new materials.
{"title":"Band gap prediction of perovskite materials based on transfer learning","authors":"Sun Tao, Yuan Jian-Mei","doi":"10.7498/aps.72.20231027","DOIUrl":"https://doi.org/10.7498/aps.72.20231027","url":null,"abstract":"The band gap is a key physical quantity in material design. First-principles calculations based on density functional theory can approximately predict the band gap, which often require significant computational resources and time. Deep learning models have the advantages of good fitting ability and automatic feature extraction from the data, and are gradually being applied to predict the band gap. In this paper, aiming at the problem of quickly obtaining the band gap value of perovskite materials, a feature fusion neural network model named CGCrabNet is established, and the transfer learning strategy is used to predict the band gap of perovskite materials. CGCrabNet extracts features from both chemical equation and crystal structure of materials, and fits the mapping between features and band gaps. It is an end-to-end neural network model. Based on the pre-training data obtained from the Open Quantum Materials Database (OQMD dataset), the CGCrabNet parameters can be fine-tuned by using only 175 perovskite material data to improve the robustness of the model.The numerical experimental results show that the prediction error of the CGCrabNet model for band gap prediciton based on the OQMD dataset is 0.014eV, which is lower than that obtained from the prediction based on Compositionally restricted attention-based network (CrabNet). The mean absolute error of the model developed in this paper for the prediction of perovskite materials is 0.374eV, which is lower 0.304eV, 0.441eV and 0.194eV than that obtained from random forest regression, support vector machine regression and gradient boosting regression, respectively. The mean absolute error of the test set of CGCrabNet trained only using perovskite data is 0.536 eV, and the mean absolute error of the pre-trained CGCrabNet has decreased by 0.162 eV, which indicates that the transfer learning strategy has significant role in improving the prediction accuracy of small data sets (perovskite material data sets). The difference between the predicted band gap of some perovskite materials such as SrHfO3and RbPaO3 by the model and the band gap calculated by first-principles is less than 0.05eV, which indicates that the CGCrabNet can quickly and accurately predict the properties of new materials and accelerate the development process of new materials.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85316877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhang Zhi-da, Yi Kang-yuan, Chen Yuan-zhen, Yan Fei
Dynamical decoupling refers to a family of techniques that are widely used to suppress decoherence in various quantum systems caused by quasi-static environmental noise. They have broad applications in the field of quantum information processing. Conventional dynamical decoupling targets at noise in two-level systems such as qubits and often consists specifically engineered sequences of π pulses that swap between two different states. On the other hand, researchers have gone beyond simple two-levels systems seeking for even more efficient quantum hardware. A variety of quantum algorithms and schemes of quantum control using multi-level systems, such as qutrits and qudits, for quantum information processing have been proposed and some of them being implemented successfully. However, decoherence in such multi-level systems is inherently more sophisticated than that in two-level systems. So far there has been little systematic research on how to tackle decoherence issues in such systems. In this work, we propose several sequences of dynamical decoupling for 19 multi-level systems that only rely on π pulses linking neighboring levels, which is experimentally friendly. Our results show that these sequences can efficiently suppress quasi-static noise presented in multi-level systems. In addition, by calculating the corresponding filter functions of these sequences, we are able to further analyze the effect of them on generic Gaussian noise that may not be quasi-static. We also give a physical interpretation of the noise filtering mechanism of these sequences by considering their control functions. Other topics discussed in our work include power spectral density and correlation of noise in multi-level systems. Our work represents a first step towards a more systematic investigation of dynamical decoupling techniques applicable to multilevel systems.
