Optical rogue waves in telecommunication data streams

Large broadening of short optical pulses due to fiber dispersion leads to a strong overlap in information data streams resulting in statistical deviations of the local power from its average. We present a theoretical analysis of rare events of high-intensity fluctuations-optical freak waves-that occur in fiber communication links using bit-overlapping transmission. Although the nature of the large fluctuations examined here is completely linear, as compared to commonly studied freak waves generated by nonlinear effects, the considered deviations inherit from rogue waves the key features of practical interest-random appearance of localized high-intensity pulses. We use the term "rogue wave" in an unusual context mostly to attract attention to both the possibility of purely linear statistical generation of huge amplitude waves and to the fact that in optics the occurrence of such pulses might be observable even with the standard Gaussian or even rarer-than-Gaussian statistics, without imposing the condition of an increased probability of extreme value events. © 2011 American Physical Society.

Reply to "comment on 'Optical rogue waves in telecommunication data streams'"

We feel that the main claim made in the abstract of the preceding Comment is wrong. Using results obtained in our paper, we prove that rogue waves with amplitudes much larger than the average level can be observed during a short period of time in purely linear propagation regimes in optical fiber systems. © 2011 American Physical Society.

Optical interconnection of core and metro networks

A network concept is introduced that exploits transparent optical grooming of traffic between an access network and a metro core ring network. This network is enabled by an optical router that allows bufferless aggregation of metro network traffic into higher-capacity data streams for core network transmission. A key functionality of the router is WDM to time-division multiplexing (TDM) transmultiplexing.

All-optical nonlinear pulse processing based on normal dispersion fiber-enhanced nonlinear optical loop mirror

A novel simple all-optical nonlinear pulse processing technique using loop mirror intensity filtering and nonlinear broadening in normal dispersion fiber is described. The pulse processor offers reamplification and cleaning up of the optical signals and phase margin improvement. The efficiency of the technique is demonstrated by application to 40-Gb/s return-to-zero optical data streams.

Normal dispersion fibre-enhanced nonlinear optical loop mirror for 2R regeneration and phase margin improvement

A novel all-optical regeneration technique using loop-mirror intensity-filtering and nonlinear broadening in normal-dispersion fibre is described. The device offers 2R-regeneration function and phase margin improvement. The technique is applied to 40Gbit/s return-to-zero optical data streams.

Normal dispersion fibre-enhanced nonlinear optical loop mirror for 2R regeneration and phase margin improvement

A novel all-optical regeneration technique using loop-mirror intensity-filtering and nonlinear broadening in normal-dispersion fibre is described. The device offers 2R-regeneration function and phase margin improvement. The technique is applied to 40Gbit/s return-to-zero optical data streams.

All-optical nonlinear pulse processing based on normal dispersion fiber-enhanced nonlinear optical loop mirror

A novel simple all-optical nonlinear pulse processing technique using loop mirror intensity filtering and nonlinear broadening in normal dispersion fiber is described. The pulse processor offers reamplification and cleaning up of the optical signals and phase margin improvement. The efficiency of the technique is demonstrated by application to 40-Gb/s return-to-zero optical data streams. © 2004 IEEE.

Statnote 36: Do the data fit the Poisson distribution

In previous Statnotes, many of the statistical tests described rely on the assumption that the data are a random sample from a normal or Gaussian distribution. These include most of the tests in common usage such as the ‘t’ test ), the various types of analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’) . In microbiology research, however, not all variables can be assumed to follow a normal distribution. Yeast populations, for example, are a notable feature of freshwater habitats, representatives of over 100 genera having been recorded . Most common are the ‘red yeasts’ such as Rhodotorula, Rhodosporidium, and Sporobolomyces and ‘black yeasts’ such as Aurobasidium pelculans, together with species of Candida. Despite the abundance of genera and species, the overall density of an individual species in freshwater is likely to be low and hence, samples taken from such a population will contain very low numbers of cells. A rare organism living in an aquatic environment may be distributed more or less at random in a volume of water and therefore, samples taken from such an environment may result in counts which are more likely to be distributed according to the Poisson than the normal distribution. The Poisson distribution was named after the French mathematician Siméon Poisson (1781-1840) and has many applications in biology, especially in describing rare or randomly distributed events, e.g., the number of mutations in a given sequence of DNA after exposure to a fixed amount of radiation or the number of cells infected by a virus given a fixed level of exposure. This Statnote describes how to fit the Poisson distribution to counts of yeast cells in samples taken from a freshwater lake.