To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field spectrograph at the Anglo Australian Observatory. This system uses 400 fibres which can observe and measure the spectra of up to 400 astronomical objects in parallel. These optical fibres are positioned by a robotic arm. During placement, complex fibre entanglements often occur, reducing the overall efficiency of the system. This work aims to develop a combinatorial genetic algorithm which can help increase the efficiency of these systems by evolving sequences of fibre re-positionings. We present an integer-based representation developed for this GA which has the ability to automatically satisfy hard constraints during sequence seeding, mutation and recombination. We also present some initial results in re-configuring fibre placements.
The design of optical fibres for applications where many performance targets have to be met simultaneously is a non‐trivial process. An evolutionary strategy (ES) combined with an algorithm to model the appropriate fibre parameters was used to design an optical fibre suitable for long haul high bandwidth communications. The ES code was developed using an object oriented approach and a parallel version was also incorporated. This allowed for the rapid implementation and subsequent design of fibres with properties of interest. Design constraints arising from the fibre manufacturing process were incorporated.
Microstructured Polymer Optical Fibers (MPOF) were first made in 2001, and subsequent development has aimed at exploiting the material and design opportunities they present. Most effort has been focused on developing approaches for high bandwidth MPOF, and investigating the properties of multimode microstructured fibers. We also consider new applications in endoscopy and photonic interconnects, as well as the use of organic dopants in MPOF.
A multiobjective evolutionary algorithm was used to design a FBG for optical clock signal extraction, yielding a population of filters that are optimal with respect to three or four different spectral criteria.
A multiobjective evolutionary optimisation algorithm is applied to a fibre Bragg grating (optical filter) design problem. The design specified a dual wavelength filter with four required spectral characteristics - total bandwidth, peak separation, peak width and minimum transmission. Five parameters which described the apodised grating profile were used to define the search space and the transfer matrix method was used to numerically evaluate the transmission spectrum of candidate solutions. Various constraints on the search space were included in the design algorithm. Two separate selection schemes were tested, a distance based approach as used in the nondominated sorting genetic algorithm (NSGA-II) and a conglomerative clustering approach as used in the strength Pareto evolutionary algorithm (SPEA). Nondominated solutions are found and it is evident that particular objectives can be achieved more easily than others. Preliminary results are discussed and future work is introduced.
One of the major problems in fabricating polymer optical fibres is the difficulty in attaining a refractive index profile of choice, which requires careful control of the chemical composition. In addition, the use of dopants to modify the refractive index means that diffusion may be a problem. In this paper we describe a new approach to resolving these issues, which has many additional benefits. We have fabricated the first microstructured polymer optical fibres (MPOFs), in which the effective refractive index of the fibre is determined by the size and spacing of small holes, which run the length of the fibre. Both single mode and multimode fibres have been made from a single material (PMMA) without the use of dopants. These fibres have been tested and modeled. It is possible to use this approach to fabricate a variety of refractive index profiles.