Simulating Feedback-Driven Galactic Chemical Evolution with Individual Stars

Transcription

1 Simulating Feedback-Driven Galactic Chemical Evolution with Individual Stars Andrew Emerick Blue Waters Fellow NSF Graduate Research Fellow Greg Bryan Mordecai-Mark Mac Low Emerick + 18a (submitted) Emerick + 18b (in prep)

2 Commitment to Open Science: Enzo: Grackle:

3 Uncertainties in Galactic Evolution Role of feedback: Coupling to ISM and galactic winds Regulating star formation Relative importance of each feedback mechanism Galactic chemical evolution: Enrichment of star formation regions Inhomogeneous mixing in the ISM Imprinting and evolution of stellar abundances

4 Star Particles = Stellar Populations in Simulations Issues with simple stellar populations at high res. (Revas + 16): IMF sampling at M* < 104 M Smoothing over stellar properties

5 Individual star simulations are logical next step Issues with simple stellar Detailed accounting of: populations at high res. (Revas + 16): Feedback (winds + radiation) IMF sampling at M* < 104 M Chemical Enrichment Smoothing over stellar properties

6 Individual star simulations are logical next step Issues with simple stellar Detailed accounting of: populations at high res. (Revas + 16): Feedback (winds + radiation) IMF sampling at M* < 104 M Chemical Enrichment Smoothing over stellar Caveat: Expensive properties

7 Galactic Chemical Evolution in Enzo Isolated galaxy simulations in Enzo (Bryan + 14)1 Stars particles from 1 to 100 Msun Multi-channel feedback (next slide) Grackle (Smith + 17) Non-equilibrium chemistry (with H2), UVB, and cooling Stellar yields with 15 individual metals: NuGrid (Ritter+ 18, Pignatari + 16) for 1sun < M* < 25 Msun M* > 25 Msun stellar winds (Slemer + in prep) 1 This Bitbucket: aemerick/enzo-emerick

8 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

9 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

10 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

11 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

12 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

13 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

14 ISM in Low Mass Dwarf Galaxies 250 pc Mgas= 2 x 106 Msun Mvir= 3 x 109 Msun

15 First Results: Feedback Driven Metal Mixing

16 First Results: Feedback Driven Metal Mixing Key results thus far: 1) Metal mixing is complex and inhomogenous. 2) Metal distributions depend upon nucleosynthetic origin. 3) Metal distribution in the ISM can be described analytically Emerick + 18a (submitted) Emerick + 18b (in prep)

17 First Results: Feedback Driven Metal Mixing Key results thus far: 1) Metal mixing is complex and inhomogenous. 2) Metal distributions depend upon nucleosynthetic origin. 3) Metal distribution in the ISM can be described analytically Emerick + 18a (submitted) Emerick + 18b (in prep)

18 Metal Fraction Distributions in the ISM

19 Metal Fraction Distributions in the ISM Histogram of gas mass binned by metal mass fraction

20 Metal Fraction Distributions in the ISM Histogram of gas mass binned by metal mass fraction Normalize to generate a PDF: p(z) dz = 1

21 Metal Fraction Distributions in the ISM Histogram of gas mass binned by metal mass fraction Normalize to generate a PDF: p(z) dz = 1 For the sake of plotting: max( p(z) ) = 1

22 Oxygen Distribution in the Disk (all ISM)

23 Oxygen Distribution in the Disk (all ISM) Interquartile Range (in dex) Median (in dex) Disk: Disk: 0.27

24 Oxygen Distribution in the ISM: Phase-by-phase Interquartile Range (in dex) Median (in dex) Disk: Disk: 0.27 CNM: CNM: 0.25

25 Oxygen Distribution in the ISM: Phase-by-phase Interquartile Range (in dex) Median (in dex) Disk: Disk: 0.27 CNM: CNM: 0.25 WNM: WNM: 0.32

26 Oxygen Distribution in the ISM: Phase-by-phase Interquartile Range (in dex) Median (in dex) Disk: Disk: 0.27 CNM: CNM: 0.25 WNM: WNM: 0.32 WIM: WIM: 0.34

27 Oxygen Distribution in the ISM: Phase-by-phase Interquartile Range (in dex) Median (in dex) Disk: Disk: 0.27 CNM: CNM: 0.25 WNM: WNM: 0.32 WIM: WIM: 0.34 HIM: HIM: 1.28

28 First Results: Feedback Driven Metal Mixing Key results thus far: 1) Metal mixing is complex and inhomogenous. 2) Metal distributions depend upon nucleosynthetic origin. 3) Metal distribution in the ISM can be described analytically Emerick + 18a (submitted) Emerick + 18b (in prep)

29 Oxygen vs. Nitrogen Distributions in the ISM SNe Dominated Enrichment

30 Oxygen vs. Nitrogen Distributions in the ISM SNe Dominated Enrichment AGB Wind Dominated Enrichment

31 Oxygen vs. Nitrogen Distributions in the ISM SNe Dominated Enrichment CNM IQR: 0.25 dex AGB Wind Dominated Enrichment

32 Oxygen vs. Nitrogen Distributions in the ISM SNe Dominated Enrichment AGB Wind Dominated Enrichment CNM IQR: 0.25 dex CNM IQR: 0.80 dex

33 First Results: Feedback Driven Metal Mixing Key results thus far: 1) Metal mixing is complex and inhomogenous. 2) Metal distributions depend upon nucleosynthetic origin. 3) Metal distribution in the ISM can be described analytically Emerick + 18a (submitted) Emerick + 18b (in prep)

34 Metal Distribution Functions in the ISM Analytic fits using log-normal + power-law PDF (e.x. Collins+2012, Burkhart+2017,Chen+2017):

35 Metal Distribution Functions in the ISM Analytic fits using log-normal + power-law PDF (e.x. Collins+2012, Burkhart+2017,Chen+2017):

36 Next Steps: 1) Physically motivated chemical evolution models (e.g. Cote ) 2) Dissect role of each feedback process in driving mixing with suite of simulations. 3) Large scale simulations of massive galaxies at high resolution (Blue Waters) a) Understand how results scale with galaxy gas fraction, SFR, halo mass, etc. b) Probe galaxy scales with better observational comparison

37 Conclusions 250 pc New feedback and chemical evolution model in Enzo Metal mixing in the ISM is complex, and far from one-zone : Significant enrichment variations across phases Significant variations across elements AGB wind elements: Couple poorly to galactic outflows (greater retention) Less efficient mixing due to energetic differences in feedback We expect similar behavior with r-process enrichment as AGB wind enrichment.