In this paper, an all-fiber Mach-Zehnder interferometer (MZI) based on a non-zero dispersion-shifted fiber (NZ-DSF) is presented. The MZI was implemented by core-offset fusion splicing one section of a NZ-DSF fiber between two pieces of single mode fibers (SMFs). Here, the NZ-DSF core and cladding were used as the arms of the MZI, while the core-offset sections acted as optical fiber couplers. Thus, a MZI interference spectrum with a fringe contrast (FC) of about 20 dB was observed. Moreover, its response spectrum was experimentally characterized to the torsion parameter and a sensitivity of 0.070 nm/° was achieved. Finally, these MZIs can be implemented in a compact size and low cost.

A distributed laser model is applied to explain the multi-peak shape of the pulses generated by the actively Q-switched erbium-doped fiber laser. In the model, all kinds of intra-cavity losses are taken into account, including the point losses produced by fiber splices and intra-cavity elements, and the distributed loss, such as the active fiber background loss and the loss caused by excited state absorption inherent in erbium-doped fibers. The model also takes into account the exact function that describes the switching dynamics of the Q-switch modulator. We show that the distributed model allows an accurate simulation of the laser pulse shape and energy, providing therefore a good agreement with the experimental results. The origin of a multi-peak pulse shape frequently observed in QS-EDFL and some other features that result from the model are discussed.

In this letter, a tunable filter design based on polymer and silicon layers is presented. It is shown that by taking advantage of the different thermal properties of these materials, the overall spectral and tuning characteristics can be controlled by selecting the thickness of these layers. Moreover, a mathematical model to simulate the reflectivity spectrum and the tuning behavior due to the temperature of the filter is presented. Finally, two filters were fabricated and their experimental behavior is well described by our mathematical approximation model.

In this letter, the viability of Artificial Neural Networks (ANNs) for widen the overall measurement range of optical sensors, based on interferometric arrangements, is demonstrated. Moreover, it is proven that by using ensembles of ANN regressions the traditional $2\pi $ ambiguity of interferometric sensors can be overcome. Here, a simple temperature sensor was implemented and from measured spectra a dataset of features was formed. For this sensor, the measurement range was increased by a factor of 2 and the achieved mean absolute error was $0.17{^{\circ }}\text{C}$ . Finally, it is shown that based on numerical results it can be expected that by using these types of ensembles the measurement range and the precision of predictions can be further enhanced.

In this work, a dual refractive index and temperature sensor based on an interferometric system and on the empirical mode decomposition (EMD) algorithm is presented. Here, it is shown that the EMD provides a comprehensive way to analyze and decompose complex reflection spectra produced by an interferometric filter build at the tip of an optical fiber. By applying the EMD algorithm, the spectrum can be decomposed into a set of intrinsic mode functions (IMF) from which the temperature and the refractive index can be easily extracted. Moreover, the proposed methodology provides a detailed insight of the behavior of this type of interferometric sensors and allows widening of the dynamic measurement ranges of both variables. Here, for proof of principle purposes, a filter based on a stack of three layers (two of them were thermo-sensitive) was fabricated. Finally, it is shown that the proposed methodology can decompose the experimental measured spectra and to determine the refractive index and the temperature, supporting the mathematical model.

Interferometric optical systems have been proposed for implementing dual‐parameter optical sensors. For this type of sensors, the sensitivity matrix equation is generally used to determine the parameters to be measured based on the sensitivity of each parameter to one particular feature of the output reflective spectrum of the interferometric system. One of the disadvantages of this method is that the measurement ranges will be very short if the sensitivities are not linear or if these present cross‐sensitivity. In this work, a multiple regression model for the simultaneous detection of refractive index and temperature based on an interferometric optical sensor is proposed. Here, the mathematical model is a weighted sum of features used to estimate the values of two response variables. These features are functions of an initial set of 27 explanatory variables whose values were extracted of the output reflective spectrum of the interferometric system. Besides, in order to sustenance the model application, the sensor was modeled and experimentally carried out. Three cases were studied: the estimation of temperature at different refractive indices, the estimation of temperature when refractive index is equal to one, and the estimation of refractive index at different temperatures. For each one of these cases, an optimal basis of functions was founded with the algorithm proposed and used to estimate the values of the response variables. Besides, a technique to reduce the initial set of variables was implemented. Finally, for the experimental data, For each one of these cases, an optimal basis of functions was founded with the algorithm 1 proposed and used to estimate the values of the response variables.