Langmuir Turbulence and Solar Radio Bursts

Langmuir waves and turbulence resulting from an electron beam-plasma instability play a fundamental role in the generation of solar radio bursts. We report recent theoretical advances in nonlinear dynamics of Langmuir waves. First, starting from the generalized Zakharov equations, we study the parametric excitation of solar radio bursts at the fundamental plasma frequency driven by a pair of oppositely propagating Langmuir waves with different wave amplitudes. Next, we briefly discuss the emergence of chaos in the Zakharov equations. We point out that chaos can lead to turbulence in the source regions of solar radio emissions. This revised version was published online in August 2006 with corrections to the Cover Date.     

Blind adaptive decision fusion for distributed detection

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We then use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k/sup 1/2/) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.     

Steady magnetospheric convection: A review of recent results

Theoretical pressure balance arguments have implied that steady convection is hardly possible in the terrestrial magnetotail and that steady energy input necessarily generates a cyclic loading-unloading sequence, i.e., repetitive substorms. However, observations have revealed that enhanced solar wind energy input to the magnetospheric system may either lead to substorm activity or enhanced but steady convection. This topic is reviewed with emphasis on several recent case studies of the Steady Magnetospheric Convection (SMC) events. In these cases extensive data sets from both satellite and ground-based instruments from various magnetospheric and ionospheric regions were available.Accurate distinction of the spatial and temporal scales of the magnetospheric processes is vital for correct interpretation of the observations during SMC periods. We show that on the large scale, the magnetospheric configuration and plasma convection are stable during SMC events, but that both reveal considerable differences from their quiet-time assemblies. On a shorter time scale, there are numerous transient activations which are similar to those found during substorms, but which presumably originate from a more distant tail reconnection process, and map to the poleward boundary of the auroral oval. The available observations and the unresolved questions are summarized here.The tail magnetic field during SMC events resembles both substorm growth and recovery phases in the neartail and midtail, respectively, but this configuration may remain stable for up to ten hours. Based on observations and model results we discuss how the magnetospheric system avoids pressure balance problems when the plasma convects earthward.Finally, the importance of further coordinated studies of SMC events is emphasized. Such studies may shed more light on the substorm dynamics and help to verify quantitatively the theoretical models of the convecting magnetosphere.     

Possible episodic gamma-ray sources

A model for production of episodic -ray event at interaction of a moving gas target with, a beam of relativistic particles is proposed. The typical duration of -ray emission is limited by the flight time of the target across the beam as well as by the time of destruction and/or expulsion of the target by luminous beam. The time-dependent radiation spectra of the expanding and moving gas cloud irradiated by the beam are calculated for the galactic binary systems Her X-1 and AE Aquarii which are reported as episodic -ray emitters at very high energies. Some predictions and observational tests for the model are discussed.On leave from Yerevan Physics Institute, Armenia     

A three-dimensional plasma and energetic particle investigation for the wind spacecraft

This instrument is designed to make measurements of the full three-dimensional distribution of suprathermal electrons and ions from solar wind plasma to low energy cosmic rays, with high sensitivity, wide dynamic range, good energy and angular resolution, and high time resolution. The primary scientific goals are to explore the suprathermal particle population between the solar wind and low energy cosmic rays, to study particle accleration and transport and wave-particle interactions, and to monitor particle input to and output from the Earth's magnetosphere.Three arrays, each consisting of a pair of double-ended semi-conductor telescopes each with two or three closely sandwiched passivated ion implanted silicon detectors, measure electrons and ions above 20 keV. One side of each telescope is covered with a thin foil which absorbs ions below 400 keV, while on the other side the incoming <400 keV electrons are swept away by a magnet so electrons and ions are cleanly separated. Higher energy electrons (up to 1 MeV) and ions (up to 11 MeV) are identified by the two double-ended telescopes which have a third detector. The telescopes provide energy resolution of E/E0.3 and angular resolution of 22.5°×36°, and full 4 steradian coverage in one spin (3 s).Top-hat symmetrical spherical section electrostatic analyzers with microchannel plate detectors are used to measure ions and electrons from 3 eV to 30 keV. All these analyzers have either 180° or 360° fields of view in a plane, E/E0.2, and angular resolution varying from 5.6° (near the ecliptic) to 22.5°. Full 4 steradian coverage can be obtained in one-half or one spin. A large and a small geometric factor analyzer measure ions over the wide flux range from quiet-time suprathermal levels to intense solar wind fluxes. Similarly two analyzers are used to cover the wide range of electron fluxes. Moments of the electron and ion distributions are computed on board.In addition, a Fast Particle Correlator combines electron data from the high sensitivity electron analyzer with plasma wave data from the WAVE experiment (Bougeretet al., in this volume) to study wave-particle interactions on fast time scales. The large geometric factor electron analyzer has electrostatic deflectors to steer the field of view and follow the magnetic field to enhance the correlation measurements.     

Some active galactic nuclei as cosmological probes

A method of using AGNs as cosmological probes and some recent results are discussed. The method is based on fitting the Hedgehog model to observations of spectra, structure and polarization of AGN radio emission and time variations of the observed quantities. If red shifts of selected AGNs are known, extragalactic distances, the Hubble constant and the deceleration parameter of the Universe can be measured using only radio observations. Recent results may give new strong arguments for the basic model to be in agreement with observations of variable spectra and structure of many AGNs, and may allow preliminary selection of AGNs for further use.     

Multistage integration model for human egomotion perception

Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.     

Optimal motion planning for dual-spacecraft interferometry

We address the question of design and optimal control of a class of dual-spacecraft interferometric imaging formations. The first main contribution is that we combine two ideas introduced separately in the literature and propose a maneuver that offers improved imaging performance. We then formulate an optimal control problem to minimize fuel consumption and maximize image quality by minimizing the relative speed, which is proportional to the signal-to-noise ratio (SNR) of the reconstructed image. We show that the necessary conditions are also sufficient and that the resulting optimal control is unique. Finally, we apply a continuation method to solve for the unique optimal trajectory.     

The Pre-CME Sun

The coronal mass ejection (CME) phenomenon occurs in closed magnetic field regions on the Sun such as active regions, filament regions, transequatorial interconnection regions, and complexes involving a combination of these. This chapter describes the current knowledge on these closed field structures and how they lead to CMEs. After describing the specific magnetic structures observed in the CME source region, we compare the substructures of CMEs to what is observed before eruption. Evolution of the closed magnetic structures in response to various photospheric motions over different time scales (convection, differential rotation, meridional circulation) somehow leads to the eruption. We describe this pre-eruption evolution and attempt to link them to the observed features of CMEs. Small-scale energetic signatures in the form of electron acceleration (signified by nonthermal radio bursts at metric wavelengths) and plasma heating (observed as compact soft X-ray brightening) may be indicative of impending CMEs. We survey these pre-eruptive energy releases using observations taken before and during the eruption of several CMEs. Finally, we discuss how the observations can be converted into useful inputs to numerical models that can describe the CME initiation.     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications