Photon-Photon and Electron-Photon Colliders with Energies Below a TeV

We investigate the potential for detecting and studying Higgs bosons in $\gamma\gamma$ and $e\gamma$ collisions at future linear colliders with energies below a TeV. Our study incorporates realistic $\gamma\gamma$ spectra based on available laser technology, and NLC and CLIC acceleration techniques. Results include detector simulations. We study the cases of: a) a SM-like Higgs boson based on a devoted low energy machine with $\sqrt{s_{ee}}\le 200$ GeV; b) the heavy MSSM Higgs bosons; and c) charged Higgs bosons in $e\gamma$ collisions.Comment: 29 pages, 13 figures, contributed to Snowmass 200

Exploring Complex Phases of the MSSM at Future Colliders

Once Supersymmetry is discovered, exploring the phases of supersymmetric parameters will be one of the most important tasks of future colliders. We analyze the possibilities of investigating the phases of the cMSSM via their effects on the Higgs sector through radiative corrections. Within two benchmark scenarios we compare the capabilities of the LHC, the ILC and a future gamma gamma collider.Comment: 6 pages, 10 figures. Talk given by S. Heinemeyer at the 2005 International Linear Collider Workshop, Stanford Ca (LCWS05

Edgeworth Expansions for Spectral Density Estimates and Studentized Sample Mean - (Now published in Economic Theory, 17 (2001), pp.497-539.

We establish valid Edgeworth expansions for the distribution of smoothed nonparametric spectral estimates, and of studentized versions of linear statistics such as the same mean, where the studentization employs such a nonparametric spectral estimate. Particular attention is paid to the spectral estimate at zero frequency and, correspondingly, the studentized sample mean, to reflect econometric interest in autocorrelation-consistent or long-run variance estimation. Our main focus is on stationary Gaussian series, though we discuss relaxation of the Gaussianity assumption. Only smoothness conditions on the spectral density that are local to the frequency of interest are imposed. We deduce empirical expansions from our Edgeworth expansions designed to improve on the normal approximation in practice, and also a feasible rule of bandwidth choice.Edgeworth expansions, nonparametric spectral estimates, stationary Gaussian series, studentized sample mean, bandwidth choice.