MMTF Discovery of Giant Ionization Cones in MR 2251-178: Implications for Quasar Radiative Feedback

We report the discovery of giant ionization cones in the 140-kpc nebula around quasar MR 2251-178 based on deep [O III] 5007/H-beta and [N II] 6583/H-alpha flux ratio maps obtained with the Maryland-Magellan Tunable Filter (MMTF) on the Baade-Magellan 6.5m telescope. These cones are aligned with the weak double-lobed radio source observed on smaller scale <30 kpc). They have an opening angle ~120deg +/- 10deg and subtend ~65-90% of 4pi steradians, where the large uncertainty takes into account possible projection effects. The material in the outer ionization cones is matter-bounded, indicating that all ionizing photons emitted through the cones escape from the system. The quasar ionizing flux is ~2-3 times fainter outside of these cones, despite the largely symmetric geometry of the nebula in [O III]. Overall, adding up the contributions from both inside and outside the cones, we find that ~65-95% of the quasar ionizing radiation makes its way out of the system. These results emphasize the need for line ratio maps to quantify the escape fraction of ionizing radiation from quasars and the importance of quasar radiative feedback on the intergalactic medium.Comment: 9 pages, 4 figures, 1 table. Accepted for publication in ApJ Letter

Spectral classification of emission-line galaxies

A revised method of classification of narrow line active galaxies and H II region-like galaxies is proposed. It involves the line ratios (O III) lambda 5007/H beta, (N II) lambda 6583/H alpha, (S II) (lambda lambda 6716 = 6731)/H alpha, and (O I) lambda 6300/H alpha. These line ratios take full advantage of the physical distinction between the two types of objects and minimize the effects of reddening correction and errors in the flux calibration. Large sets of internally consistent data are used including new previously unpublished measurements. Prediction of recent photoionization models by power law spectra and by hot stars are compared with the observations. The classification is based on the observational data interpreted on the basis of these models