Confinement of nonneutral plasmas on magnetic surfaces

The confinement of a nonneutral plasma in a magnetic-surface, or stellarator, configuration is explored. The fluid equilibrium equations are derived and are found to be fundamentally different from previous results. Diocotron modes are predicted to be stable. The collisional confinement time can be very long. Possible applications include positron trapping and confinement of positron-electron plasmas. The basic physics can be addressed experimentally in the simple tabletop stellarator planned for construction at Columbia University.     

Design criteria of a chemical reactor based on a chaotic flow

We consider the design criteria of a chemical mixing device based on a chaotic flow, with an emphasis on the steady-state devices. The merit of a reactor, defined as the Q-factor, is related to the physical dimension of the device and the molecular diffusivity of the reactants through the local Lyapunov exponents of the flow. The local Lyapunov exponent can be calculated for any given flow field and it can also be measured in experimental situations. Easy-to-compute formulae are provided to estimate the Q-factor given either the exact spatial dependence of the local Lyapunov exponent or its probability distribution function. The requirements for optimization are made precise in the context of local Lyapunov exponents. (c) 1999 American Institute of Physics.     

Determination of the number of atoms trapped in an optical cavity

The number of atoms trapped within the mode of an optical cavity is determined in real time by monitoring the transmission of a weak probe beam. Continuous observation of atom number is accomplished in the strong coupling regime of cavity quantum electrodynamics and functions in concert with a cooling scheme for radial atomic motion. The probe transmission exhibits sudden steps from one plateau to the next in response to the time evolution of the intracavity atom number, from N>or=3 to N=2-->1-->0 atoms, with some trapping events lasting over 1 s.     

Reconstruction of chaotic signals using symbolic data

We discuss the reconstruction of dynamical systems from noisy time-series. In particular, we consider the use of the symbol statistics (coarse-grained signal data) as the target for reconstruction. The statistics of symbol sequences is relatively insensitive to moderate amounts of measurement noise (σ(noise)/σ(signal) ≈ 10–20%), while larger amounts produce a substantial bias. We show that it is possible to produce robust reconstructions even when σ(noise)/σ(signal) ≈ O(1). Our study shows that even at such high noise levels the procedure is convergent: i.e. the accuracy of parameter estimates is limited only by the amount of data and computer time available.