Measuring temporal fluctuation on femtosecond scale in a random medium

We report an observation of femtosecond optical fluctuations of transmitted light when a coherent femtosecond pulse propagates through a random medium. They are a result of random interference among scattered waves coming from different trajectories in the time domain. Temporal fluctuations are measured by using cross-correlated frequency optical gating. It is shown that a femtosecond pulse will be broadened and distorted in pulse shape while it is propagating in random medium. The real and imaginary components of transmitted electric field are also distorted severely. The average of the fluctuated transmission pulses yields a smooth profile, probability functions show good agreement with Gaussian distribution. (c) 2007 Elsevier B.V. All rights reserved.

A novel hollow-core holey fibre with random hole distributions in the cladding

We provide a novel hollow-core holey fibre that owns a random distribution of air holes in the cladding. Our experiments demonstrate that many of the features previously attributed to photonic crystal fibres with perfect arrangement of air holes, in particular, photonic bandgap guidance, can also be obtained in the fibre. Additionally, this fibre exhibits a second guided mode with both the two-lobe patterns, and each pattern is in different colour.

Taxonomic status of the white-head langur (Trachypithecus francoisi leucoscephalus) inferred from allozyme electrophoresis and random amplified polymorphism DNA (RAPD)

Six sample specimens of Trachypithecus francoisi and 3 of T. leucocephalus were analyzed by use of allozyme electrophoresis and random amplified polymorphism DNA (RAPD) in order to clarify the challenged taxonomic status of the white-head langur. Among the 44 loci surveyed, only 1 locus (PGM-2) was found to be polymorphic. Nei's genetic distance was 0.0025. In total, thirty 10-mer arbitrary primers were used for RAPD analysis, of which 22 generated clear bands. Phylogenetic trees were constructed based on genetic distances using neighbor-joining and UPGMA methods. The results show that T. francoisi and T: leucocephalus are not monophyletic. T. francoisi from Guangxi, China and Vietnam could not be clearly distinguished, and they are not divided into 2 clusters. A t-test was performed to evaluate between genetic distances within and between T. leucocephalus and T. francoisi taxa groups. The statistical test shows that the taxa group within T: leucocephalus and T: francoisi does not significantly differ from that between T: leucocephalus and T: francoisi at the 5% level. Our results suggest that the level of genetic differentiation between T, leucocephalus and T. francoisi is relatively low. Recent gene flow might exist between T. francoisi and T. leucocephalus. Combining morphological features, geographical distribution, allozyme data, RAPD data, and mtDNA sequences, we suggest that the white-head langur might be a subspecies of T. francoisi.

A fully three-dimensional atomistic quantum mechanical study on random dopant-induced effects in 25-nm MOSFETs

A fully 3-D atomistic quantum mechanical simulation is presented to study the random dopant-induced effects in nanometer metal-oxide-semiconductor field-effect transistors. The empirical pseudopotential is used to represent the single particle Hamiltonian, and the linear combination of bulk band method is used to solve the million atom Schrodinger equation. The gate threshold fluctuation and lowering due to the discrete dopant configurations are studied. It is found that quantum mechanical effects increase the threshold fluctuation while decreasing the threshold lowering. The increase of threshold fluctuation is in agreement with the researchers' early study based on an approximated density gradient approach. However, the decrease in threshold lowering is in contrast with the density gradient calculations.

An ultra-low power CMOS random number generator

This paper proposes an ultra-low power CMOS random number generator (RING), which is based on an oscillator-sampling architecture. The noisy oscillator consists of a dual-drain MOS transistor, a noise generator and a voltage control oscillator. The dual-drain MOS transistor can bring extra-noise to the drain current or the output voltage so that the jitter of the oscillator is much larger than the normal oscillator. The frequency division ratio of the high-frequency sampling oscillator and the noisy oscillator is small. The RNG has been fabricated in a 0.35 mu m CMOS process. It can produce good quality bit streams without any post-processing. The bit rate of this RNG could be as high as 100 kbps. It has a typical ultra-low power dissipation of 0.91 mu W. This novel circuit is a promising unit for low power system and communication applications. (c) 2007 Elsevier Ltd. All rights reserved.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

Random telegraph noise in the photoluminescence of individual GaxIn1-xAs quantum dots in GaAs

We have investigated random telegraph noise in the photoluminescence from InGaAs quantum dots in GaAs. Dots switching among two and three levels have been measured. The experiments show that the switching InGaAs dots behave very similarly to switching InP dots in GaInP. but differently from the more commonly investigated colloidal dots. The switching is attributed to defects, and we show that the switching can be used as a monitor of the defect.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

Fully lithography independent fabrication of nanogap electrodes for lateral phase-change random access memory application

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