Dispersion-induced dynamics of coupled modes in a semiconductor laser with saturable absorption

We present an experimental and theoretical study of modal nonlinear dynamics in a specially designed dual-mode semiconductor Fabry-Perot laser with a saturable absorber. At zero bias applied to the absorber section, we have found that with increasing device current, single mode self-pulsations evolve into a complex dynamical state where the total intensity experiences regular bursts of pulsations on a constant background. Spectrally resolved measurements reveal that in this state the individual modes of the device can follow highly symmetric but oppositely directed spiralling orbits. Using a generalization of the rate equation description of a semiconductor laser with saturable absorption to the multimode case, we show that these orbits appear as a consequence of the interplay between the material dispersion in the gain and absorber sections of the laser. Our results provide insights into the factors that determine the stability of multimode states in these systems, and they can inform the development of semiconductor mode-locked lasers with tailored spectra.Comment: 10 pages, 10 figure

Collisions with other Universes: the Optimal Analysis of the WMAP data

An appealing theory is that our current patch of universe was born as a nucleation bubble from a phase of false vacuum eternal inflation. We search for evidence for this theory by looking for the signal imprinted on the CMB that is generated when another bubble "universe" collides with our own. We create an efficient and optimal estimator for the signal in the WMAP 7-year data. We find no detectable signal, and constrain the amplitude, a, of the initial curvature perturbation that would be generated by a collision: -4.66 \times 10^{-8} < a (\sin{\thetabubble})^{4/3} < 4.73 \times 10^{-8} [Mpc^{-1}] at 95% confidence where \thetabubble is the angular radius of the bubble signal.Comment: 5 pages, 3 figure

Optimal analysis of azimuthal features in the CMB

We present algorithms for searching for azimuthally symmetric features in CMB data. Our algorithms are fully optimal for masked all-sky data with inhomogeneous noise, computationally fast, simple to implement, and make no approximations. We show how to implement the optimal analysis in both Bayesian and frequentist cases. In the Bayesian case, our algorithm for evaluating the posterior likelihood is so fast that we can do a brute-force search over parameter space, rather than using a Monte Carlo Markov chain. Our motivating example is searching for bubble collisions, a pre-inflationary signal which can be generated if multiple tunneling events occur in an eternally inflating spacetime, but our algorithms are general and should be useful in other contexts.Comment: 30 pages, 5 figure

Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space

Existing work in multi-agent collision prediction and avoidance typically assumes discrete-time trajectories with Gaussian uncertainty or that are completely deterministic. We propose an approach that allows detection of collisions even between continuous, stochastic trajectories with the only restriction that means and variances can be computed. To this end, we employ probabilistic bounds to derive criterion functions whose negative sign provably is indicative of probable collisions. For criterion functions that are Lipschitz, an algorithm is provided to rapidly find negative values or prove their absence. We propose an iterative policy-search approach that avoids prior discretisations and yields collision-free trajectories with adjustably high certainty. We test our method with both fixed-priority and auction-based protocols for coordinating the iterative planning process. Results are provided in collision-avoidance simulations of feedback controlled plants.Comment: This preprint is an extended version of a conference paper that is to appear in \textit{Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014)

The innovative capacity of voluntary organisations and the provision of public services: A longitudinal approach

The prior history of voluntary and community organisations (VCOs) as pioneers of public services during the late nineteenth and early twentieth century has lead to reification of the innovativeness of these organisations. Is this reification justified – are VCOs inherently innovative, or is innovation contingent on other factors? This paper reports on a longitudinal study of this capacity conducted over 1994 – 2006. This study finds that the innovative capacity of VCOs is in fact not an inherent capacity but rather is contingent upon the public policy framework that privileges innovation above other activity of VCOs. The implications of this for theory, policy and practice are considered

Practical Bayesian Optimization for Variable Cost Objectives

We propose a novel Bayesian Optimization approach for black-box functions with an environmental variable whose value determines the tradeoff between evaluation cost and the fidelity of the evaluations. Further, we use a novel approach to sampling support points, allowing faster construction of the acquisition function. This allows us to achieve optimization with lower overheads than previous approaches and is implemented for a more general class of problem. We show this approach to be effective on synthetic and real world benchmark problems.Comment: 8 pages, 7 figure