Least-squares deconvolution based analysis of stellar spectra

In recent years, astronomical photometry has been revolutionised by space missions such as MOST, CoRoT and Kepler. However, despite this progress, high-quality spectroscopy is still required as well. Unfortunately, high-resolution spectra can only be obtained using ground-based telescopes, and since many interesting targets are rather faint, the spectra often have a relatively low S/N. Consequently, we have developed an algorithm based on the least-squares deconvolution profile, which allows to reconstruct an observed spectrum, but with a higher S/N. We have successfully tested the method using both synthetic and observed data, and in combination with several common spectroscopic applications, such as e.g. the determination of atmospheric parameter values, and frequency analysis and mode identification of stellar pulsations.Comment: Proceedingspaper, 8 pages, 4 figures, appears in "Setting a New Standard in the Analysis of Binary Stars", Eds K. Pavlovski, A. Tkachenko, and G. Torres, EAS Publications Serie

Pade-Improved Estimate of Perturbative Contributions to Inclusive Semileptonic b→ub\to u Decays

Pade-approximant methods are used to estimate the three-loop perturbative contributions to the inclusive semileptonic $b \to u$ decay rate. These improved estimates of the decay rate reduce the theoretical uncertainty in the extraction of the CKM matrix element $|V_{ub}|$ from the measured inclusive semileptonic branching ratio.Comment: 3 pages, latex, write-up of talk presented at DPF 200

Schwinger-Dyson equations in large-N quantum field theories and nonlinear random processes

We propose a stochastic method for solving Schwinger-Dyson equations in large-N quantum field theories. Expectation values of single-trace operators are sampled by stationary probability distributions of the so-called nonlinear random processes. The set of all histories of such processes corresponds to the set of all planar diagrams in the perturbative expansions of the expectation values of singlet operators. We illustrate the method on the examples of the matrix-valued scalar field theory and the Weingarten model of random planar surfaces on the lattice. For theories with compact field variables, such as sigma-models or non-Abelian lattice gauge theories, the method does not converge in the physically most interesting weak-coupling limit. In this case one can absorb the divergences into a self-consistent redefinition of expansion parameters. Stochastic solution of the self-consistency conditions can be implemented as a "memory" of the random process, so that some parameters of the process are estimated from its previous history. We illustrate this idea on the example of two-dimensional O(N) sigma-model. Extension to non-Abelian lattice gauge theories is discussed.Comment: 16 pages RevTeX, 14 figures; v2: Algorithm for the Weingarten model corrected; v3: published versio

Distribution and Dynamics in a Simple Tax Regime Transition

We examine transitions between excise tax and license fee regimes in the laboratory. The regimes have matched equilibrium Marshallian surplus, but license fees generate more tax revenue. The license fees are large “avoidable costs,” known to hamper competitive equilibrium convergence. With moderately experienced subjects, the prolonged transition to the license fee equilibrium has these features: (1) Prices below equilibrium levels, resulting in firm losses; (2) Marshallian surplus above equilibrium levels; and (3) transitional windfalls for the tax authority. With highly experienced subjects, license fees lead to the instability and lower seller profits and efficiency observed in past avoidable cost markets.Tax Regime Transitions, Avoidable Costs, Double Auctions, Experimental Methods.