
We study supersymmetric models without R parity and with universal soft supersymmetry breaking terms. We show that as a result of the renormalization group flow of the parameters, a misalignment between the directions in field space of the down-type Higgs vacuum expectation value $v_d$ and of the $��$ term is always generated. This misalignment induces a mixing between the neutrinos and the neutralinos, resulting in one massive neutrino. By means of a simple approximate analytical expression, we study the dependence on the different parameters that contribute to the misalignment and to $m_��$. In large part of the parameter space this effect dominates over the standard one-loop contributions to $m_��$; we estimate 1 MeV $\lsim m_��\lsim 1 GeV$. Laboratory, cosmological and astrophysical constraints imply $m_��\lsim 100 eV$. To be phenomenologically viable, these models must be supplemented with some additional mechanism to ensure approximate alignment and to suppress $m_��$.
21 pages, LaTex. Few points clarified, results unchanged. Final version to appear on Physical Review D
High Energy Physics - Phenomenology, High Energy Physics - Phenomenology (hep-ph), FOS: Physical sciences
High Energy Physics - Phenomenology, High Energy Physics - Phenomenology (hep-ph), FOS: Physical sciences
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 100 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
