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Brightening single-photon emitters by combining an ultrathin metallic antenna and a silicon quasi-BIC antenna 下载免费PDF全文
Bright single-photon emitters(SPEs)are fundamental components in many quantum applications.However,it is difficult to simultaneously get large Purcell enhancements and quantum yields in metallic nanostructures because of the huge losses in the metallic nanostructures.Herein,we propose to combine an ultrathin metallic bowtie antenna with a silicon antenna above a metallic substrate to simultaneously get large Purcell enhancements,quantum yields,and collection efficiencies.As a result,the brightness of SPEs in the hybrid nanostructure is greatly increased.Due to the deep subwavelength field confinement(mode size<10 nm)of surface plasmons in the ultrathin metallic film(thickness<4 nm),the Purcell enhancement of the metallic bowtie antenna improves by more than 25 times when the metal thickness decreases from 20 nm to 2 nm.In the hybrid nanostructures by combining an ultrathin metallic bowtie antenna with a silicon antenna,the Purcell enhancement(Fp≈2.6×106)in the hybrid nanostructures is 63 times greater than those(≤4.1×104)in the previous metallic and hybrid nanostructures.Because of the reduced ratio of electromagnetic fields in the ultrathin metallic bowtie antenna when the high-index silicon antenna is under the quasi-BIC state,a high quantum yield(QY≈0.70)is obtained.Moreover,the good radiation directivity of the quasi-BIC(bound state in the continuum)mode of the silicon antenna and the reflection of the metallic substrate result in a high collection efficiency(CE≈0.71).Consequently,the overall enhancement factor of brightness of a SPE in the hybrid nanostructure is EF?≈Fp×QY×CE≈1.3×106,which is 5.6×102 times greater than those(EF?≤2.2×103)in the previous metallic and hybrid nanostructures. 相似文献
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An Alternating Direction Method of Multipliers for MCP-penalized Regression with High-dimensional Data 下载免费PDF全文
The minimax concave penalty (MCP) has been demonstrated theoretically and practically to be effective in nonconvex penalization for variable selection and parameter estimation. In this paper, we develop an efficient alternating direction method of multipliers (ADMM) with continuation algorithm for solving the MCP-penalized least squares problem in high dimensions. Under some mild conditions, we study the convergence properties and the Karush–Kuhn–Tucker (KKT) optimality conditions of the proposed method. A high-dimensional BIC is developed to select the optimal tuning parameters. Simulations and a real data example are presented to illustrate the efficiency and accuracy of the proposed method. 相似文献
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In this paper we consider the problem of identifying a parsimonious subset multivariate ARCH model based on the AIC principle.
The proposed approach can reduce the number of parameters in the final ARCH specification and allows for non-constant correlations
between the components. Some simulation results illustrate the viability of the proposed procedure. 相似文献
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Ja-Yong Koo 《Journal of computational and graphical statistics》2013,22(3):266-284
Abstract This article deals with regression function estimation when the regression function is smooth at all but a finite number of points. An important question is: How can one produce discontinuous output without knowledge of the location of discontinuity points? Unlike most commonly used smoothers that tend to blur discontinuity in the data, we need to find a smoother that can detect such discontinuity. In this article, linear splines are used to estimate discontinuous regression functions. A procedure of knot-merging is introduced for the estimation of regression functions near discontinuous points. The basic idea is to use multiple knots for spline estimates. We use an automatic procedure involving the least squares method, stepwise knot addition, stepwise basis deletion, knot-merging, and the Bayes information criterion to select the final model. The proposed method can produce discontinuous outputs. Numerical examples using both simulated and real data are given to illustrate the performance of the proposed method. 相似文献
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In this paper, we are interested in investigating the causal relationships among futures sugar prices in the Zhengzhou futures exchange market (ZF), the spot sugar prices in Zhengzhou (ZS) and the futures sugar prices in New York futures exchange market (NF). A useful tool called Bayesian network is introduced to analyze the problem. Since there are only three variables in our Bayesian network, the algorithm is straightforward: we display all the 25 possible network structures and adopt certain scoring metrics to evaluate them. We applied five different scoring metrics in total. Firstly, for each metric, we obtained 24 scores, each calculated from one of the 24 possible structures i.e. a Directed Acyclic Graph (DAG). Then we eliminated the network structure which represents the independence of the three variables according to our prior knowledge concerning the futures sugar market. After that, the optimal network structure which implies the causal relationships was selected according to the corresponding scoring metric. Finally, after comparing the results from different scoring metrics, we obtained the relatively affirmative conclusion that ZS causes ZF from both the Bayesian Dirichlet (BD) metric, Bayesian Dirichlet-Akaike Information Criterion (BD-AIC) metric, Bayesian Dirichlet-Bayesian Information Criterion (BD-BIC) metric and Bayesian Information Criterion (BIC) metric. The conclusions that NF causes ZF and ZF causes ZS from the Akaike Information Criterion (AIC) metric and ZF causes ZS from the BIC metric were useful and significant to our investigation. 相似文献
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M.D. Spiridonakos 《Journal of sound and vibration》2010,329(7):768-785
This article addresses the problem of parametric time-domain identification and dynamic analysis for time-varying (TV) mechanical structures under unobservable random excitation. The methods presented are based on time-dependent autoregressive moving average (TARMA) models, and are classified according to the mathematical structure imposed on the TV parameter evolution as unstructured parameter evolution, stochastic parameter evolution, and deterministic parameter evolution. The features and relative merits of each class are outlined. A representative method from each is then assessed through its application to the identification and dynamic analysis of a laboratory TV structure consisting of a beam with a mass moving on it. The results are mutually compared and contrasted to those obtained through “frozen-configuration” (multiple experiment) baseline identification. 相似文献
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This paper discusses the topic of model selection for finite-dimensional normal regression models. We compare model selection criteria according to prediction errors based upon prediction with refitting, and prediction without refitting. We provide a new lower bound for prediction without refitting, while a lower bound for prediction with refitting was given by Rissanen. Moreover, we specify a set of sufficient conditions for a model selection criterion to achieve these bounds. Then the achievability of the two bounds by the following selection rules are addressed: Rissanen's accumulated prediction error criterion (APE), his stochastic complexity criterion, AIC, BIC and the FPE criteria. In particular, we provide upper bounds on overfitting and underfitting probabilities needed for the achievability. Finally, we offer a brief discussion on the issue of finite-dimensional vs. infinite-dimensional model assumptions.Support from the National Science Foundation, grant DMS 8802378 and support from ARO, grant DAAL03-91-G-007 to B. Yu during the revision are gratefully acknowledged. 相似文献