{"title":"Dynamic decoupling for multi-level systems","authors":"Zhang Zhi-da, Yi Kang-yuan, Chen Yuan-zhen, Yan Fei","doi":"10.7498/aps.72.20222398","DOIUrl":"https://doi.org/10.7498/aps.72.20222398","url":null,"abstract":"Dynamical decoupling refers to a family of techniques that are widely used to suppress decoherence in various quantum systems caused by quasi-static environmental noise. They have broad applications in the field of quantum information processing. Conventional dynamical decoupling targets at noise in two-level systems such as qubits and often consists specifically engineered sequences of π pulses that swap between two different states. On the other hand, researchers have gone beyond simple two-levels systems seeking for even more efficient quantum hardware. A variety of quantum algorithms and schemes of quantum control using multi-level systems, such as qutrits and qudits, for quantum information processing have been proposed and some of them being implemented successfully. However, decoherence in such multi-level systems is inherently more sophisticated than that in two-level systems. So far there has been little systematic research on how to tackle decoherence issues in such systems. In this work, we propose several sequences of dynamical decoupling for 19 multi-level systems that only rely on π pulses linking neighboring levels, which is experimentally friendly. Our results show that these sequences can efficiently suppress quasi-static noise presented in multi-level systems. In addition, by calculating the corresponding filter functions of these sequences, we are able to further analyze the effect of them on generic Gaussian noise that may not be quasi-static. We also give a physical interpretation of the noise filtering mechanism of these sequences by considering their control functions. Other topics discussed in our work include power spectral density and correlation of noise in multi-level systems. Our work represents a first step towards a more systematic investigation of dynamical decoupling techniques applicable to multilevel systems.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83652689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Microwave Thermoacoustic Imaging (MTAI) is an exciting imaging technique rooted in the underlying principle of exploiting the distinct electrical properties of biological tissues. By harnessing short-pulsed microwaves as a stimulation source and leveraging their interaction with the human body, MTAI has paved the way for revolutionary advancements in medical imaging. When microwaves are absorbed by polar molecules and ions within the tissues, an ingenious thermoelastic effect gives rise to ultrasound waves. These ultrasound waves, brimming with invaluable pathological and physiological insights, propagate outward, carrying the essence of the biological tissue's composition and functionality. Through a meticulous collection of ultrasound signals from all directions surrounding the tissue, it becomes possible to reconstruct intricate internal structures and visualize the tissue's functional dynamics. MTAI excels in non-invasiveness, capable of delving several centimeters beneath the surface with a microscopic resolution on the order of micrometers. The magic lies in the transformative conversion of microwave energy into ultrasound waves, tapping into the tissue's hidden depths without causing harm. This groundbreaking imaging modality unlocks a realm of possibilities for acquiring profound insights into the intricate structures and functionality of deep-seated tissues. Furthermore, the inherent polarization characteristics of microwaves empower MTAI to capture additional dimensions of information, unraveling the intricate polarization properties and illuminating a richer understanding of the tissue's complexity. The immense potential of MTAI extends far and wide within the realm of medicine. It has already demonstrated remarkable achievements in non-invasively imaging brain structures, screening for breast tumors, visualizing arthritis in human joints, and detecting liver fat content. These accomplishments have laid a solid foundation, firmly establishing MTAI as a trailblazing medical imaging technique. This article offers a comprehensive and in-depth exploration of the physical principles underpinning MTAI, the sophisticated system devices involved, and the recent groundbreaking research breakthroughs. Moreover, it delves into the exciting prospects and challenges that lie ahead in the future development of MTAI. As the technology continues to progress by leaps and bounds, MTAI is poised to shatter barriers, ushering in a new era of unrivaled imaging quality and performance. This, in turn, will open the floodgates for transformative innovation and application in the realms of medical diagnosis and treatment. The anticipation is palpable as MTAI strives to make substantial contributions to the ever-evolving field of medical imaging, bestowing upon humanity more precise, reliable, and life-enhancing diagnostic capabilities.
