With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provi...With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.展开更多
The transition metal dichalcogenides(TMD)monolayers have shown strong second-harmonic generation(SHG)ow-ing to their lack of inversion symmetry.These ultrathin layers then serve as the frequency converters that can be...The transition metal dichalcogenides(TMD)monolayers have shown strong second-harmonic generation(SHG)ow-ing to their lack of inversion symmetry.These ultrathin layers then serve as the frequency converters that can be intergraded on a chip.Here,taking MoSSe as an example,we report the first detailed experimental study of the SHG of Janus TMD monolayer,in which the transition metal layer is sandwiched by the two distinct chalcogen layers.It is shown that the SHG effectively arises from an in-plane second-harmonic polarization under paraxial focusing and detection.Based on this,the orientation-resolved SHG spectroscopy is realized to readily determine the zigzag and armchair axes of the Janus crystal with an accuracy better than±0.6°.Moreover,the SHG intensity is wavelength-dependent and can be greatly enhanced(~60 times)when the two-photon transition is resonant with the C-exciton state.Our findings uncover the SHG properties of Janus MoSSe monolayer,therefore lay the basis for its integrated frequency-doubling applications.展开更多
High resolution angle-resolved photoemission spectroscopy(ARPES)measurements are carried out on CaKFe_4 As_4,KCa_2 Fe_4 As_4 F_2 and(Ba_(0.6)K_(0.4))Fe_2 As_2 superconductors.Clear evidence of band folding between the...High resolution angle-resolved photoemission spectroscopy(ARPES)measurements are carried out on CaKFe_4 As_4,KCa_2 Fe_4 As_4 F_2 and(Ba_(0.6)K_(0.4))Fe_2 As_2 superconductors.Clear evidence of band folding between the Brillouin zone center and corners with a(π,π)wave vector has been found from the measured Fermi surface and band structures in all the three kinds of superconductors.A dominant √2×√2 surface reconstruction is observed on the cleaved surface of CaKFe_4As_4 by scanning tunneling microscopy(STM)measurements.We propose that the commonly observed √2×√2 reconstruction in the FeAs-based superconductors provides a general scenario to understand the origin of the(π,π)band folding.Our observations provide new insights in understanding the electronic structure and superconductivity mechanism in iron-based superconductors.展开更多
Twisted graphene systems with flat bands have attracted much attention for they are excellent platforms to research novel quantum phases. Recently, transport measurements about twisted monolayer–bilayer graphene(t MB...Twisted graphene systems with flat bands have attracted much attention for they are excellent platforms to research novel quantum phases. Recently, transport measurements about twisted monolayer–bilayer graphene(t MBG) have shown the existence of correlated states and topological states in this system. However, the direct observations of the band structures and the corresponding spatial distributions are still not sufficient. Here we show that the distributions of flat bands in t MBG host two different modes by scanning tunneling microscopy and spectroscopy(STM/S). By tuning our t MBG device from the empty filling state to the full filling state through the back gate, we observe that the distributions of two flat bands develop from localized mode to delocalized mode. This gate-controlled flat band wavefunction polarization is unique to the t MBG system. Our work suggests that t MBG is promising to simulate both twisted bilayer graphene(TBG) and twisted double bilayer graphene(t DBG) and would be an ideal platform to explore novel moiré physics.展开更多
基金supported by the National Natural Science Foundation of China under Grant 52077146.
文摘With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.61888102,51771224,and 62175253)the National Key R&D Program of China(Grant Nos.2018YFA0305803 and 2019YFA0308501)+4 种基金the Chinese Academy of Sciences(Grant Nos.XDB33030100 and XDB30010000)J.S.and X.L.thank the supports from the National Natural Science Foundation of China(Grant Nos.20173025,22073022,and 11874130)the National Key R&D Program of China(Grant No.2017YFA0205004)the Chinese Academy of Sciences(Grant Nos.XDB3600000 and Y950291)the DNL Cooperation Fund(Grant No.DNL202016).
文摘The transition metal dichalcogenides(TMD)monolayers have shown strong second-harmonic generation(SHG)ow-ing to their lack of inversion symmetry.These ultrathin layers then serve as the frequency converters that can be intergraded on a chip.Here,taking MoSSe as an example,we report the first detailed experimental study of the SHG of Janus TMD monolayer,in which the transition metal layer is sandwiched by the two distinct chalcogen layers.It is shown that the SHG effectively arises from an in-plane second-harmonic polarization under paraxial focusing and detection.Based on this,the orientation-resolved SHG spectroscopy is realized to readily determine the zigzag and armchair axes of the Janus crystal with an accuracy better than±0.6°.Moreover,the SHG intensity is wavelength-dependent and can be greatly enhanced(~60 times)when the two-photon transition is resonant with the C-exciton state.Our findings uncover the SHG properties of Janus MoSSe monolayer,therefore lay the basis for its integrated frequency-doubling applications.
基金Supported by the National Key Research and Development Program of China (Grant Nos.2016YFA0300300,2017YFA0302900,2018YFA0704200 and 2019YFA0308000)the National Natural Science Foundation of China (Grant Nos.11888101,11922414 and11874405)+2 种基金the Strategic Priority Research Program (B) of the Chinese Academy of Sciences (Grant No.XDB25000000)the Youth Innovation Promotion Association of CAS (Grant No.2017013)the Research Program of Beijing Academy of Quantum Information Sciences (Grant No.Y18G06)。
文摘High resolution angle-resolved photoemission spectroscopy(ARPES)measurements are carried out on CaKFe_4 As_4,KCa_2 Fe_4 As_4 F_2 and(Ba_(0.6)K_(0.4))Fe_2 As_2 superconductors.Clear evidence of band folding between the Brillouin zone center and corners with a(π,π)wave vector has been found from the measured Fermi surface and band structures in all the three kinds of superconductors.A dominant √2×√2 surface reconstruction is observed on the cleaved surface of CaKFe_4As_4 by scanning tunneling microscopy(STM)measurements.We propose that the commonly observed √2×√2 reconstruction in the FeAs-based superconductors provides a general scenario to understand the origin of the(π,π)band folding.Our observations provide new insights in understanding the electronic structure and superconductivity mechanism in iron-based superconductors.
基金support from the National Key R&D Program of China (Grant No. 2019YFA0307800)Beijing Natural Science Foundation (Grant No. Z190011)+1 种基金the National Natural Science Foundation of China (Grant No. 11974347)Fundamental Research Funds for the Central Universities。
文摘Twisted graphene systems with flat bands have attracted much attention for they are excellent platforms to research novel quantum phases. Recently, transport measurements about twisted monolayer–bilayer graphene(t MBG) have shown the existence of correlated states and topological states in this system. However, the direct observations of the band structures and the corresponding spatial distributions are still not sufficient. Here we show that the distributions of flat bands in t MBG host two different modes by scanning tunneling microscopy and spectroscopy(STM/S). By tuning our t MBG device from the empty filling state to the full filling state through the back gate, we observe that the distributions of two flat bands develop from localized mode to delocalized mode. This gate-controlled flat band wavefunction polarization is unique to the t MBG system. Our work suggests that t MBG is promising to simulate both twisted bilayer graphene(TBG) and twisted double bilayer graphene(t DBG) and would be an ideal platform to explore novel moiré physics.
