Fullbright

October 2012 – November 2013, Fulbright Scholar at Stanford University, CA, USA and Blanceflor Boncompagni-Ludovisi Scholar, CA, USA.

This Fellowship is supported by the Italy Fulbright Program funded by the Department of State and by the Italian government. The success rate of this fellowship is 8%. It is open to any disciplines and to any level of researchers.

Responsibilities:
Conduct a full time research project from the title “GRB relations and their theoretical interpretation”. Mentored 2 students in summer. Participation as a local organizer for the Open House at Stanford.

Key achievements:

  • Determination on whether the luminosities and time distributions are redshift independent (Dainotti et al. 2013a). Such an independence implies absence of this evolution, which, if exists, can be removed creating the new observables divided by their evolution functions. These new variables are the de-evolved ones. After fully applying a statistical method that takes into account selection bias and redshift evolution, they demonstrated that the relation is intrinsic at 12 sigma level and described how to recover it and how this can be used to constrain physical models of the plateau emission, whose origin is still unknown.
  • Evaluation of how changes of the observed slope, bobs, of the La-Ta correlation may affect the determination of the cosmological parameters (Dainotti et al. 2013a). To this end, Dainotti et al. (2013a) simulated a sample of 101 GRBs with a central value of bobs that differs from the intrinsic one by a 5σ factor. By comparing all their results with the values obtained by SNe Ia, they outlined an overestimation in the value of the matter density parameter, ΩM of the 13%, while the Hubble constant, H0, is still compatible in 1 σ. Instead, for a subsample of high luminous GRBs, ΩM is underestimated by the 13%, while H0 of 5%. Thus, they concluded that any approach involving cosmology should take into consideration only intrinsic correlations, namely corrected for cosmological evolutions and selection bias.