{"title":"Biomedical Microwave-induced Thermoacoustic Imaging","authors":"Yu Wang, Huiming Zhang, Huan Qin","doi":"10.7498/aps.72.20230732","DOIUrl":"https://doi.org/10.7498/aps.72.20230732","url":null,"abstract":"Microwave Thermoacoustic Imaging (MTAI) is an exciting imaging technique rooted in the underlying principle of exploiting the distinct electrical properties of biological tissues. By harnessing short-pulsed microwaves as a stimulation source and leveraging their interaction with the human body, MTAI has paved the way for revolutionary advancements in medical imaging. When microwaves are absorbed by polar molecules and ions within the tissues, an ingenious thermoelastic effect gives rise to ultrasound waves. These ultrasound waves, brimming with invaluable pathological and physiological insights, propagate outward, carrying the essence of the biological tissue's composition and functionality. Through a meticulous collection of ultrasound signals from all directions surrounding the tissue, it becomes possible to reconstruct intricate internal structures and visualize the tissue's functional dynamics. MTAI excels in non-invasiveness, capable of delving several centimeters beneath the surface with a microscopic resolution on the order of micrometers. The magic lies in the transformative conversion of microwave energy into ultrasound waves, tapping into the tissue's hidden depths without causing harm. This groundbreaking imaging modality unlocks a realm of possibilities for acquiring profound insights into the intricate structures and functionality of deep-seated tissues. Furthermore, the inherent polarization characteristics of microwaves empower MTAI to capture additional dimensions of information, unraveling the intricate polarization properties and illuminating a richer understanding of the tissue's complexity. The immense potential of MTAI extends far and wide within the realm of medicine. It has already demonstrated remarkable achievements in non-invasively imaging brain structures, screening for breast tumors, visualizing arthritis in human joints, and detecting liver fat content. These accomplishments have laid a solid foundation, firmly establishing MTAI as a trailblazing medical imaging technique. This article offers a comprehensive and in-depth exploration of the physical principles underpinning MTAI, the sophisticated system devices involved, and the recent groundbreaking research breakthroughs. Moreover, it delves into the exciting prospects and challenges that lie ahead in the future development of MTAI. As the technology continues to progress by leaps and bounds, MTAI is poised to shatter barriers, ushering in a new era of unrivaled imaging quality and performance. This, in turn, will open the floodgates for transformative innovation and application in the realms of medical diagnosis and treatment. The anticipation is palpable as MTAI strives to make substantial contributions to the ever-evolving field of medical imaging, bestowing upon humanity more precise, reliable, and life-enhancing diagnostic capabilities.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91237546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Chuan-Sheng, Ding Shuai, Han Xu, Wang Bing-Zhong
Achieving tunable focus of electromagnetic field energy at multiple target points is a critical challenge in the wireless power transfer (WPT) domain. Although techniques such as optimal constrained power focusing (OCPF) and time reversal (TR) have been proposed. The former presents limited practical applicability while the latter is noteworthy for its adaptive spatio-temporal synchronous focusing characteristics. However, the time reversal mirror (TRM) method necessitates intricate pretesting and has highly complex systems. In this study, we introduce a novel channel processing method, named channel extraction, selection, weighting, and reconstruction (CESWR), to attain balanced power distribution for multiple users, characterized by low complexity, high computability, and rapid convergence. Diverging from the traditional TR approach, our proposed method, grounded in channel correlation considerations, filters the channel impulse response (CIR) for multiple targets, segregating them into distinct characteristic and similar components for each target. This method ensures focused generation at both receiving ends while facilitating high-precision regulation of the peak voltage of the received signal. Furthermore, this study embarks on a rigorous examination of the linearity intrinsic to the proposed methodology, explicating a singular correspondence between the tuning of theoretical weights and the resultant outcomes. In order to authenticate the efficacy of this methodology, we construct a single-input multiple-output time-reversal cavity (SIMO-TRC) system for the experimental section of this manuscript. Subsequent experimentation, conducted for both loosely and tightly correlated models, furnishes invaluable insights. Evidently, in the loosely correlated model, the CESWR method exhibits proficiency in attaining a peak voltage ratio (PVR) of nearly 1.00 at the two receivers, with a minuscule numerical discrepancy of merely 8×10-6 mV. In stark contrast, under the tightly correlated model, the CESWR method demonstrates an enhanced ability to differentiate between two targets, thus offering a noticeable improvement over the classic single-target TR method.
