Indirect modulation of a terahertz quantum cascade laser using gate tunable graphene

We bring together two areas of terahertz (THz) technology that have benefited from recent advancements in research, i.e., graphene, a material that has plasmonic resonances in the THz frequency, and quantum cascade lasers (QCLs), a compact electrically driven unipolar source of THz radiation. We demonstrate the use of single-layer large-area graphene to indirectly modulate a THz QCL operating at 2.0 THz. By tuning the Fermi level of the graphene via a capacitively coupled backgate voltage, the optical conductivity and, hence, the THz transmission can be varied. We show that, by changing the pulsing frequency of the backgate, the THz transmission can be altered. We also show that, by varying the pulsing frequency of the backgate from tens of Hz to a few kHz, the amplitude-modulated THz signal can be switched by 15% from a low state to a high state. © 2009-2012 IEEE.

An organizing center in a planar model of neuronal excitability

This paper studies the excitability properties of a generalized FitzHugh-Nagumo model. The model differs from the classical FitzHugh-Nagumo model in that it accounts for the effect of cooperative gating variables such as activation of calcium currents. Excitability is explored by unfolding a pitchfork bifurcation that is shown to organize five different types of excitability. In addition to the three classical types of neuronal excitability, two novel types are described and distinctly associated to the presence of cooperative variables. © 2012 Society for Industrial and Applied Mathematics.

Improving the performance of low-gain designs for bounded control of linear systems

An online scheduling of the parameter ensuring in addition to closed loop stability was presented. Attention was given to saturated linear low-gain control laws. Null controllability of the considered linear systems was assumed. The family of low gain control laws achieved semiglobal stabilization.

Efficient parametric uncertainty analysis within the hybrid Finite Element/Statistical Energy Analysis method

This paper is concerned with the development of efficient algorithms for propagating parametric uncertainty within the context of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) approach to the analysis of complex vibro-acoustic systems. This approach models the system as a combination of SEA subsystems and FE components; it is assumed that the FE components have fully deterministic properties, while the SEA subsystems have a high degree of randomness. The method has been recently generalised by allowing the FE components to possess parametric uncertainty, leading to two ensembles of uncertainty: a non-parametric one (SEA subsystems) and a parametric one (FE components). The SEA subsystems ensemble is dealt with analytically, while the effect of the additional FE components ensemble can be dealt with by Monte Carlo Simulations. However, this approach can be computationally intensive when applied to complex engineering systems having many uncertain parameters. Two different strategies are proposed: (i) the combination of the hybrid FE/SEA method with the First Order Reliability Method which allows the probability of the non-parametric ensemble average of a response variable exceeding a barrier to be calculated and (ii) the combination of the hybrid FE/SEA method with Laplace's method which allows the evaluation of the probability of a response variable exceeding a limit value. The proposed approaches are illustrated using two built-up plate systems with uncertain properties and the results are validated against direct integration, Monte Carlo simulations of the FE and of the hybrid FE/SEA models. © 2013 Elsevier Ltd.