Some historical extracts relevant to the discovery and application of the diffraction of X-rays by crystals to contribute to the centennial celebration and the International Year of Crystallography

Illustrative extracts from the writings of Paul P. Ewald and of Max von Laue are presented. The latter in turn contains extensive text contributions from William Lawrence Bragg. These selections we have chosen so as to indicate the nature of the discovery of X-ray diffraction from crystals (experiments undertaken by Friedrich, Knipping and von Laue) and its early and prompt application in crystal structure analyses (by William Henry Bragg and William Lawrence Bragg). The platform for these discoveries was provided by a macroscopic physics problem dealt with by Ewald in his doctoral thesis with Arnold Sommerfeld in the Munich Physics Department, which is also where von Laue was based. W.L. Bragg was a student in Cambridge who used Trinity College Cambridge as his address on his early papers; experimental work was done by him in the Cavendish Laboratory, Cambridge, and also with his father, W.H. Bragg, in the Leeds University Physics Department. Of further historical interest is the award of an Honorary DSc (Doctor of Science) degree in 1936 to Max von Laue by the University of Manchester, UK, while William Lawrence Bragg was Langworthy Professor of Physics there. © 2012 Copyright Taylor and Francis Group, LLC.

The theory of on-line learning: a statistical physics approach

In this paper we review recent theoretical approaches for analysing the dynamics of on-line learning in multilayer neural networks using methods adopted from statistical physics. The analysis is based on monitoring a set of macroscopic variables from which the generalisation error can be calculated. A closed set of dynamical equations for the macroscopic variables is derived analytically and solved numerically. The theoretical framework is then employed for defining optimal learning parameters and for analysing the incorporation of second order information into the learning process using natural gradient descent and matrix-momentum based methods. We will also briefly explain an extension of the original framework for analysing the case where training examples are sampled with repetition.

Statistical physics of error-correcting codes

In this thesis we use statistical physics techniques to study the typical performance of four families of error-correcting codes based on very sparse linear transformations: Sourlas codes, Gallager codes, MacKay-Neal codes and Kanter-Saad codes. We map the decoding problem onto an Ising spin system with many-spins interactions. We then employ the replica method to calculate averages over the quenched disorder represented by the code constructions, the arbitrary messages and the random noise vectors. We find, as the noise level increases, a phase transition between successful decoding and failure phases. This phase transition coincides with upper bounds derived in the information theory literature in most of the cases. We connect the practical decoding algorithm known as probability propagation with the task of finding local minima of the related Bethe free-energy. We show that the practical decoding thresholds correspond to noise levels where suboptimal minima of the free-energy emerge. Simulations of practical decoding scenarios using probability propagation agree with theoretical predictions of the replica symmetric theory. The typical performance predicted by the thermodynamic phase transitions is shown to be attainable in computation times that grow exponentially with the system size. We use the insights obtained to design a method to calculate the performance and optimise parameters of the high performance codes proposed by Kanter and Saad.

The preparation of carbon fibres: a study of the physics and chemistry of the preparation of carbon fibres from acrylic precursors

High strength, high modulus carbon fibres are becoming increasingly important as high performance engineering materials. This thesis describes how they may be prepared by heat treatment from filaments spun from polyacrylonitrile and its copolymers. The chemistry of the first stages of heat treatment is very important in controlling the mechanical properties of the carbonised product. A cyclisation reaction has been found to be responsible for the relatively high thermal stability of pyrolysed polyacrylonitrile, but without oxidation the fibres degrade and fuse. An initial oxidation stage is, therefore, essential to the preparation of fibre of high orientation. The cyclised product of pyrolysis is probably a poly 1,4 dihydropiridine and oxidation converts this to aromatic structures, and cyclised structures containing carbonyl and other oxygenated groups. Oxidation is found to assist the carbon fibre preparation process, by producing a product which condenses at an earlier stage of heat treatment, before fusion can occur. Carbon fibre strength and modulus are dependent upon producing a highly oriented crystal structure. While oxidation of the polymer stabilises the fibre so as to prevent disorientation, further large increases in orientation, with a commensurate improvement in strength and modulus, can be obtained by stretching at temperatures above 1,700 °C. This process is analogous to the way fibre orientation is increased by the stretching of the precursor. A lamellar graphite structure can be created in high temperature fibre, by carefully controlling the degree of oxidation. This type of graphite can produce very high values of Young's modulus. More often, however, graphite fibre has a fibrillar fine structure, which is explicable in terms of continuous graphite ribbons. A ribbon model is the most satisfactory representation of the structure of carbon fibre, as it explains the mechanism of the development of long range order and the variation of Young's modulus with crystalline preferred orientation.

The influence of external forces on a monopolistic market:a statistical physics perspective

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