Magnetized strangelets at finite temperature

The main properties of strangelets, namely their energy per baryon, radius and electric charge, are studied in the unpaired magnetized strange quark matter (MSQM) and paired magnetized colour flavour locked (MCFL) phases. Temperature effects are taken into account in order to study their stability compared to the Fe-56 isotope and nonmagnetized strangelets within the framework of the MIT bag model. We conclude that the presence of a magnetic field tends to stabilize the strangelets more, even when temperature is considered. It is also shown that MCFL strangelets are more stable than ordinary MSQM strangelets for typical gap values of the order of O(100) MeV. A distinctive feature in the detection of strangelets either in cosmic rays or in heavy-ion collider experiments could be their electric charge. We find that the electric charge is modified in the presence of the magnetic field, leading to higher (lower) charge values for MSQM (MCFL) strangelets, when compared to the nonmagnetized case.

New physics contributions to A(FB)(t(t)over-bar) at the Tevatron

The Tevatron has measured a discrepancy relative to the standard model prediction in the forward-backward asymmetry in top quark pair production. This asymmetry grows with the rapidity difference of the two top quarks. It also increases with the invariant mass of the t (t) over bar pair, reaching, for high invariant masses, 3.4 standard deviations above the next-to-leading order prediction for the charge asymmetry of QCD. However, perfect agreement between experiment and the standard model was found in both total and differential cross section of top quark pair production. As this result could be a sign of new physics we have parametrized this new physics in terms of a complete set of dimension six operators involving the top quark. We have then used a Markov chain Monte Carlo approach in order to find the best set of parameters that fits the data, using all available data regarding top quark pair production at the Tevatron. We have found that just a very small number of operators are able to fit the data better than the standard model.