Molecular gas in the galaxy M83 : Its distribution, kinematics, and relation to star formation

The barred spiral galaxy M83 (NGC5236) has been observed in the 12CO J=1–0 and J=2–1 millimetre lines with the Swedish-ESO Submillimetre Telescope (SEST). The sizes of the CO maps are 100×100, and they cover the entire optical disk. The CO emission is strongly peaked toward the nucleus. The molecular spiral arms are clearly resolved and can be traced for about 360º. The total molecular gas mass is comparable to the total Hi mass, but H2 dominates in the optical disk. Iso-velocity maps show the signature of an inclined, rotating disk, but also the effects of streaming motions along the spiral arms. The dynamical mass is determined and compared to the gas mass. The pattern speed is determined from the residual velocity pattern, and the locations of various resonances are discussed. The molecular gas velocity dispersion is determined, and a trend of decreasing dispersion with increasing galactocentric radius is found. A total gas (H2+Hi+He) mass surface density map is presented, and compared to the critical density for star formation of an isothermal gaseous disk. The star formation rate (SFR) in the disk is estimated using data from various star formation tracers. The different SFR estimates agree well when corrections for extinctions, based on the total gas mass map, are made. The radial SFR distribution shows features that can be associated with kinematic resonances. We also find an increased star formation efficiency in the spiral arms. Different Schmidt laws are fitted to the data. The star formation properties of the nuclear region, based on high angular resolution HST data, are also discussed.

Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).