Narrow bandwidth Bragg gratings imprinted in polymer optical fibers for different spectral windows

The production and characterization of narrow bandwidth fiber Bragg gratings (FBGs) in different spectral regions using polymer optical fibers (POFs) is reported. Narrow bandwidth FBGs are increasingly important for POF transmission systems, WDM technology and sensing applications. Long FBGs with resonance wavelength around 600-nm, 850-nm and 1550-nm in several types of polymer optical fibers were inscribed using a scanning technique with a short optical path. The technique allowed the inscription in relative short periods of time. The obtained 3-dB bandwidth varies from 0.22 down to 0.045 nm considering a Bragg grating length between 10 and 25-mm, respectively.

Narrow bandwidth Bragg gratings imprinted in polymer optical fibers for different spectral windows

The production and characterization of narrow bandwidth fiber Bragg gratings (FBGs) in different spectral regions using polymer optical fibers (POFs) is reported. Narrow bandwidth FBGs are increasingly important for POF transmission systems, WDM technology and sensing applications. Long FBGs with resonance wavelength around 600-nm, 850-nm and 1550-nm in several types of polymer optical fibers were inscribed using a scanning technique with a short optical path. The technique allowed the inscription in relative short periods of time. The obtained 3-dB bandwidth varies from 0.22 down to 0.045 nm considering a Bragg grating length between 10 and 25-mm, respectively.

Narrow bandwidth Bragg gratings imprinted in polymer optical fibers for different spectral windows

The production and characterization of narrow bandwidth fiber Bragg gratings (FBGs) in different spectral regions using polymer optical fibers (POFs) is reported. Narrow bandwidth FBGs are increasingly important for POF transmission systems, WDM technology and sensing applications. Long FBGs with resonance wavelength around 600-nm, 850-nm and 1550-nm in several types of polymer optical fibers were inscribed using a scanning technique with a short optical path. The technique allowed the inscription in relative short periods of time. The obtained 3-dB bandwidth varies from 0.22 down to 0.045 nm considering a Bragg grating length between 10 and 25-mm, respectively. © 2013 Elsevier B.V.

An ultra-sensitive localised surface plasmon resonance fibre device for environmental sensing based upon a structured bi-metal coating

We demonstrate a bi-metal coating (platinum and gold or silver) localised surface plasmon resonance fibre device that produces an index spectral sensitivity of over 11,000 nm/RIU, yielding an index resolution of 5×10-6in the aqueous index regime, consisting of a structured multi-layered thin film on D-shaped fibre. © 2014 SPIE.

A comparison of the spectral properties of high temperature annealed long period gratings inscribed by fs laser, UV and fusion-arc

Long period gratings have been inscribed in standard single mode fibre using a fs laser system, a fusion arc and a UV laser and a comparative study carried out of their thermal behaviour. The fs laser induced gratings can survive temperatures in excess of 800°C, however the inscription process can induce considerable birefringence within the device. Annealing studies have been carried out showing that below 600°C, all three grating types show a blue shift in their room temperature resonance wavelengths following cyclic heating, while above 600°C, the UV and arc induced LPGs exhibit a red shift, with the fs LPG showing an even stronger blue shift. High temperature annealing is also shown to considerably reduce the birefringence induced by the fs inscription process.

Resonance fluorescence spectrum of a \Lambda-type quantum emitter close to a metallic nanoparticle

We theoretically study the resonance fluorescence spectrum of a three-level quantum emitter coupled to a spherical metallic nanoparticle. We consider the case that the quantum emitter is driven by a single laser field along one of the optical transitions. We show that the development of the spectrum depends on the relative orientation of the dipole moments of the optical transitions in relation to the metal nanoparticle. In addition, we demonstrate that the location and width of the peaks in the spectrum are strongly modified by the exciton-plasmon coupling and the laser detuning, allowing to achieve controlled strongly subnatural spectral line. A strong antibunching of the fluorescent photons along the undriven transition is also obtained. Our results may be used for creating a tunable source of photons which could be used for a probabilistic entanglement scheme in the field of quantum information processing.

Magnetic resonance spectroscopy. Data analysis for clinical applications

This text is taken from the postgraduate thesis, which one of the authors (A.B.) developed for the degree of Medical Physicist in the School on Medical Physics of the University of Florence. The text explores the feasibility of quantitative Magnetic Resonance Spectroscopy as a tool for daily clinical routine use. The results and analysis comes from two types of hyper spectral images: the first set are hyper spectral images coming from a standard phantom (reference images); and hyper spectral images obtained from a group of patients who have undergone MRI examinations at the Santa Maria Nuova Hospital. This interdisciplinary work stems from the IFAC-CNR know how in terms of data analysis and nanomedicine, and the clinical expertise of Radiologists and Medical Physicists. The results reported here, which were the subject of the thesis, are original, unpublished, and represent independent work.

Evolution of classifiers for pitch estimation of piano music using cartesian genetic programming

Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

Speaker identification using higher order spectral phase features and their effectiveness vis-a-vis Mel-Cepstral features

The effectiveness of higher-order spectral (HOS) phase features in speaker recognition is investigated by comparison with Mel Cepstral features on the same speech data. HOS phase features retain phase information from the Fourier spectrum unlikeMel–frequency Cepstral coefficients (MFCC). Gaussian mixture models are constructed from Mel– Cepstral features and HOS features, respectively, for the same data from various speakers in the Switchboard telephone Speech Corpus. Feature clusters, model parameters and classification performance are analyzed. HOS phase features on their own provide a correct identification rate of about 97% on the chosen subset of the corpus. This is the same level of accuracy as provided by MFCCs. Cluster plots and model parameters are compared to show that HOS phase features can provide complementary information to better discriminate between speakers.