8,028 research outputs found
Highly efficient optical power transfer to whispering-gallery modes by use of a symmetrical dual-coupling configuration
We report that greater than 99.8% optical power transfer to whispering-gallery modes was achieved in fused-silica microspheres by use of a dual-tapered-fiber coupling method. The intrinsic cavity loss and the taper-to-sphere coupling coefficient are inferred from the experimental data. It is shown that the low intrinsic cavity loss and the symmetrical dual-coupling structure are crucial for obtaining the high coupling efficiency
Highly efficient hybrid fiber taper coupled microsphere laser
A novel hybrid fiber taper is proposed and demonstrated as the coupler in a microsphere laser system. The pump wave and the laser emission, respectively, are more efficiently coupled to and from the sphere modes with this taper structure. A 980-nm pumped erbium–ytterbium codoped phosphate microsphere laser is demonstrated in the 1550-nm band. As much as 112 µW of single-frequency laser output power was measured, with a differential quantum efficiency of 12%
Discussion: "A significance test for the lasso"
Discussion of "A significance test for the lasso" by Richard Lockhart,
Jonathan Taylor, Ryan J. Tibshirani, Robert Tibshirani [arXiv:1301.7161].Comment: Published in at http://dx.doi.org/10.1214/13-AOS1175B the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Adaptive covariance matrix estimation through block thresholding
Estimation of large covariance matrices has drawn considerable recent
attention, and the theoretical focus so far has mainly been on developing a
minimax theory over a fixed parameter space. In this paper, we consider
adaptive covariance matrix estimation where the goal is to construct a single
procedure which is minimax rate optimal simultaneously over each parameter
space in a large collection. A fully data-driven block thresholding estimator
is proposed. The estimator is constructed by carefully dividing the sample
covariance matrix into blocks and then simultaneously estimating the entries in
a block by thresholding. The estimator is shown to be optimally rate adaptive
over a wide range of bandable covariance matrices. A simulation study is
carried out and shows that the block thresholding estimator performs well
numerically. Some of the technical tools developed in this paper can also be of
independent interest.Comment: Published in at http://dx.doi.org/10.1214/12-AOS999 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Optimal estimation of the mean function based on discretely sampled functional data: Phase transition
The problem of estimating the mean of random functions based on discretely
sampled data arises naturally in functional data analysis. In this paper, we
study optimal estimation of the mean function under both common and independent
designs. Minimax rates of convergence are established and easily implementable
rate-optimal estimators are introduced. The analysis reveals interesting and
different phase transition phenomena in the two cases. Under the common design,
the sampling frequency solely determines the optimal rate of convergence when
it is relatively small and the sampling frequency has no effect on the optimal
rate when it is large. On the other hand, under the independent design, the
optimal rate of convergence is determined jointly by the sampling frequency and
the number of curves when the sampling frequency is relatively small. When it
is large, the sampling frequency has no effect on the optimal rate. Another
interesting contrast between the two settings is that smoothing is necessary
under the independent design, while, somewhat surprisingly, it is not essential
under the common design.Comment: Published in at http://dx.doi.org/10.1214/11-AOS898 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Cognitive Beamforming for Multiple Secondary Data Streams With Individual SNR Constraints
In this paper, we consider cognitive beamforming for multiple secondary data
streams subject to individual signal-to-noise ratio (SNR) requirements for each
secondary data stream. In such a cognitive radio system, the secondary user is
permitted to use the spectrum allocated to the primary user as long as the
caused interference at the primary receiver is tolerable. With both secondary
SNR constraint and primary interference power constraint, we aim to minimize
the secondary transmit power consumption. By exploiting the individual SNR
requirements, we formulate this cognitive beamforming problem as an
optimization problem on the Stiefel manifold. Both zero forcing beamforming
(ZFB) and nonzero forcing beamforming (NFB) are considered. For the ZFB case,
we derive a closed form beamforming solution. For the NFB case, we prove that
the strong duality holds for the nonconvex primal problem and thus the optimal
solution can be easily obtained by solving the dual problem. Finally, numerical
results are presented to illustrate the performance of the proposed cognitive
beamforming solutions.Comment: This is the longer version of a paper to appear in the IEEE
Transactions on Signal Processin
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