Thomas Spriggs
The study of Planetary Nebulae (PNe) in other galaxies offers a view into the late stages of stellar evolution in galactic environments that are considerably different compared to that of the Milky Way. For instance, the specific number of PNe is thought to depend on the stellar metallicity of their parent population at a given stellar age. Massive early-type galaxies provide a benchmark for studying PNe in a super-Solar metallicity regime for old stellar population, and in this respect, integral field spectroscopy offers a unique way to detect PNe against the bright stellar background their central regions. In the framework of the Fornax 3D Project, we use MUSE@VLT to explore the PNe population of the brightest early-type galaxies within the Virial radius of the Fornax cluster, correlating our PNe findings with our own measurements for the stellar kinematics and metallicity. We also discuss the universality of the PN luminosity function, its use as a distance indicator and further report on the agreement with literature values from Surface Brightness Fluctuation measurements.
Using VLT/MUSE Spectrograph.
Page 1: Figure 1 depicts a simplified stellar evolution diagram of the final evolutionary stages of stars with initial masses of 1-8 Mʘ. Stars like our own Sun, will drastically increase in size and pass through the Red Giant branch, where the star has drastically increased in size. Later, the outer envelope expands a second time (Asymptotic Giant Branch). Strong mass loss creates a diffuse, gaseous environment around the exposed core. This is the start of the Planetary nebulae (PNe) phase.
Figure 2 shows an integrated spectrum of a PNe, highlighting a PN’s modelled [OIII] 5007 Å (doubly ionised Oxygen) emission.
The title of the accompanying published paper, and QR code for ease of access, are included.
Page 2: Figure 3 shows the galaxy NGC1380 (FCC167), a red box shows the fields of view (FOV) covered by our observations (MUSE@VLT). Figure 4 shows the white-light image from our data-cube, this is the very central region of the galaxy. Figure 5 breaks down the components of a generic spectrum. This is the result of running the two routines: pPXF [1] and GandALF [2], which work together to model the stellar and nebulous emission components of our spectral data. By removing the star’s light, we reveal the fainter emissions from PNe.
Figure 6 shows a signal divided by noise map, in the emission of double ionised oxygen. This is used to initially find the PNe sources.
Page 3: PNe are not only interesting objects but, have important applications in extragalactic Astronomy. Ciardullo [3] first introduced an analytical planetary nebulae luminosity function (PNLF). They found that the number of bright objects dropped off suddenly. This invariant feature of the PNLF, as calibrated by Ciardullo [3], using M31 PNe, allows us to estimate a distance to the host galaxy. Figure 7 is an example PNLF from our work. Converting between apparent (m5007) and absolute magnitude (M*5007= - 4.5), results in a distance modulus.
Comparing our independently derived distances from the PNLF, against Surface Brightness Fluctuations (SBF) [4] (see figure 8), we find good agreement between the two average estimates.
Page 4: This work primarily focuses on the results of Buzzoni et al 2006 [5], where PNe from galaxy haloes were compared with metallicity measurements from the galaxy centre. Halo and central region stars are often quite different. Figure 9, from Buzzoni et al 2006 [5], depicts an apparent trend between the luminosity specific PN frequency (alpha), and the metallicity measure of the host galaxy (Mg2).
Our work: figure 10, shows the preliminary results of comparing central PNe, against metallicity measurements made in the same spatial regions. We find a, similar, though weaker, trend.
Figure 11 is an annotated diagram [6] to help understand how metallicity may alter stellar evolution at the horizontal branch phase: metal poorer stars produce PNe, metal richer stars (hotter Horizontal branch stars, EHB) bypassing the PN phase.
References:
1 - Cappellari, M. 2017, MNRAS, 466, 798
2 - Sarzi, M., Falcón-Barroso, J., Davies, R. L., et al. 2006, MNRAS, 366, 1151
3 - Ciardullo, R., Jacoby, G. H., Ford, H. C., & Neill, J. D. 1989, ApJ, 339, 53
4 - Blakeslee, J. P., Jordán, A., Mei, S., et al. 2009, ApJ, 694, 556
5 - Buzzoni, A., Arnaboldi, M., & Corradi, R. L. M. 2006, MNRAS, 368, 877
6 - Dorman, B. et al 1993, 1993ApJ…419…596