Color centers play key roles in,e.g.,solid state lighting and quantum information technology.Here,we describe an approach for predicting the optical line shapes of such emitters based on direct sampling of the underly...Color centers play key roles in,e.g.,solid state lighting and quantum information technology.Here,we describe an approach for predicting the optical line shapes of such emitters based on direct sampling of the underlying autocorrelation functions through molecular dynamics simulations(MD-ACF).The energy landscapes are represented by a machine-learned potential that describes both the ground and excited state landscapes through a single model,guaranteeing size-consistent predictions.We apply this methodology to the(V_(Si)V_(C))_(kk)^(0)divacancy defect in 4H-SiC and demonstrate that at low temperatures,the present MD-ACF approach reproduces results from the traditional generating function approach.Unlike the latter,it is,however,also applicable at high temperatures as it avoids harmonic and parallel-mode approximations and can be applied to study non-crystalline materials.The MD-ACF methodology thus promises to substantially widen the range of computational predictions of the optical properties of color centers and related defects.展开更多
为了研究室外视距(line of sight,Lo S)和非视距(non-Lo S,NLo S)传输场景中车辆与车辆(vehicle-to-vehicle,V2V)之间的无线通信系统,提出一种基于几何街道散射场景的统计信道模型,其发射端和接收端都处于移动状态。先假设有无穷多的散...为了研究室外视距(line of sight,Lo S)和非视距(non-Lo S,NLo S)传输场景中车辆与车辆(vehicle-to-vehicle,V2V)之间的无线通信系统,提出一种基于几何街道散射场景的统计信道模型,其发射端和接收端都处于移动状态。先假设有无穷多的散射体随机分布在街道两侧;并且在发射端和接收端都采用多天线技术,然后模型定量给出了几何街道散射场景下到发射角(angle of arrival,AOD)和到达角(angle of arrival,AOA)之间的几何关系。同时研究了信号在几何散射信道模型中的空间互相关函数、时间自相关函数(autocorrelation function,ACF)、频率互相关函数以及多普勒功率谱密度(power spectral density,PSD)的影响。理论分析和仿真结果表明提出的V2V通信系统的无线信道的统计特性符合理论和经验,拓展了多输入多输出宽带V2V通信系统的研究。展开更多
Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been...Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.展开更多
基金funding from the Swedish Research Council(Nos.2020-04935 and 2021-05072)as well as computational resources provided by the National Academic Infrastructure for Supercomputing in Sweden at NSC,PDCC3SE partially funded by the Swedish Research Council through grant agreement No.2022-06725+1 种基金as well as the Berzelius resource provided by the Knut and Alice Wallenberg Foundation at NSC.Parts of the computations were performed on resources provided by UNINETT Sigma2-the National Infrastructure for High-Performance Computing and Data Storage in Norway.C.L.acknowledges the support provided by the Research Council of Norway and the University of Oslo through the research project QuTe(no.325573,FriPro ToppForsk-program)funding from the Swedish Strategic Research Foundation through a Future Research Leader program(FFL21-0129).
文摘Color centers play key roles in,e.g.,solid state lighting and quantum information technology.Here,we describe an approach for predicting the optical line shapes of such emitters based on direct sampling of the underlying autocorrelation functions through molecular dynamics simulations(MD-ACF).The energy landscapes are represented by a machine-learned potential that describes both the ground and excited state landscapes through a single model,guaranteeing size-consistent predictions.We apply this methodology to the(V_(Si)V_(C))_(kk)^(0)divacancy defect in 4H-SiC and demonstrate that at low temperatures,the present MD-ACF approach reproduces results from the traditional generating function approach.Unlike the latter,it is,however,also applicable at high temperatures as it avoids harmonic and parallel-mode approximations and can be applied to study non-crystalline materials.The MD-ACF methodology thus promises to substantially widen the range of computational predictions of the optical properties of color centers and related defects.
文摘为了研究室外视距(line of sight,Lo S)和非视距(non-Lo S,NLo S)传输场景中车辆与车辆(vehicle-to-vehicle,V2V)之间的无线通信系统,提出一种基于几何街道散射场景的统计信道模型,其发射端和接收端都处于移动状态。先假设有无穷多的散射体随机分布在街道两侧;并且在发射端和接收端都采用多天线技术,然后模型定量给出了几何街道散射场景下到发射角(angle of arrival,AOD)和到达角(angle of arrival,AOA)之间的几何关系。同时研究了信号在几何散射信道模型中的空间互相关函数、时间自相关函数(autocorrelation function,ACF)、频率互相关函数以及多普勒功率谱密度(power spectral density,PSD)的影响。理论分析和仿真结果表明提出的V2V通信系统的无线信道的统计特性符合理论和经验,拓展了多输入多输出宽带V2V通信系统的研究。
文摘Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.
