2017 |
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3. | Ujjwal, Sangeeta R; Ramaswamy, Ram Symmetries and symmetry-breaking in oscillator ensembles Journal Article Physics News, 47 (2), pp. 11–16, 2017. Links | BibTeX | Tags: Chaos Theory, Symmetry Breaking @article{Ujjwal2017b, title = {Symmetries and symmetry-breaking in oscillator ensembles}, author = {Sangeeta R Ujjwal and Ram Ramaswamy}, url = {https://ramramaswamy.org/papers/.pdf}, year = {2017}, date = {2017-01-01}, journal = {Physics News}, volume = {47}, number = {2}, pages = {11–16}, keywords = {Chaos Theory, Symmetry Breaking}, pubstate = {published}, tppubtype = {article} } |
2010 |
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2. | T U Singh H H Jafri, ; Ramaswamy, R Transition to weak generalized synchrony in chaotically driven flows Journal Article Physical Review E, 81 (1), pp. 016208, 2010. Abstract | Links | BibTeX | Tags: Chaos Theory, Generalized Synchronization @article{Singh2010b, title = {Transition to weak generalized synchrony in chaotically driven flows}, author = {T U Singh, H H Jafri, and R Ramaswamy}, url = {https://link.aps.org/doi/10.1103/PhysRevE.81.016208}, doi = {10.1103/PhysRevE.81.016208}, year = {2010}, date = {2010-01-14}, journal = {Physical Review E}, volume = {81}, number = {1}, pages = {016208}, abstract = {We study regimes of strong and weak generalized synchronization in chaotically forced nonlinear flows. The transition between these dynamical states can occur via a number of different routes, and here we examine the onset of weak generalized synchrony through intermittency and blowout bifurcations. The quantitative characterization of this dynamical transition is facilitated by measures that have been developed for the study of strange nonchaotic motion. Weak and strong generalized synchronous motion show contrasting sensitivity to parametric variation and have distinct distributions of finite-time Lyapunov exponents.}, keywords = {Chaos Theory, Generalized Synchronization}, pubstate = {published}, tppubtype = {article} } We study regimes of strong and weak generalized synchronization in chaotically forced nonlinear flows. The transition between these dynamical states can occur via a number of different routes, and here we examine the onset of weak generalized synchrony through intermittency and blowout bifurcations. The quantitative characterization of this dynamical transition is facilitated by measures that have been developed for the study of strange nonchaotic motion. Weak and strong generalized synchronous motion show contrasting sensitivity to parametric variation and have distinct distributions of finite-time Lyapunov exponents. |
1996 |
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1. | Mehra, V; Ramaswamy, R Maximal Lyapunov exponent at crises Journal Article Physical Review E, 53 (4), pp. 3420-3424, 1996. Abstract | Links | BibTeX | Tags: Chaos Theory, Lyapunov exponent @article{Mehra1996, title = {Maximal Lyapunov exponent at crises}, author = {V Mehra and R Ramaswamy }, url = {https://link.aps.org/doi/10.1103/PhysRevE.53.3420}, doi = {10.1103/PhysRevE.53.3420}, year = {1996}, date = {1996-04-01}, journal = {Physical Review E}, volume = {53}, number = {4}, pages = {3420-3424}, abstract = {We study the variation of Lyapunov exponents of simple dynamical systems near attractor-widening and attractor-merging crises. The largest Lyapunov exponent has universal behavior, showing abrupt variation as a function of the control parameter as the system passes through the crisis point, either in the value itself, in the case of an attractor-widening crisis, or in the slope, for an attractor-merging crisis. The distribution of local Lyapunov exponents is very different for the two cases: the fluctuations remain constant through a merging crisis, but there is a dramatic increase in the fluctuations at a widening crisis.}, keywords = {Chaos Theory, Lyapunov exponent}, pubstate = {published}, tppubtype = {article} } We study the variation of Lyapunov exponents of simple dynamical systems near attractor-widening and attractor-merging crises. The largest Lyapunov exponent has universal behavior, showing abrupt variation as a function of the control parameter as the system passes through the crisis point, either in the value itself, in the case of an attractor-widening crisis, or in the slope, for an attractor-merging crisis. The distribution of local Lyapunov exponents is very different for the two cases: the fluctuations remain constant through a merging crisis, but there is a dramatic increase in the fluctuations at a widening crisis. |