22 resultados para wide gain bandwidth


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Nonlinear CW pump broadening over non-standard transmission fiber is used for the first time to achieve superior gain variation performance in a single-pump broadband Raman amplifier. A threefold increase in the bandwidth for 0.1 dB gain variation is reported.

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We have generated near-transform-limited picosecond pulses(ΔτΔν≈0.45) from a gain-switched diode laser using periodic and chirped fiber Bragg gratings. This configuration reduced the spectral bandwidth from 11 to 0.08 nm and the pulse duration was reduced, from 30 to<18 ps. Average and peak powers of 27 and 770 mW, respectively, were obtained.

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We use the GN-model to assess Nyquist-WDM 100/200Gbit/s PM-QPSK/16QAM signal reach on low loss, large core area fibre using extended range, variable gain hybrid Raman-EDFAs. 5000/1500km transmission is possible over a wide range of amplifier spans. © OSA 2014.

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For the first time, we demonstrate the possibility to switch between three distinct pulse regimes in a dissipative dispersion-managed (DM) fibre laser by solely controlling the gain saturation energy. Nonlinear Schrödinger equation based simulations show the transitions between hyper-Gaussian similaritons, parabolic similaritons, and dissipative solitons in the same laser cavity. It is also shown that such transitions exist in a wide dispersion range from all-normal to slightly net-normal dispersion. This work demonstrates that besides dispersion and filter managements gain saturation energy can be a new degree of freedom to manage pulse regimes in DM fibre lasers, which offers flexibility in designing ultrafast fibre lasers. Also, the result indicates that in contrast to conservative soliton lasers whose intensity profiles are unique, dissipative DM lasers show diversity in pulse shapes. The findings not only give a better understanding of pulse shaping mechanisms in mode-locked lasers, but also provide insight into dissipative systems.

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How are the image statistics of global image contrast computed? We answered this by using a contrast-matching task for checkerboard configurations of ‘battenberg’ micro-patterns where the contrasts and spatial spreads of interdigitated pairs of micro-patterns were adjusted independently. Test stimuli were 20 × 20 arrays with various sized cluster widths, matched to standard patterns of uniform contrast. When one of the test patterns contained a pattern with much higher contrast than the other, that determined global pattern contrast, as in a max() operation. Crucially, however, the full matching functions had a curious intermediate region where low contrast additions for one pattern to intermediate contrasts of the other caused a paradoxical reduction in perceived global contrast. None of the following models predicted this: RMS, energy, linear sum, max, Legge and Foley. However, a gain control model incorporating wide-field integration and suppression of nonlinear contrast responses predicted the results with no free parameters. This model was derived from experiments on summation of contrast at threshold, and masking and summation effects in dipper functions. Those experiments were also inconsistent with the failed models above. Thus, we conclude that our contrast gain control model (Meese & Summers, 2007) describes a fundamental operation in human contrast vision.

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We present an ultra-long Raman fibre laser amplified system which, with only a single pump wavelength, provides comparable gain flatness and broader spectral bandwidth than a conventional gain flattened C-band EDFA. A 20x42.7Gb/s experiment shows compatibility with DWDM systems. ©2010 IEEE.

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This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.