Algorithms for determining the radial profile of the photoelastic coefficient in glass and polymer optical fibers

Abstract

We discuss two algorithms to determine the value and the radial profile of the photoelastic coefficient C in glass and polymer optical fibers. We conclude that C is constant over the fiber cross-sections, with exception of silica glass fibers containing a fluorine-doped depressed cladding. In the undoped and Ge-doped parts of these silica glass fibers we find a consistent value for C that is slightly larger than in bulk silica. In the fluorine-doped trenches of the absolute value of C decreases with about 27%. In polymethyl methacrylate optical fibers, the value of C significantly varies from fiber to fiber.

Case II diffusion of water in Na2O–3SiO2 glass: Constant tensile stress gradient at the diffusion interface

“…Results are reported as birefringence ($$\Delta /y)$$ alongside approximate equivalent stress. The stress optic coefficient variation with water content ahead the hydrated interface is expected to be small 23 . It is also likely that the effect upon stress optic coefficient is consistent across all heat‐treated samples.…”

“…The stress optic coefficient variation with water content ahead the hydrated interface is expected to be small. 23 It is also likely that the effect upon stress optic coefficient is consistent across all heat-treated samples.…”

Determination of the radial profile of the photoelastic coefficient of polymer optical fibers

“…In our previous publication [18] we introduced two algorithms to compute the inverse Abel transform. Both algorithms are based on Fourier theory but the approach is different.…”

“…Moreover, the first algorithm requires the integration of a derivative, which is very sensitive to measurement noise. To establish the radial distribution of the photoelastic constant, we have demonstrated in [18] that both algorithms are fully equivalent, but that the first algorithm requires a larger amount of Fourier coefficients. If we consider increased measurement noise, the influence of the noise on the inverse Abel transform becomes predominant and a large number of Fourier coefficients leads to very noisy shapes.…”