Ying-Cheng Lai - Selected Publications#

Journal publications (as of July 27, 2020): approximately 495 (125 in the last 5 years); Original Contributions in Proceedings: 40; Google Scholar (as of July 27, 2020): 23,500 citations, h-index = 73, i10 index = 369 (1,814 citations in 2019)

1. L.-Z. Wang, R.-Q. Su, Z.-G. Huang, X. Wang, W.-X. Wang, C. Grebogi, and Y.-C. Lai*, "A geometrical approach to control and controllability of nonlinear dynamical networks," Nature Communications 7, 11323, 1-11 (2016). Controlling nonlinear network dynamics represents a challenging and outstanding problem in complex systems. This paper developed an experimentally feasible control framework for nonlinear dynamical networks with applications to controlling synthetic biological circuits.

2. W.-X. Wang, Y.-C. Lai*, and C. Grebogi, "Data-based Identification and Prediction of Nonlinear and Complex Dynamical Systems", Physics Reports 644, 1-76 (2016). This is a seminal work in bringing compressive sensing to uncover the equations of dynamics and/or the topology of complex networks with the availability of only a very sparse data set.

3. X.-Y. Yan, W.-X. Wang*, Z.-Y. Gao*, and Y.-C. Lai*, "Universal model of individual and population mobility on diverse spatial scales," Nature Communications 8, 1639, 1-9 (2017). This paper established a universal underlying mechanism capable of explaining a variety of human mobility behaviours, and has significant applications for understanding many dynamical processes associated with human mobility.

4. J.-J. Jiang, Z.-G. Huang, W. Lin, T. P. Seager, C. Grebogi, A. Hastings, and Y.-C. Lai*, "Predicting tipping points in mutualistic networks through dimension reduction," Proceedings of the National Academy of Sciences (USA) 115, E639-E647 (2018). This paper developed a reduced model for complex mutualistic networks, which can serve as a paradigm for understanding and predicting the tipping point dynamics in real world mutualistic networks for safeguarding pollinators, and the general principle can be extended to a broad range of disciplines to address the issues of resilience and sustainability.

5. H.-Y. Xu, G.-L. Wang, L. Huang, and Y.-C. Lai*, "Chaos in Dirac electron optics: emergence of a relativistic quantum chimera," Physical Review Letters 120, 124101 (2018). This paper uncovered a remarkable quantum scattering phenomenon in two-dimensional Dirac material systems where the manifestations of both classically integrable and chaotic dynamics emerge simultaneously and are electrically controllable with potential applications in spintronics.

6. L. Huang, H.-Y. Xu, C. Grebogi, and Y.-C. Lai*, "Relativistic quantum chaos," Physics Reports 753, 1-128 (2018). This work opened up a new field within Physics bringing together relativity, quantum mechanics and chaotic dynamics, with implication to the fundamentals of quantum mechanics and applications to 2-D Dirac materials such as graphene.

7. A. Hastings*, K. C. Abbott, K. Cuddington, T. Francis, G. Gellner, Y.-C. Lai, A. Morozov, S. Petrivskii, K. Scranton, and M. L. Zeeman, "Transient phenomena in ecology," Science 361, eaat6412, 1-9 (2018). This paper articulated a classification of transient dynamics in ecological systems based on ideas and concepts from dynamical systems theory, providing ways to understand the likelihood of transients for particular systems and to guide investigations to determine the timing of sudden switches in dynamics and other characteristics of transients, with implications to management and control of complex ecological systems.

8. J.-J. Jiang and Y.-C. Lai*, "Irrelevance of linear controllability to nonlinear dynamical networks" Nature Communications 10, 3961, 1-10 (2019). This paper uncovered the phenomenon that the nodal importance ranking for nonlinear and linear control exhibits opposite trends, suggesting strongly the irrelevance of linear controllability to real-world complex networked systems.

9. H.-Y. Xu and Y.-C. Lai*, "Anomalous chiral edge states in spin-1 Dirac quantum dots," Physical Review Research 2, 013062 (2020). This paper uncovered an unexpected family of in-gap chiral edge states in noninverted spin-1 Dirac quantum dots - a significant contribution to the fundamentals of the field of topological quantum states.

10. Z.-H. Lin, M. Feng, M. Tang, Z. Liu, C. Xu, P. M. Hui, and Y.-C. Lai, "Non-Markovian recovery makes complex networks more resilient against large-scale failures", Nature Communications 11, 2490 (2020). This paper reported the counter-intuitive phenomenon that memory in recovery can make a complex network more resilient against cascading failures and presented a comprehensive theoretical/computational framework to understand this phenomenon.

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