Optimization of laser-plasma injector via beam loading effects using ionization-induced injection

Simulations of ionization induced injection in a laser driven plasma wakefield show that high-quality electron injectors in the 50-200 MeV range can be achieved in a gas cell with a tailored density profile. Using the PIC code Warp with parameters close to existing experimental conditions, we show that the concentration of $\mathrm{N_2}$ in a hydrogen plasma with a tailored density profile is an efficient parameter to tune electron beam properties through the control of the interplay between beam loading effects and varying accelerating field in the density profile. For a given laser plasma configuration, with moderate normalized laser amplitude, $a_0=1.6$ and maximum electron plasma density, $n_{e0}=4\times 10^{18}\,\mathrm{cm^{-3}}$, the optimum concentration results in a robust configuration to generate electrons at 150~MeV with a rms energy spread of 4\% and a spectral charge density of 1.8~pC/MeV.Comment: 13 pages, 10 figure

Coupling efficiency for phase locking of a spin transfer oscillator to a microwave current

The phase locking behavior of spin transfer nano-oscillators (STNOs) to an external microwave signal is experimentally studied as a function of the STNO intrinsic parameters. We extract the coupling strength from our data using the derived phase dynamics of a forced STNO. The predicted trends on the coupling strength for phase locking as a function of intrinsic features of the oscillators i.e. power, linewidth, agility in current, are central to optimize the emitted power in arrays of mutually coupled STNOs

Regulatory Dynamics on Random Networks: Asymptotic Periodicity and Modularity

We study the dynamics of discrete-time regulatory networks on random digraphs. For this we define ensembles of deterministic orbits of random regulatory networks, and introduce some statistical indicators related to the long-term dynamics of the system. We prove that, in a random regulatory network, initial conditions converge almost surely to a periodic attractor. We study the subnetworks, which we call modules, where the periodic asymptotic oscillations are concentrated. We proof that those modules are dynamically equivalent to independent regulatory networks.Comment: 23 pages, 3 figure