2004
DOI: 10.1163/156939304323062004
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Dynamics of Stochastic Optical Solitons

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Cited by 13 publications
(8 citation statements)
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“…In most instances, a consequence of this is an adiabatic deformation of the soliton parameters like its amplitude, width, frequency and velocity accompanied by small amounts of radiation or small amplitudedispersive waves. The adiabatic parameter dynamics and the evolution of energy, in presence of perturbation terms, neglecting the radiation, are [2,[16][17][18] …”
Section: Perturbation Termsmentioning
confidence: 99%
See 1 more Smart Citation
“…In most instances, a consequence of this is an adiabatic deformation of the soliton parameters like its amplitude, width, frequency and velocity accompanied by small amounts of radiation or small amplitudedispersive waves. The adiabatic parameter dynamics and the evolution of energy, in presence of perturbation terms, neglecting the radiation, are [2,[16][17][18] …”
Section: Perturbation Termsmentioning
confidence: 99%
“…It can be assumed that noise is distributed all along the fiber length since the amplifier spacing satisfies z a 51 [3,18]. In (27), sðx; tÞ represents the Markovian stochastic process with Gaussian statistics and is assumed that sðx; tÞ [14,[16][17][18] is a function of t only so that sðx; tÞ ¼ sðtÞ. Now, the complex stochastic term sðtÞ can be decomposed into real and imaginary parts as…”
Section: Perturbation Termsmentioning
confidence: 99%
“…In (23), it is necessary to have 0 < p < 2 to prevent wave collapse (Biswas, 2003(Biswas, , 2004 and, in particular, p = 2 to avoid self-focussing singularity (Abdullaev and Garnier, 1999). The soliton solution of (23) is given by (Biswas, 2003) q…”
Section: Power Law Nonlinearitymentioning
confidence: 99%
“…It can be assumed that noise is distributed all along the fiber length since the amplifier spacing satisfies z a 1 (Kivshar and Agarwal, 2003). In (8), σ (x, t) represents the Markovian stochastic process with Gaussian statistics and is assumed that σ (x, t) (Biswas, 2004;Elgin, 1993) is a function of t only so that σ (x, t) = σ (t). Now, the complex stochastic term σ (t) can be decomposed into real and imaginary parts as…”
Section: Power Law Nonlinearitymentioning
confidence: 99%
“…These include the Painleve analysis, Hirota bilinear method, Ablowitz-Kaup-NewellSegur (AKNS) technique, Darboux-Backlund transform, collective variable (CV) approach, Lagrangian variational method etc. [9][10][11][12][13][14][15][16][17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%