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Effective long-time phase dynamics of limit-cycle oscillators driven by weak colored noise. (English) Zbl 1311.34086

Summary: An effective white-noise Langevin equation is derived that describes long-time phase dynamics of a limit-cycle oscillator driven by weak stationary colored noise. Effective drift and diffusion coefficients are given in terms of the phase sensitivity of the oscillator and the correlation function of the noise, and are explicitly calculated for oscillators with sinusoidal phase sensitivity functions driven by two typical colored Gaussian processes. The results are verified by numerical simulations using several types of stochastic or chaotic noise. The drift and diffusion coefficients of oscillators driven by chaotic noise exhibit anomalous dependence on the oscillator frequency, reflecting the peculiar power spectrum of the chaotic noise.{
©2010 American Institute of Physics}

MSC:

34C15 Nonlinear oscillations and coupled oscillators for ordinary differential equations
34F05 Ordinary differential equations and systems with randomness
34C28 Complex behavior and chaotic systems of ordinary differential equations
60H10 Stochastic ordinary differential equations (aspects of stochastic analysis)

References:

[1] DOI: 10.1016/0022-5193(67)90051-3 · doi:10.1016/0022-5193(67)90051-3
[2] DOI: 10.1007/978-1-4757-3484-3 · doi:10.1007/978-1-4757-3484-3
[3] DOI: 10.1007/978-3-642-69689-3 · doi:10.1007/978-3-642-69689-3
[4] Pikovsky A., Synchronization: A Universal Concept in Nonlinear Sciences (2003) · Zbl 1219.37002
[5] Koch C., Biophysics of Computation (1999)
[6] DOI: 10.1103/PhysRevE.80.011918 · doi:10.1103/PhysRevE.80.011918
[7] DOI: 10.1177/027836499000900206 · doi:10.1177/027836499000900206
[8] DOI: 10.1038/43843a · doi:10.1038/43843a
[9] Rinzel J., Methods in Neuronal Modeling (1998)
[10] DOI: 10.1209/0295-5075/23/5/011 · doi:10.1209/0295-5075/23/5/011
[11] DOI: 10.1007/BF00160535 · Zbl 0718.92004 · doi:10.1007/BF00160535
[12] DOI: 10.1162/neco.1996.8.5.979 · doi:10.1162/neco.1996.8.5.979
[13] DOI: 10.1143/PTP.75.1105 · doi:10.1143/PTP.75.1105
[14] DOI: 10.1016/0167-2789(91)90001-P · Zbl 0749.58044 · doi:10.1016/0167-2789(91)90001-P
[15] DOI: 10.1103/PhysRevLett.71.807 · doi:10.1103/PhysRevLett.71.807
[16] DOI: 10.1103/PhysRevE.50.3249 · doi:10.1103/PhysRevE.50.3249
[17] DOI: 10.1103/PhysRevE.70.026210 · doi:10.1103/PhysRevE.70.026210
[18] DOI: 10.1103/PhysRevE.75.036209 · doi:10.1103/PhysRevE.75.036209
[19] DOI: 10.1209/0295-5075/88/60005 · doi:10.1209/0295-5075/88/60005
[20] DOI: 10.1103/PhysRevLett.93.244102 · doi:10.1103/PhysRevLett.93.244102
[21] DOI: 10.1103/PhysRevLett.93.244102 · doi:10.1103/PhysRevLett.93.244102
[22] DOI: 10.1016/j.jsv.2005.03.010 · doi:10.1016/j.jsv.2005.03.010
