The Diagnostic Potential of Fe Lines Applied to Protostellar Jets

Abstract

We investigate the diagnostic capabilities of iron lines for tracing the physical conditions of shock-excited gas in jets driven by pre-main sequence stars. We have analyzed the 3000-25000 \uc5, X-shooter spectra of two jets driven by the pre-main sequence stars ESO-H\u3b1 574 and Par-Lup 3-4. Both spectra are very rich in [Fe II] lines over the whole spectral range; in addition, lines from [Fe III] are detected in the ESO-H\u3b1 574 spectrum. Non-local thermal equilibrium codes solving the equations of the statistical equilibrium along with codes for the ionization equilibrium are used to derive the gas excitation conditions of electron temperature and density and fractional ionization. An estimate of the iron gas-phase abundance is provided by comparing the iron lines emissivity with that of neutral oxygen at 6300 \uc5. The [Fe II] line analysis indicates that the jet driven by ESO-H\u3b1 574 is, on average, colder (T e 3c 9000 K), less dense (n e 3c 2 7 104 cm-3), and more ionized (x e 3c 0.7) than the Par-Lup 3-4 jet (T e 3c 13,000 K, n e 3c 6 7 104 cm-3, x e < 0.4), even if the existence of a higher density component (n e 3c 2 7 105 cm-3) is probed by the [Fe III] and [Fe II] ultra-violet lines. The physical conditions derived from the iron lines are compared with shock models suggesting that the shock at work in ESO-H\u3b1 574 is faster and likely more energetic than the Par-Lup 3-4 shock. This latter feature is confirmed by the high percentage of gas-phase iron measured in ESO-H\u3b1 574 (50%-60% of its solar abundance in comparison with less than 30% in Par-Lup 3-4), which testifies that the ESO-H\u3b1 574 shock is powerful enough to partially destroy the dust present inside the jet. This work demonstrates that a multiline Fe analysis can be effectively used to probe the excitation and ionization conditions of the gas in a jet without any assumption on ionic abundances. The main limitation on the diagnostics resides in the large uncertainties of the atomic data, which, however, can be overcome through a statistical approach involving many line