Browsing by Subject "dependence"
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Item Dependence of cross sections for multi-electron loss by 6 mev/amu xe18+ ions on target atomic number(Texas A&M University, 2004-09-30) Peng, YongIt has been proposed to use heavy ion beams with energies around 10 MeV/amu, masses around 200, and average charges of 1+ as a driver for inertial fusion reactor. Current designs require the beams to travel through a region where the background gas pressure is several milli-torr. Thus, it is important to assess the rate at which the charge state of an incident beam evolves while passing through the background gas. The first objective of this project is to study the dependence of cross sections for multi-electron loss on target atomic number by using 6 MeV/amu Xe18+ ions and to compare the results with the n-body Classical Trajectory Monte Carlo calculations. A secondary objective of this project is to determine the extent to which the cross sections for molecular targets can be represented as sum of the cross sections for their atomic constituents. Cross sections for loss of one through eight electrons from 6 MeV/amu Xe18+ in single collisions have been measured with noble gas targets. The target Z-dependence of the total loss cross section was found to be well represented by two straight line segments. The cross section for He and Ne define one straight line segment and those for Ar, Kr and Xe define the other, where exhibits a smaller slope. The predictions of n-CTMC calculations are in good agreement with the measured total electron loss cross sections. A semiempirical fitting procedure based on the independent electron approximation provided a reasonably good representation of the individual cross sections for all of the noble gas targets. Additional measurements performed with a variety of molecular targets provided a rigorous test of cross section additivity and showed that the additivity rule works well for electron loss from heavy ions in the present energy and charge regime. A semiempirical calculation based the IEA shows that the average most probable impact parameter for electron loss is much smaller than the target molecular bond length. This result is believed to account for the finding of the insensitivity of the electron loss cross section to molecular structure.Item Essays on time series and causality analysis in financial markets(2009-05-15) Zohrabyan, TatevikFinancial market and its various components are currently in turmoil. Many large corporations are devising new ways to overcome the current market instability. Consequently, any study fostering the understanding of financial markets and the dependencies of various market components would greatly benefit both the practitioners and academicians. To understand different parts of the financial market, this dissertation employs time series methods to model causality and structure and degree of dependence. The relationship of housing market prices for nine U.S. census divisions is studied in the first essay. The results show that housing market is very interrelated. The New England and West North Central census divisions strongly lead house prices of the rest of the country. Further evidence suggests that house prices of most census divisions are mainly influenced by house price changes of other regions. The interdependence of oil prices and stock market indices across countries is examined in the second essay. The general dependence structure and degree is estimated using copula functions. The findings show weak dependence between stock market indices and oil prices for most countries except for the large oil producing nations which show high dependence. The dependence structure for most oil consuming (producing) countries is asymmetric implying that stock market index and oil price returns tend to move together more during the market downturn (upturn) than a market boom (downturn). In the third essay, the relationship among stock returns of ten U.S. sectors is studied. Copula models are used to explore the non-linear, general association among the series. The evidence shows that sectors are strongly related to each other. Energy sector is relatively weakly connected with the other sectors. The strongest dependence is between the Industrials and Consumer Discretionary sectors. The high dependence suggests small (if any) gains from industry diversification in U.S. In conclusion, the correct formulation of relationships among variables of interest is crucial. This is one of the fundamental issues in portfolio analysis. Hence, a thorough examination of time series models that are used to understand interactions of financial markets can be helpful for devising more accurate investment strategies.