Probing the solar wind acceleration region using spectroscopic techniques

Measurements of the intensities and profiles of UV and EUV spectral lines can provide a powerful tool for probing the physical conditions in the solar corona out to 8 R and beyond. We discuss here how measurements of spectral line radiation in conjunction with measurements of the white light K-corona can provide information on electron, proton and ion temperatures and velocity distribution functions; densities; chemical abundances and mass flow velocities. Because of the fundamental importance of such information, we provide a comprehensive review of the formation of coronal resonance line radiation, with particular emphasis on the H i L line, and discuss observational considerations such as requirements for rejection of stray light and effects of emission from the geocorona and interplanetary dust. Finally, we summarize some results of coronal H i L and white light observations acquired on sounding rocket flights.Paper presented at the IX-th Lindau Workshop The Source Region of the Solar Wind.     

Neural network learning of low-probability events

In the problem of stationary target identification (STI) via millimeter wave (MMW) seeker radars in heavy clutter environments, it is often necessary to use nonparametric identification procedures, as detailed parametric models of clutter and target returns are generally unavailable. Neural networks provide an attractive approach to perform nonparametric identification. However, when identifying low-probability events, the computational overhead associated with training a neural network can become excessive. This is because low-probability events must be adequately represented in the training sample. We present a modified backpropagation training algorithm based on a likelihood ratio weighting function (LRWF) to train the neural network using a much smaller training set than that required using the standard backpropagation algorithm This algorithm is closely related to the importance sampling technique used in digital communication systems to obtain probability of error estimates by using a much smaller number of simulation runs than what is required with standard Monte Carlo simulation. The modified backpropagation technique results in a significant reduction in computational overhead in training the network, resulting from a substantial reduction in the size of the training set required to achieve a given level of performance. We demonstrate the performance of the algorithm on simulated data for the STI problem in MMW radar     

The spacelab Lyman alpha and white light coronagraphs program

The Harvard-Smithsonian Center for Astrophysics and the High Altitude Observatory have defined a joint coronagraphs experiment for a future Spacelab mission. The instrumentation package would include an ultraviolet light coronagraph to measure the intensity and profiles of spectral lines formed between 1.2 and 8 solar radii from Sun center and a white light coronagraph to measure the intensity and polarization of visible light. The overall goals of the joint program are to use new coronal plasma diagnostic techniques to understand the physical processes and mechanisms operating in the solar corona, to understand the acceleration of high-speed and low-speed solar wind streams and to extrapolate this knowledge to other stars in order to help understand the physics of stellar coronae and stellar mass loss.Proceedings of the Conference Solar Physics from Space, held at the Swiss Federal Institute of Technology Zurich (ETHZ), 11–14 November 1980.