{"title":"Channel processing-based time-reversal method for multi-target tunable focusing","authors":"Chen Chuan-Sheng, Ding Shuai, Han Xu, Wang Bing-Zhong","doi":"10.7498/aps.72.20230547","DOIUrl":"https://doi.org/10.7498/aps.72.20230547","url":null,"abstract":"Achieving tunable focus of electromagnetic field energy at multiple target points is a critical challenge in the wireless power transfer (WPT) domain. Although techniques such as optimal constrained power focusing (OCPF) and time reversal (TR) have been proposed. The former presents limited practical applicability while the latter is noteworthy for its adaptive spatio-temporal synchronous focusing characteristics. However, the time reversal mirror (TRM) method necessitates intricate pretesting and has highly complex systems. In this study, we introduce a novel channel processing method, named channel extraction, selection, weighting, and reconstruction (CESWR), to attain balanced power distribution for multiple users, characterized by low complexity, high computability, and rapid convergence. Diverging from the traditional TR approach, our proposed method, grounded in channel correlation considerations, filters the channel impulse response (CIR) for multiple targets, segregating them into distinct characteristic and similar components for each target. This method ensures focused generation at both receiving ends while facilitating high-precision regulation of the peak voltage of the received signal. Furthermore, this study embarks on a rigorous examination of the linearity intrinsic to the proposed methodology, explicating a singular correspondence between the tuning of theoretical weights and the resultant outcomes. In order to authenticate the efficacy of this methodology, we construct a single-input multiple-output time-reversal cavity (SIMO-TRC) system for the experimental section of this manuscript. Subsequent experimentation, conducted for both loosely and tightly correlated models, furnishes invaluable insights. Evidently, in the loosely correlated model, the CESWR method exhibits proficiency in attaining a peak voltage ratio (PVR) of nearly 1.00 at the two receivers, with a minuscule numerical discrepancy of merely 8×10-6 mV. In stark contrast, under the tightly correlated model, the CESWR method demonstrates an enhanced ability to differentiate between two targets, thus offering a noticeable improvement over the classic single-target TR method.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91294217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Active matter is a new and challenging field of physics. Chiral active particle experiences a constant torque and performs circular motion due to the self-propulsion force not aligning with the propulsion direction. Recently, most of studies of the active particle systems focused on constant temperature, but did not take into consideration the constraints by the barriers. In our work, the rectification of a ring containing chiral active particles with transversal temperature difference is numerically investigated in a two-dimensional periodic channel. It is found that the ring powered by chiral active particles can be rectified by the transversal temperature difference and the direction of the transport is determined by the chirality of active particles. The average velocity is a peaked function of angular velocity, the temperature of the lower wall or temperature difference. The transport behaviors of the ring containing one chiral active particle is qualitatively different from those of the ring containing several particles. Especially, the ring radius can strongly affect the transport behaviors. For the ring containing one chiral active particle, the interaction between the particle and the ring facilitates the rectification of the ring when the circular trajectory radius of the chiral particle is large. The average velocity decreases with the increase of the ring radius because the propelling force to the ring by the particle is small. When the circular trajectory radius is small, the interaction between the particle and the ring suppresses the transport. The speed increases as the ring radius increases because the directional transport comes from the difference in temperature between the upper wall and the lower wall. For the ring containing several particles, the interaction between particles reduces the rectification of the ring. The average velocity increases with the increase of the ring radius due to the interaction between particles decreasing. Remarkably, the velocity of the ring decreases as the particle number increases when the ring radius is small, but is a peaked function when the ring radius is not small. Our results offer new possibilities for manipulating an active particle flow on a microscale, and can be applied practically to propelling carriers and motors by a bath of bacteria or artificial microswimmers, such as hybrid micro-device engineering, drug delivery, micro-fluidics, and lab-on-chip technology.
