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    Numerical Detection of Stochastic to Deterministic Transition

    Source: Journal of Computational and Nonlinear Dynamics:;2015:;volume( 010 ):;issue: 001::page 11001
    Author:
    Brojen Singh, R. K.
    DOI: 10.1115/1.4027441
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We present the numerical estimation of noise parameter induced in the dynamics of the variables by random particle interactions involved in the stochastic chemical oscillator and use it as order parameter to detect the transition from stochastic to deterministic regime. In stochastic regime, this noise parameter is found to be increased as system size decreases, whereas in deterministic regime it remains constant to minimum value as system size increases. This let the transition from fluctuating to fixed limit cycle oscillation as the system goes from stochastic to deterministic transition. We also numerically estimated the strength of the noise parameter involved both in chemical Langevin equation and Master equation formalisms and found that strength of this parameter is much smaller in the former than the latter.
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      Numerical Detection of Stochastic to Deterministic Transition

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    contributor authorBrojen Singh, R. K.
    date accessioned2017-05-09T01:15:31Z
    date available2017-05-09T01:15:31Z
    date issued2015
    identifier issn1555-1415
    identifier othercnd_010_01_011001.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/157226
    description abstractWe present the numerical estimation of noise parameter induced in the dynamics of the variables by random particle interactions involved in the stochastic chemical oscillator and use it as order parameter to detect the transition from stochastic to deterministic regime. In stochastic regime, this noise parameter is found to be increased as system size decreases, whereas in deterministic regime it remains constant to minimum value as system size increases. This let the transition from fluctuating to fixed limit cycle oscillation as the system goes from stochastic to deterministic transition. We also numerically estimated the strength of the noise parameter involved both in chemical Langevin equation and Master equation formalisms and found that strength of this parameter is much smaller in the former than the latter.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleNumerical Detection of Stochastic to Deterministic Transition
    typeJournal Paper
    journal volume10
    journal issue1
    journal titleJournal of Computational and Nonlinear Dynamics
    identifier doi10.1115/1.4027441
    journal fristpage11001
    journal lastpage11001
    identifier eissn1555-1423
    treeJournal of Computational and Nonlinear Dynamics:;2015:;volume( 010 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian