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Studying the performance of critical slowing down indicators in a biological system with a period-doubling route to chaos
This paper aims to investigate critical slowing down indicators in different situations where the system’s parameters change. Variation of the bifurcation parameter is important since it allows finding bifurcation points. A system’s parameters can vary through different functions. In this paper, fiv...
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Published in: | Physica A 2020-04, Vol.544, p.123396, Article 123396 |
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description | This paper aims to investigate critical slowing down indicators in different situations where the system’s parameters change. Variation of the bifurcation parameter is important since it allows finding bifurcation points. A system’s parameters can vary through different functions. In this paper, five cases of bifurcation parameter variation are considered in a biological model with a period-doubling route to chaos. The first case is a slow and small stepwise variation of the bifurcation parameter. The second case is a cyclic, state-dependent variation of the bifurcation parameter. In the third case, a small cyclic variation is combined with a sizeable stochastic resonance. The fourth case involves variations by a large noise, and finally, in the fifth case, significant stepwise changes in the parameter are studied. To identify the conditions under which critical slowing down occurs, an improved version of four well-known critical slowing down indicators (autocorrelation at lag-1, variance, kurtosis, and skewness) are used. The results show that when bifurcations are caused by a sudden change in a parameter or state, critical slowing down cannot be observed before the bifurcation points. However, in cases with slowly varying parameters, critical slowing down can be detected before the bifurcation points. Thus critical slowing down indicators can predict these bifurcation points. In other words, in three cases, the system approaches bifurcation points slowly. In other cases, the bifurcations occur suddenly because of a significant shift in the parameter or state. Thus critical slowing down indicators cannot predict those bifurcation points. However, critical slowing down indicators can predict the bifurcation points in other cases.
•Critical transitions in different situations.•Critical slowing down in many bifurcations.•Prediction of critical slowing down. |
doi_str_mv | 10.1016/j.physa.2019.123396 |
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•Critical transitions in different situations.•Critical slowing down in many bifurcations.•Prediction of critical slowing down.</description><subject>Bifurcation parameter</subject><subject>Critical slowing down</subject><subject>Period-doubling route to chaos</subject><issn>0378-4371</issn><issn>1873-2119</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRS0EEqXwBWz8Awm2x3ktWKCKl4TEAlhbjh-NqzSubJcqf09CWLOa0cw9o9FB6JaSnBJa3u3yQzdGmTNCm5wygKY8QytaV5AxSptztCJQ1RmHil6iqxh3hBBaAVuh8SMd9eiGLU6dwQcTrA97OSiDvcUquOSU7HHs_WnOaH8asBv0NEw-xKnFErfO93675MaYzB6fXOqmxXTNeZ1pf2z7mQ7-mAxOHqtO-niNLqzso7n5q2v09fT4uXnJ3t6fXzcPb5kCAikDzWtKiFK8sKBly6q25lZrxgF0QZuisSAbwqAmtqSyak1bcE4tb2xZKc1gjWC5q4KPMRgrDsHtZRgFJWK2J3bi156Y7YnF3kTdL5SZXvt2JoionJm8aBeMSkJ79y__A6NTfC4</recordid><startdate>20200415</startdate><enddate>20200415</enddate><creator>Navid Moghadam, Nastaran</creator><creator>Nazarimehr, Fahimeh</creator><creator>Jafari, Sajad</creator><creator>Sprott, Julien C.</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20200415</creationdate><title>Studying the performance of critical slowing down indicators in a biological system with a period-doubling route to chaos</title><author>Navid Moghadam, Nastaran ; Nazarimehr, Fahimeh ; Jafari, Sajad ; Sprott, Julien C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-3d48100cc45f3dab27b84fdd2433d51959f3a902380f61a7beb5441f49f67cd23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Bifurcation parameter</topic><topic>Critical slowing down</topic><topic>Period-doubling route to chaos</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Navid Moghadam, Nastaran</creatorcontrib><creatorcontrib>Nazarimehr, Fahimeh</creatorcontrib><creatorcontrib>Jafari, Sajad</creatorcontrib><creatorcontrib>Sprott, Julien C.</creatorcontrib><collection>CrossRef</collection><jtitle>Physica A</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Navid Moghadam, Nastaran</au><au>Nazarimehr, Fahimeh</au><au>Jafari, Sajad</au><au>Sprott, Julien C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Studying the performance of critical slowing down indicators in a biological system with a period-doubling route to chaos</atitle><jtitle>Physica A</jtitle><date>2020-04-15</date><risdate>2020</risdate><volume>544</volume><spage>123396</spage><pages>123396-</pages><artnum>123396</artnum><issn>0378-4371</issn><eissn>1873-2119</eissn><abstract>This paper aims to investigate critical slowing down indicators in different situations where the system’s parameters change. Variation of the bifurcation parameter is important since it allows finding bifurcation points. A system’s parameters can vary through different functions. In this paper, five cases of bifurcation parameter variation are considered in a biological model with a period-doubling route to chaos. The first case is a slow and small stepwise variation of the bifurcation parameter. The second case is a cyclic, state-dependent variation of the bifurcation parameter. In the third case, a small cyclic variation is combined with a sizeable stochastic resonance. The fourth case involves variations by a large noise, and finally, in the fifth case, significant stepwise changes in the parameter are studied. To identify the conditions under which critical slowing down occurs, an improved version of four well-known critical slowing down indicators (autocorrelation at lag-1, variance, kurtosis, and skewness) are used. The results show that when bifurcations are caused by a sudden change in a parameter or state, critical slowing down cannot be observed before the bifurcation points. However, in cases with slowly varying parameters, critical slowing down can be detected before the bifurcation points. Thus critical slowing down indicators can predict these bifurcation points. In other words, in three cases, the system approaches bifurcation points slowly. In other cases, the bifurcations occur suddenly because of a significant shift in the parameter or state. Thus critical slowing down indicators cannot predict those bifurcation points. However, critical slowing down indicators can predict the bifurcation points in other cases.
•Critical transitions in different situations.•Critical slowing down in many bifurcations.•Prediction of critical slowing down.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.physa.2019.123396</doi></addata></record> |
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subjects | Bifurcation parameter Critical slowing down Period-doubling route to chaos |
title | Studying the performance of critical slowing down indicators in a biological system with a period-doubling route to chaos |
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