Antikaon condensation and the metastability of protoneutron stars

We investigate the condensation of $\bar K^0$ meson along with $K^-$ condensation in the neutrino trapped matter with and without hyperons. Calculations are performed in the relativistic mean field models in which both the baryon-baryon and (anti)kaon-baryon interactions are mediated by meson exchange. In the neutrino trapped matter relevant to protoneutron stars, the critical density of $K^-$ condensation is shifted considerably to higher density whereas that of $\bar K^0$ condensation is shifted slightly to higher density with respect to that of the neutrino free case. The onset of $K^-$ condensation always occurs earlier than that of $\bar K^0$ condensation. A significant region of maximum mass protoneutron stars is found to contain $\bar K^0$ condensate for larger values of the antikaon potential. With the appearance of $\bar K^0$ condensation, there is a region of symmetric nuclear matter in the inner core of a protoneutron star. It is found that the maximum mass of a protoneutron star containing $K^-$ and $\bar K^0$ condensate is greater than that of the corresponding neutron star. We revisit the implication of this scenario in the context of the metastability of protoneutron stars and their evolution to low mass black holes.Comment: 26 pages; Revtex; 8 figures include

A MANUSH or HUMANS Characterisation of the Human Development Index

Proposing a set of axioms MANUSH (Monotonicity, Anonymity, Normalisation, Uniformity, Shortfall sensitivity, Hiatus sensitivity to level), this paper evaluates three aggregation methods of computing Human Development Index (HDI). The old measure of HDI, which is a linear average of the three dimensions, satisfies monotonicity, anonymity, and normalisation (or MAN) axioms. The current geometric mean approach additionally satisfies the axiom of uniformity, which penalises unbalanced development across dimensions. We propose ℋα measure, which for α ≥ 2 also satisfies axioms of shortfall sensitivity (emphases on the worse-off to better-off dimensions should be at least in proportion to their shortfalls) and hiatus sensitivity to level (higher overall attainment must simultaneously lead to a reduction in gap across dimensions). Special cases of ℋα are the linear average (α = 1), the displaced ideal (α = 2), and the leximin ordering (α → ∞) methods. For its axiomatic advantages, we propose to make use of the displaced ideal (α = 2) method in the computation of HDI replacing the current geometric mean