Dynamic non-linear optical processes in semiconductors

In this article active non-linear optical effects in semiconductors are reviewed. These processes arise because of the dynamics of excited populations of charge carriers temporarily created in otherwise empty states when a beam of laser radiation is incident on the material. A large number of different effects have been observed in different semiconductor materials recently and the non-linearities cover a wide range of magnitudes both in time-scale and size of non-linearity. The theory and physical concepts relevant to these processes are described and experimental observations using both high power pulsed and low power c.w. lasers are reviewed. Applications in optical bistability, phase conjugation, optical gating and optoelectronic gating are discussed.     

Infrared spectral changes with crystallization in poly(vinylchloride): Correlations with X-ray and density data

The influence of crystallinity and stereoregularity on the infrared (IR) spectrum of atactic PVC in the solid state has been studied by many researchers [1-12]. Although the molecules in commercial PVC consist of both syndiotactic and isotactic sequences, the bulk polymer is not highly stereoregular, having approximately 50% syndiotacticity. Its infrared spectrum is different from that of highly syndiotactic PVC [3,5,7,9,10-12], particularly in the carbon-to-chlorine stretching region where there are three bands located at 610(615), 635, and 690 cm^?1. These three bands are known to be of complex origin, since each band consists of more than one absorption frequency and its relative intensity depends on the physical state or history of the specimen [3,5,7,9,10-12]. The spectrum in this region is most rigorously interpreted in terms of chain conformational structure, the spatial arrangement of the atoms around the C-C1 bond. Thus, while changes in absorbance intensities for the bands with history do not necessarily reflect changes in crystallinity, their history dependence renders these bands potentially useful as crystallinity indicators.     

Investigating the mechanisms of diamond polishing using Raman spectroscopy

Recent research has shown that a phase transformation of diamond to a different form of carbon is involved when diamonds are polished in the traditional fashion. The question as to how this phase transformation is activated and maintained to produce high wear rates is of great technological interest since it may radically change the way we view the processing of diamond. This paper describes the use of Raman spectroscopy to examine debris produced on the diamond polishing wheel, both during its preparation and during polishing. In addition, polished diamond surfaces were examined for the possible existence of non-diamond surface layers in an attempt to identify material removal mechanisms. Raman spectroscopy proves ideal for these analyses because its relatively high spatial resolution is well suited to the analysis of small wear features and debris particles, and because of the wealth of information it reveals about chemical structure. This level of structural information has been lacking in previous analyses of diamond polishing debris. In addition to the non-diamond carbon found in the wear debris, significant quantities of two iron oxides, magnetite (Fe₃O₄) and haematite (α-Fe₂O₃), were also found. An interesting observation was that a transformation from magnetite to haematite could be induced either by using high power laser excitation or by frictional heating during polishing. It is suggested that some of the Raman peaks previously attributed to lonsdaleite might better be explained by the presence of these oxides.     

Relation between the common anion rule and the defect model of Schottky barrier formation

We present calculations of the energy levels of anion vacancies near the (110) surface of GaInAs, GaInP and GaAlAs. The results suggest that the defect model of Schottky barrier formation with anion vacancy-like states being responsible for Fermi level pinning is consistent with the common anion rule as observed in GaInAs and GaInP and also with the exception to the rule presented by GaAlAs.     

A Construction of Difference Sets in High Exponent 2-Groups Using Representation Theory

Nontrivial difference sets in groups of order a power of 2 are part of the family of difference sets called Menon difference sets (or Hadamard), and they have parameters (2^2d+2, 2^2d+1±2 ^d , 2^2d ±2 ^d ). In the abelian case, the group has a difference set if and only if the exponent of the group is less than or equal to 2 ^d+2. In [14], the authors construct a difference set in a nonabelian group of order 64 and exponent 32. This paper generalizes that result to show that there is a difference set in a nonabelian group of order 2^2d+2 with exponent 2 ^d+3. We use representation theory to prove that the group has a difference set, and this shows that representation theory can be used to verify a construction similar to the use of character theory in the abelian case.     

Lehmer pairs of zeros,the de Bruijn-Newman constant Λ, and the Riemann Hypothesis

We give here a rigorous formulation for a pair of consecutive simple positive zeros of the functionH ₀ (which is closely related to the Riemann -function) to be a Lehmer pair of zeros ofH ₀. With this formulation, we establish that each such pair of zeros gives a lower bound for the de Bruijn-Newman constant (where the Riemann Hypothesis is equivalent to the assertion that 0). We also numerically obtain the following new lower bound for :

Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features

Extraction of relevant lip features is of continuing interest in the visual speech domain. Using end-to-end feature extraction can produce good results, but at the cost of the results being difficult for humans to comprehend and relate to. We present a new, lightweight feature extraction approach, motivated by human-centric glimpse-based psychological research into facial barcodes, and demonstrate that these simple, easy to extract 3D geometric features (produced using Gabor-based image patches), can successfully be used for speech recognition with LSTM-based machine learning. This approach can successfully extract low dimensionality lip parameters with a minimum of processing. One key difference between using these Gabor-based features and using other features such as traditional DCT, or the current fashion for CNN features is that these are human-centric features that can be visualised and analysed by humans. This means that it is easier to explain and visualise the results. They can also be used for reliable speech recognition, as demonstrated using the Grid corpus. Results for overlapping speakers using our lightweight system gave a recognition rate of over 82%, which compares well to less explainable features in the literature.