{"title":"Transport of closed ring containing chiral active particles under transversal temperature difference","authors":"Jing-Jing Liao, Qi Kang, Fei Luo, Fu-Jun Lin","doi":"10.7498/aps.72.20221772","DOIUrl":"https://doi.org/10.7498/aps.72.20221772","url":null,"abstract":"Active matter is a new and challenging field of physics. Chiral active particle experiences a constant torque and performs circular motion due to the self-propulsion force not aligning with the propulsion direction. Recently, most of studies of the active particle systems focused on constant temperature, but did not take into consideration the constraints by the barriers. In our work, the rectification of a ring containing chiral active particles with transversal temperature difference is numerically investigated in a two-dimensional periodic channel. It is found that the ring powered by chiral active particles can be rectified by the transversal temperature difference and the direction of the transport is determined by the chirality of active particles. The average velocity is a peaked function of angular velocity, the temperature of the lower wall or temperature difference. The transport behaviors of the ring containing one chiral active particle is qualitatively different from those of the ring containing several particles. Especially, the ring radius can strongly affect the transport behaviors. For the ring containing one chiral active particle, the interaction between the particle and the ring facilitates the rectification of the ring when the circular trajectory radius of the chiral particle is large. The average velocity decreases with the increase of the ring radius because the propelling force to the ring by the particle is small. When the circular trajectory radius is small, the interaction between the particle and the ring suppresses the transport. The speed increases as the ring radius increases because the directional transport comes from the difference in temperature between the upper wall and the lower wall. For the ring containing several particles, the interaction between particles reduces the rectification of the ring. The average velocity increases with the increase of the ring radius due to the interaction between particles decreasing. Remarkably, the velocity of the ring decreases as the particle number increases when the ring radius is small, but is a peaked function when the ring radius is not small. Our results offer new possibilities for manipulating an active particle flow on a microscale, and can be applied practically to propelling carriers and motors by a bath of bacteria or artificial microswimmers, such as hybrid micro-device engineering, drug delivery, micro-fluidics, and lab-on-chip technology.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90805052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luo Jie, Zhang Zi-Qiu, Xu Jun-Hao, Qin Zhao-Ting, Zhao Yuan-Shuai, He Hong, Li Guan-Nan, Tang Jian-Feng
A series of rare earth Dy3+, Tb3+, Eu3+ singly doped Gd2Te4O11 (GTO) tellurite phosphors with intrinsic polarity were prepared by hydrothermal method. The phase structure, morphology and thermal stability of the phosphors were characterized. Their luminescence properties were tested in detail. The results show all those phosphors were crystalized into single phase of digadolinium tellurite with short rod-like shape. The maximum size achieved microns in axial direction. The phosphors have good thermal stability. For the GTO:Dy3+, the fluorescence emission under UV excitation is mainly located in the yellow-green region. The optimal doping concentration corresponding to the strongest excitation and emission is 2.5%, and the CIE color coordinates are (0.39, 0.43). The fluorescence decay curves show that the lifetime of the GTO:Dy3+ on 4F9/2 energy level decreases gradually with increasing doping concentration of Dy3+, which may be related to the cross relaxation (CR) between Dy3+ ions. For the GTO:Eu3+, the fluorescence emission under UV excitation is mainly located in the red and orange-red regions. The emission intensity was enhanced with increasing doping concentration of Eu3+. When the doping concentration is 10%, the CIE color coordinates are (0.62, 0.38), which located in the orange-red region with high color purity. The fluorescence lifetime of Eu3+ on 5D0 energy level is hardly affected by the change of Eu3+ doping concentration. For the GTO:Tb3+, with increasing the Tb3+ concentration, the fluorescence emission under UV excitation changes from blue-violet region to yellow-green region, which can be ascribed to the influence of CR between Tb3+ ions. The fluorescence decay behavior revealed that the Tb3+ ions on 5D4 excited state may undergo energy transfer and reabsorption, which deviated fluorescence decay from the single exponential model. When the concentration of Tb3+ is 0.5%, the sample exhibits white light emission, having the CIE color coordinates of (0.33, 0.35) and color rendering index of 86. The measurements of temperature-dependent emission spectra show that the above-mentioned phosphors have good luminescent thermal stability. The internal quantum efficiencies (IQE) of those three types of phosphors were tested, and the IQE of GTO:Eu3+ are better than those of GTO:Dy3+ and GTO:Tb3+. All those phosphors still have much room for improvement in the luminescent performance. These phosphors have potential for the use of UV-excited white LED.
