David Rosin, Visiting Scholar
Office Location: 183 Physics
Office Phone: (919) 660-2500
Email Address: firstname.lastname@example.org
Nonlinear dynamics and complex systems
M.Sc., Technische Universität Berlin, 2011
Ph.D. Candidate, Duke University and TU Berlin
- Dynamics and control of networks
- Artificial neural networks
- Neuromorphic computing
- Physical generation of random numbers
- Excitability in optic and electronic systems
We study networks of chaotic, oscillatory and excitable components and apply them as physical random number generators and reservoir computers. The latter is an alternative computing approach that uses the complex dynamics of networks to map information into a higher dimensional space. We realize the networks experimentally with circuits of autonomous logic gates on field-programmable gate arrays (FPGAs). This allows us to build large networks like ensembles of hundreds of oscillators that are coupled to achieve exotic dynamics known as chimera states.
Besides electronic realizations, we also study dynamical systems based on opto-electronic components. Recently, we could show that an opto-electronic oscillator displays, in addition to its well-studied chaotic and oscillatory regime, excitability.
- D. P. Rosin, D. Rontani, D. J. Gauthier, and E. Schöll, Control of Synchronization Patterns in Neural-like Boolean Networks,
Phys. Rev. Lett., vol. 110 no. 104102
(2013) [pdf] .
- D. P. Rosin, D. Rontani, and D. J. Gauthier, Ultra-Fast Physical Generation of Random Numbers Using Hybrid Boolean Networks, vol. 87
pp. 040902(R) [pdf] .
- D. P. Rosin, D. Rontani, D. J. Gauthier and E. Schöll, Excitability in autonomous Boolean networks,
Europhys. Lett., vol. 100
pp. 30003 [pdf] .
- D. P. Rosin, K. E. Callan, D. J. Gauthier and E. Schöll, Pulse-train solutions and excitability in an optoelectronic oscillator,
Europhys. Lett., vol. 96
pp. 34001 [pdf] .