A new jet algorithm based on the k-means clustering for the reconstruction of heavy states from jets

A jet algorithm based on the k-means clustering procedure is proposed which can be used for the invariant-mass reconstruction of heavy states decaying to hadronic jets. The proposed algorithm was tested by reconstructing E+ E- to ttbar to 6 jets and E+ E- to W+W- to 4 jets processes at \sqrt{s}=500 GeV using a Monte Carlo simulation. It was shown that the algorithm has a reconstruction efficiency similar to traditional jet-finding algorithms, and leads to 25% and 40% reduction of reconstruction width for top quarks and W bosons, respectively, compared to the kT (Durham) algorithm. In addition, it is expected that the peak positions measured with the new algorithm have smaller systematical uncertainty.Comment: 11 pages, 3 eps figures (Eur. Phys. J. C, in press

Jets in Deep Inelastic Scattering and High Energy Photoproduction at HERA

Recent results on jet production in neutral current deep inelastic scattering and high energy photoproduction at the HERA electron-proton-collider are briefly reviewed. The results are compared to QCD expectations in NLO and $\alpha_s$ determinations using these data are summarized.Comment: 12 pages, 10 figures, talk given at the 9th Adriatic Meeting "Particle Physics and the Universe" in Dubrovnik/Croatia, 4.-24.9.200

HepSim: a repository with predictions for high-energy physics experiments

A file repository for calculations of cross sections and kinematic distributions using Monte Carlo generators for high-energy collisions is discussed. The repository is used to facilitate effective preservation and archiving of data from theoretical calculations, as well as for comparisons with experimental data. The HepSim data library is publicly accessible and includes a number of Monte Carlo event samples with Standard Model predictions for current and future experiments. The HepSim project includes a software package to automate the process of downloading and viewing online Monte Carlo event samples. A data streaming over a network for end-user analysis is discussed.Comment: 12 pages, 2 figure