Clues to the origin of Fermi Bubbles from OVIII/OVII line ratio

We constrain the origin of Fermi Bubbles using 2D hydrodynamical simulations of both star formation driven and black hole accretion driven wind models. We compare our results with recent observations of OVIII to OVII line ratio within and near Fermi Bubbles. Our results suggest that independent of the driving mechanisms, a low luminosity ($\mathcal{L} \sim 0.7-1\times 10^{41}$ erg s$^{-1}$) energy injection best reproduces the observed line ratio for which the shock temperature is $\approx 3\times 10^6$ K. Assuming the Galactic halo temperature to be $2\times 10^6$K, we estimate the shock velocity to be $\sim 300$ km s$^{-1}$ for a weak shock. The corresponding estimated age of the Fermi bubbles is $\sim 15-25$ Myr. Such an event can be produced either by a star formation rate of $\sim 0.5$ M$_\odot$ yr$^{-1}$ at the Galactic centre or a very low luminosity jet/accretion wind arising from the central black hole. Our analysis rules out any activity that generates an average mechanical luminosity $\gtrsim 10^{41}$ \ergps as a possible origin of the Fermi Bubbles.Comment: 14 pages, 9 figures, accepted version (MNRAS); includes updates on the electron-proton equilibrium time scale and its implications for high energy jet

Quark-lepton complementarity model based predictions for θ23PMNS\theta_{23}^{PMNS} with neutrino mass hierarchy

After the successful investigation and confirmation of non zero $\theta_{13}^{PMNS}$ by various experiments, we are standing at a square where we still encounter a number of issues, which are to be settled. In this paper, we have extended our recent work towards a precise prediction of the $\theta_{23}^{PMNS}$ mixing angle, taking into account the neutrino mass hierarchy. We parameterize the non-trivial correlation between quark (CKM) and lepton (PMNS) mixing matrices in quark-lepton complementarity (QLC) model as $V_{c}= U_{CKM}. \psi. U_{PMNS}$, where $\psi$ is a diagonal phase matrix. Monte Carlo simulations are used to estimate the texture of $V_{c}$ and compare the results with the standard Tri-Bi-Maximal (TBM) and Bi-Maximal(BM) structures of neutrino mixing matrix. We have predicted the value of $\theta_{23}^{PMNS}$ for normal and inverted neutrino mass hierarchies. The value of $\theta_{23}^{PMNS}$ obtained for two cases are about $1.3\sigma$ away from each other, implying the better precision can give us a strong hint for the type of neutrino mass hierarchy.Comment: 3 pages, 3 figure

Bound State Solutions of Klein-Gordon Equation with the Kratzer Potential

The relativistic problem of spinless particle subject to a Kratzer potential is analyzed. Bound state solutions for the s-wave are found by separating the Klein-Gordon equation in two parts, unlike the similar works in the literature, which provides one to see explicitly the relativistic contributions, if any, to the solution in the non-relativistic limit.Comment: 6 page

On-site residence time in a driven diffusive system: violation and recovery of mean-field

We investigate simple one-dimensional driven diffusive systems with open boundaries. We are interested in the average on-site residence time defined as the time a particle spends on a given site before moving on to the next site. Using mean-field theory, we obtain an analytical expression for the on-site residence times. By comparing the analytic predictions with numerics, we demonstrate that the mean-field significantly underestimates the residence time due to the neglect of time correlations in the local density of particles. The temporal correlations are particularly long-lived near the average shock position, where the density changes abruptly from low to high. By using Domain wall theory (DWT), we obtain highly accurate estimates of the residence time for different boundary conditions. We apply our analytical approach to residence times in a totally asymmetric exclusion process (TASEP), TASEP coupled to Langmuir kinetics (TASEP + LK), and TASEP coupled to mutually interactive LK (TASEP + MILK). The high accuracy of our predictions is verified by comparing these with detailed Monte Carlo simulations