Nicholas D. Haynes

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We demonstrate reservoir computing with a physical system using a single autonomous Boolean logic element with time-delay feedback. The system generates a chaotic transient with a window of consistency lasting between 30 and 300 ns, which we show is sufficient for reservoir computing. We then characterize the dependence of computational performance on(More)
Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch(More)
We study networks of nonlocally coupled electronic oscillators that can be described approximately by a Kuramoto-like model. The experimental networks show long complex transients from random initial conditions on the route to network synchronization. The transients display complex behaviors, including resurgence of chimera states, which are network(More)
High-power lasers are making increasing demands on laser hosts especially in the area of thermal management. Traditional hosts, such as YAG, are unsuitable for many high-power applications and therefore, new hosts are being developed including rare-earth sesquioxides. We report new measurements of the refractive indices of these materials as functions of(More)
The refractive indices and thermo-optic coefficients for varying concentrations of Er3+ doped polycrystalline yttria were measured at a variety of wavelengths and temperatures. A Lorenz oscillator model was employed to model the room temperature indices and thermo-optic coefficients were calculated based on temperature dependent index measurements from 0.45(More)
Biochemical systems with switch-like interactions, such as gene regulatory networks, are well modeled by autonomous Boolean networks. Specifically, the topology and logic of gene interactions can be described by systems of continuous piecewise-linear differential equations, enabling analytical predictions of the dynamics of specific networks. However, most(More)
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