A spectral method for determining the stability of periodically stationary pulses in fiber lasers is introduced. Pulse stability is characterized in terms of the spectrum (eigenvalues) of the monodromy operator, which is the linearization of the round trip operator about a periodically stationary pulse. A formula for the continuous (essential) spectrum of the monodromy operator is presented, which quantifies the growth and decay of continuous waves far from the pulse.
View Article and Find Full Text PDFWe describe a new class of surface flows, diffeomorphic surface flows, induced by restricting diffeomorphic flows of the ambient Euclidean space to a surface. Different from classical surface PDE flows such as mean curvature flow, diffeomorphic surface flows are solutions of integro-differential equations in a group of diffeomorphisms. They have the potential advantage of being both topology-invariant and singularity free, which can be useful in computational anatomy and computer graphics.
View Article and Find Full Text PDFWe study four-wave mixing between pulses in two subchannels of a quasi-linear 40-Gbit/s subchannel-multiplexed system. For a pseudorandom bit string there are resonances in the mean of the ghost pulse energy and in the jitter of the energy in the marks as functions of the subchannel frequency spacing. However, away from these resonances the effect of four-wave mixing decreases as the subchannel spacing increases, permitting propagation over longer distances.
View Article and Find Full Text PDFWe calculate the time shift function for collisions of pairs of pulses in different channels in a prototypical return-to-zero wavelength-division-multiplexed system with dispersion management and precompensation and postcompensation. Once the time shift function is known, the impairments that are due to collision-induced timing jitter can be rapidly determined. We characterize the shape of this function and determine how it scales with the initial pulse separation in time and with channel separation in wavelength.
View Article and Find Full Text PDFWe describe a neural network that enhances and completes salient closed contours in images. Our work is different from all previous work in three important ways. First, like the input provided to primary visual cortex (V1) by the lateral geniculate nucleus (LGN), the input to our computation is isotropic.
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