[23] DOI: 10.1103/PhysRevE.77.036218 · doi:10.1103/PhysRevE.77.036218
[24] DOI: 10.1103/PhysRevE.79.036205 · doi:10.1103/PhysRevE.79.036205
[25] DOI: 10.1126/science.7770778 · doi:10.1126/science.7770778
[26] Binder M. D., J. Neurophysiol. 86 pp 2266– (2001)
[27] DOI: 10.1523/JNEUROSCI.4605-05.2006 · doi:10.1523/JNEUROSCI.4605-05.2006
[28] DOI: 10.1529/biophysj.106.088021 · doi:10.1529/biophysj.106.088021
[29] DOI: 10.1071/ZO9530291 · doi:10.1071/ZO9530291
[30] DOI: 10.1007/978-94-011-2916-9 · doi:10.1007/978-94-011-2916-9
[31] DOI: 10.2307/3545809 · doi:10.2307/3545809
[32] DOI: 10.1038/24293 · doi:10.1038/24293
[33] DOI: 10.1162/089976602317318956 · Zbl 0987.92009 · doi:10.1162/089976602317318956
[34] DOI: 10.1143/PTPS.161.360 · doi:10.1143/PTPS.161.360
[35] DOI: 10.1143/PTPS.161.360 · doi:10.1143/PTPS.161.360
[36] DOI: 10.1103/PhysRevE.78.060104 · doi:10.1103/PhysRevE.78.060104
[37] DOI: 10.1103/PhysRevE.78.060104 · doi:10.1103/PhysRevE.78.060104
[38] DOI: 10.1103/PhysRevE.78.060104 · doi:10.1103/PhysRevE.78.060104
[39] DOI: 10.1103/PhysRevE.78.060104 · doi:10.1103/PhysRevE.78.060104
[40] DOI: 10.1103/PhysRevLett.98.184101 · doi:10.1103/PhysRevLett.98.184101
[41] DOI: 10.1103/PhysRevE.76.056110 · doi:10.1103/PhysRevE.76.056110
[42] DOI: 10.1103/PhysRevE.72.026220 · doi:10.1103/PhysRevE.72.026220
[43] DOI: 10.1143/PTPS.161.294 · doi:10.1143/PTPS.161.294
[44] DOI: 10.1143/PTPS.161.294 · doi:10.1143/PTPS.161.294
[45] DOI: 10.1103/PhysRevLett.101.154101 · doi:10.1103/PhysRevLett.101.154101
[46] DOI: 10.1103/PhysRevLett.102.194102 · doi:10.1103/PhysRevLett.102.194102
[47] DOI: 10.1073/pnas.85.7.2029 · doi:10.1073/pnas.85.7.2029
[48] DOI: 10.1103/PhysRevLett.72.2984 · doi:10.1103/PhysRevLett.72.2984
[49] DOI: 10.1103/PhysRevLett.87.010602 · doi:10.1103/PhysRevLett.87.010602
[50] DOI: 10.1023/A:1023635805818 · Zbl 1031.34051 · doi:10.1023/A:1023635805818
[51] DOI: 10.1016/j.physleta.2005.06.115 · Zbl 1194.60057 · doi:10.1016/j.physleta.2005.06.115
[52] DOI: 10.1103/PhysRevLett.98.044102 · doi:10.1103/PhysRevLett.98.044102
[53] Pavliotis G. A., Multiscale Methods: Averaging and Homogenization (2008)
[54] DOI: 10.1007/978-3-662-05389-8 · doi:10.1007/978-3-662-05389-8
[55] DOI: 10.1007/978-3-642-61544-3 · doi:10.1007/978-3-642-61544-3
[56] DOI: 10.1152/jn.00563.2007 · doi:10.1152/jn.00563.2007
[57] DOI: 10.1007/s10827-008-0120-8 · doi:10.1007/s10827-008-0120-8
[58] Arfken G. B., Mathematical Methods for Physicists (2001) · Zbl 0970.00005
[59] DOI: 10.1103/PhysRevE.80.011911 · doi:10.1103/PhysRevE.80.011911
[60] DOI: 10.1162/089976604322860668 · Zbl 1054.92006 · doi:10.1162/089976604322860668
[61] DOI: 10.1103/PhysRevE.80.036113 · doi:10.1103/PhysRevE.80.036113
[62] Strogatz S. H., Nonlinear Dynamics and Chaos (2001)
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