Characterization of integrated Bragg gratings in silicon-on-insulator

Silicon-on-insulator (SOI) is rapidly emerging as a very promising material platform for integrated photonics. As it combines the potential for optoelectronic integration with the low-cost and large volume manufacturing capabilities and they are already accumulate a huge amount of applications in areas like sensing, quantum optics, optical telecommunications and metrology. One of the main limitations of current technology is that waveguide propagation losses are still much higher than in standard glass-based platform because of many reasons such as bends, surface roughness and the very strong optical confinement provided by SOI. Such high loss prevents the fabrication of efficient optical resonators and complex devices severely limiting the current potential of the SOI platform. The project in the first part deals with the simple waveguides loss problem and trying to link that with the polarization problem and the loss based on Fabry-Perot Technique. The second part of the thesis deals with the Bragg Grating characterization from again the point of view of the polarization effect which leads to a better stop-band use filters. To a better comprehension a brief review on the basics of the SOI and the integrated Bragg grating ends up with the fabrication techniques and some of its applications will be presented in both parts, until the end of both the third and the fourth chapters to some results which hopefully make its precedent explanations easier to deal with.

An integrated system for building and running reproducible research

Our generation of computational scientists is living in an exciting time: not only do we get to pioneer important algorithms and computations, we also get to set standards on how computational research should be conducted and published. From Euclid’s reasoning and Galileo’s experiments, it took hundreds of years for the theoretical and experimental branches of science to develop standards for publication and peer review. Computational science, rightly regarded as the third branch, can walk the same road much faster. The success and credibility of science are anchored in the willingness of scientists to expose their ideas and results to independent testing and replication by other scientists. This requires the complete and open exchange of data, procedures and materials. The idea of a “replication by other scientists” in reference to computations is more commonly known as “reproducible research”. In this context the journal “EAI Endorsed Transactions on Performance & Modeling, Simulation, Experimentation and Complex Systems” had the exciting and original idea to make the scientist able to submit simultaneously the article and the computation materials (software, data, etc..) which has been used to produce the contents of the article. The goal of this procedure is to allow the scientific community to verify the content of the paper, reproducing it in the platform independently from the OS chosen, confirm or invalidate it and especially allow its reuse to reproduce new results. This procedure is therefore not helpful if there is no minimum methodological support. In fact, the raw data sets and the software are difficult to exploit without the logic that guided their use or their production. This led us to think that in addition to the data sets and the software, an additional element must be provided: the workflow that relies all of them.