All-optical clock recovery using a ridge width varied two-section partly gain-coupled DFB self-pulsation laser

A 1.55 mu m InGaAsP-InP partly gain-coupled two-section DFB self-pulsation laser (SPL) with a varied ridge width has been fabricated. The laser produces self-pulsations with a frequency tuning range of more than 135 GHz. All-optical clock recovery from 40 Gb/s degraded data streams has been demonstrated. Successful lockings of the device at frequencies of 30 GHz, 40 GHz, 50 GHz, and 60 GHz to a 10 GHz sidemode injection are also conducted, which demonstrates the capability of the device for all-optical clock recovery at different frequencies. This flexibility of the device is highly desired for practical uses. Crown Copyright

OPTICAL CHARACTERISTICS OF GAAS/ALGAAS RIDGE-QUANTUM-WELL-WIRES GROWN BY MBE ON NONPLANAR SUBSTRATES

With conventional photolithography and wet chemical etching, we have realized GaAs/AlGaAs buried ridge-quantum-well-wires (RQWWs) with vertically stacked wires in lateral arrays promising for device application, which were grown in situ by a single-step molecular beam epitaxy growth and formed at the ridge tops of mesas on nonplanar substrates. Confocal photoluminescence (CPL) and polarization-dependent photoreflectance (PR) are applied to study optical characteristics of RQWWs. Lateral bandgap modulation due to lateral variation of QW layer thickness is demonstrated not only by CPL but also by PR. As one evidence for RQWWs, a large blue shift is observed at the energy level positions for electronic transitions corresponding to quantum wells (QWs) at the ridge tops of mesas compared with those corresponding to QWs on nonpatterned areas of the same sample. The blue shift is in contradiction with the fact that the GaAs QW layers at the tops of the mesas are thicker than those on nonpatterned areas. The other evidence for RQWWs, optical anisotropy is provided by the polarization-dependent PR, which results from lateral quantum size effect existing at the tops of the mesas.

Temperature Distribution in Ridge Structure InGaN Laser Diodes and Its Influence on Device Characteristics

Time-dependent thermal simulation of ridge-geometry InGaN laser diodes is carried out with a two-dimensional model. A high temperature in the waveguide layer and a large temperature step between the regions under and outside the ridge are generated due to the poor thermal conductivity of the sapphire substrate and the large threshold current and voltage. The temperature step is thought to have a strong influence on the characteristics of the laser diodes. Time-resolved measurements of light-current curves,spectra, and the far-field pattern of the InGaN laser diodes under pulsed operation are performed. The results show that the thermal lensing effect improves the confinement of the higher order modes and leads to a lower threshold current and a higher slope efficiency of the device while the high temperature in the active layer results in a drastic decrease in the slope efficiency.

Single ridge waveguide electroabsorption modulated DFB laser for 2.5Gb/s transmission

In this paper we proposed a single ridge waveguide electroabsorption modulated distributed feedback laser (EML) for long-haul high-speed optical fiber communication system. This EML was successfully fabricated by two step metal organic vapor phase epitaxy (MOVPE) including selective area growth (SAG) and helium partially implantation. No obvious changes of the threshold current (< 0.2 mA), extinction ratio (< 0.1 dB), output power (< 0.2 dBm) and isolation resistance were achieved in the preliminary aging test. With 2.5 Gb/s NRZ modulation, no power penalty was observed after the optical signal was transmitted through 280 Km normal single mode fiber.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381]; Chinese Academy of Sciences [KZCX2-YW-432]

Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression

Semisupervised dimensionality reduction has been attracting much attention as it not only utilizes both labeled and unlabeled data simultaneously, but also works well in the situation of out-of-sample. This paper proposes an effective approach of semisupervised dimensionality reduction through label propagation and label regression. Different from previous efforts, the new approach propagates the label information from labeled to unlabeled data with a well-designed mechanism of random walks, in which outliers are effectively detected and the obtained virtual labels of unlabeled data can be well encoded in a weighted regression model. These virtual labels are thereafter regressed with a linear model to calculate the projection matrix for dimensionality reduction. By this means, when the manifold or the clustering assumption of data is satisfied, the labels of labeled data can be correctly propagated to the unlabeled data; and thus, the proposed approach utilizes the labeled and the unlabeled data more effectively than previous work. Experimental results are carried out upon several databases, and the advantage of the new approach is well demonstrated.

Selection for variables in quantitative structure-activity/property relationship studies - Comparison between methods of orthogonal descriptors and leaps-and-bounds regression analysis

In this paper, the comparison of orthogonal descriptors and Leaps-and-Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps-and-Bounds regression for the data set of nitrobenzenes used in this study. Leaps-and-Bounds regression can be used effectively for selection of variables in quantitative structure-activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.

Studies on the method of leaps and bounds regression

In this paper, we introduce the method of leaps and bounds regression which can be used to select variables quickly and obtain the best regression models. These models contain one variable, two variables, three variables and so on. The results obtained by using leaps and bounds regression were compared with those achieved by using stepwise regression to lead to the conclusion that leaps and bounds regression is an effective method.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

Study on Phenol Compounds Using Multiple Regression and Neural Network Methods

In this paper, the molecular connectivity indices and the electronic charge parameters of forty-eight phenol compounds nave been calculated. and applied for studying the relationship between partition coefficients and structure of phenol compounds. The results demonstrate that the properties of compounds can be described better with selective parameters, and the results obtained by neural network are superior to that by multiplle regression.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.