{"title":"Synthesis and luminescent properties of rare earths doped Gd2Te4O11 tellurite phosphors","authors":"Luo Jie, Zhang Zi-Qiu, Xu Jun-Hao, Qin Zhao-Ting, Zhao Yuan-Shuai, He Hong, Li Guan-Nan, Tang Jian-Feng","doi":"10.7498/aps.72.20221341","DOIUrl":"https://doi.org/10.7498/aps.72.20221341","url":null,"abstract":"A series of rare earth Dy<sup>3+</sup>, Tb<sup>3+</sup>, Eu<sup>3+</sup> singly doped Gd<sub>2</sub>Te<sub>4</sub>O<sub>11</sub> (GTO) tellurite phosphors with intrinsic polarity were prepared by hydrothermal method. The phase structure, morphology and thermal stability of the phosphors were characterized. Their luminescence properties were tested in detail. The results show all those phosphors were crystalized into single phase of digadolinium tellurite with short rod-like shape. The maximum size achieved microns in axial direction. The phosphors have good thermal stability. For the GTO:Dy<sup>3+</sup>, the fluorescence emission under UV excitation is mainly located in the yellow-green region. The optimal doping concentration corresponding to the strongest excitation and emission is 2.5%, and the CIE color coordinates are (0.39, 0.43). The fluorescence decay curves show that the lifetime of the GTO:Dy<sup>3+</sup> on <sup>4</sup>F<sub>9/2</sub> energy level decreases gradually with increasing doping concentration of Dy<sup>3+</sup>, which may be related to the cross relaxation (CR) between Dy<sup>3+</sup> ions. For the GTO:Eu<sup>3+</sup>, the fluorescence emission under UV excitation is mainly located in the red and orange-red regions. The emission intensity was enhanced with increasing doping concentration of Eu<sup>3+</sup>. When the doping concentration is 10%, the CIE color coordinates are (0.62, 0.38), which located in the orange-red region with high color purity. The fluorescence lifetime of Eu<sup>3+</sup> on <sup>5</sup>D<sub>0</sub> energy level is hardly affected by the change of Eu<sup>3+</sup> doping concentration. For the GTO:Tb<sup>3+</sup>, with increasing the Tb<sup>3+</sup> concentration, the fluorescence emission under UV excitation changes from blue-violet region to yellow-green region, which can be ascribed to the influence of CR between Tb<sup>3+</sup> ions. The fluorescence decay behavior revealed that the Tb<sup>3+</sup> ions on <sup>5</sup>D<sub>4</sub> excited state may undergo energy transfer and reabsorption, which deviated fluorescence decay from the single exponential model. When the concentration of Tb<sup>3+</sup> is 0.5%, the sample exhibits white light emission, having the CIE color coordinates of (0.33, 0.35) and color rendering index of 86. The measurements of temperature-dependent emission spectra show that the above-mentioned phosphors have good luminescent thermal stability. The internal quantum efficiencies (IQE) of those three types of phosphors were tested, and the IQE of GTO:Eu<sup>3+</sup> are better than those of GTO:Dy<sup>3+</sup> and GTO:Tb<sup>3+</sup>. All those phosphors still have much room for improvement in the luminescent performance. These phosphors have potential for the use of UV-excited white LED.","PeriodicalId":6995,"journal":{"name":"Acta Physica Sinica","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90822671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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