NAC – 24.05.2016 Do we understand how stellar winds change stellar fireworks? Mathieu Renzo PhD @ API Collaborators: S. E. de Mink, C. D. Ott, S. N. Shore, E. Zapartas, Y. G¨ otberg, C. Neijssel 1 / 16
Outline Importance of Massive Stars... • ... and their mass loss Stellar Winds • Outline of the Theory • Treatment in Evolutionary Codes Preliminary Results • Final Masses • Impact on the core structure Conclusions 2 / 16
Why are Massive Stars Important? M ZAMS � 8 − 10 M ⊙ • Nucleosynthesis • Chemical Evolution of Galaxies • Effects on Star Formation • Re-ionization Epoch • Observations of Farthest Galaxies • Catastrophic Events 3 / 16
Mass Loss – Why does it Matter... ... for the environment of the stars? • Pollution of the InterStellar Medium (ISM) • Tailoring of the CircumStellar Material (CSM) • Effects on the Star Formation ... for the stellar structure? • Evolutionary Timescales • Appearance & Classification (e.g. WR) • Light Curve and Explosion Spectrum • Final Fate (BH, NS or WD?) 4 / 16
Possible Mass Loss Mechanisms Radiative Driving ⇐ Stellar Winds Dynamical Instabilities ⇐ LBVs, Pulsations, Super-Eddington Winds, Centrifugal Disk Shedding, Binary interactions ⇐ Roche Lobe OverFlows Figure: η Carinae. (RLOF) 5 / 16
Outline Importance of Massive Stars... • ... and their mass loss Stellar Winds • Outline of the Theory • Treatment in Evolutionary Codes Preliminary Results • Final Masses • Impact on the core structure Conclusions 6 / 16
Radiatively Driven Winds in One Slide ∆ p = h c ( ν i cos ( θ i ) − ν f cos ( θ f )) Problems: High Non-Linearity and Clumpiness: = � ρ 2 � def � ρ � 2 � = 1 ⇒ Inhomogeneities ⇒ ˙ M � = 4 π r 2 ρ v ( r ) f cl 7 / 16
Radiatively Driven Winds in One Slide Risk: ∆ p = h Possible Overestimation of the c ( ν i cos ( θ i ) − ν f cos ( θ f )) Wind Mass Loss Rate Problems: High Non-Linearity and Clumpiness: = � ρ 2 � def � ρ � 2 � = 1 ⇒ Inhomogeneities ⇒ ˙ M � = 4 π r 2 ρ v ( r ) f cl 7 / 16
Mass Loss in (Semi–)Empirical parametric models. Uncertainties encapsulated in efficiency factor: ˙ M ( L , T eff , Z , R , M , ... ) ⇐ η ˙ M ( L , T eff , Z , R , M , ... ) η is a free parameter: η ∈ [ 0, + ∞ ) Figure: From Smith 2014, ARA&A, 52, 487S 8 / 16
Different dM / dt algorithms with Grid of Z ⊙ ≃ 0.019 , non-rotating stellar models: • Initial mass: M ZAMS = { 15, 20, 25, 30, 35 } M ⊙ ; • Efficiency: � f cl = { 1, 1 1 η ≡ 10 } ; 3 , • Different combinations of wind mass loss rates for “hot” ( T eff ≥ 15 [ kK ] ), “cool” ( T eff < 15 [ kK ] ) and WR stars: Kudritzki et al. ’89; Vink et al. ’00, ’01; Van Loon et al. ’05; Nieuwenhuijzen et al. ’90; De Jager et al. ’88; Nugis & Lamers ’00; Hamann et al. ’98. 9 / 16
Outline Importance of Massive Stars... • ... and their mass loss Stellar Winds • Outline of the Theory • Treatment in Evolutionary Codes Preliminary Results • Final Masses • Impact on the core structure Conclusions 10 / 16
Results 1: Impact on the Final Mass VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL VNJH KNJH VdJH KdJH 1.0 Legend: 0.9 • η = 0.1 x η = 0.33 0.8 + η = 1.0 M / M ZAMS 0.7 • η → largest 0.6 uncertainty • Dust driven 0.5 ( vL ) → very high mass 0.4 loss for lower 0.3 M ZAMS . 15 20 25 30 35 M ZAMS [ M ⊙ ] 11 / 16
Results 1: Impact on the Final Mass VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL VvLNL KvLNL KNJNL VNJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL KdJNL VdJNL VNJH KNJH VdJH KdJH 1.0 Legend: 0.9 • η = 0.1 Impossible to map: x η = 0.33 0.8 + η = 1.0 M / M ZAMS 0.7 M f ≡ M f ( M ZAMS ) • η → largest 0.6 uncertainty • Dust driven 0.5 ( vL ) → very high mass 0.4 loss for lower 0.3 M ZAMS . 15 20 25 30 35 M ZAMS [ M ⊙ ] 11 / 16
Computing Advanced Burning Stages • Initially small effect ⇒ N zones � 20 000 ; • Complex nuclear burning ⇒ N iso � 200 ; SurfSara’s Cartesius Computer. 12 / 16
Results 2: Core Structure def 2.5/ M ⊙ Compactness Parameter: ξ 2.5 ( t ) = R ( M ) /1000 km • “Large” ξ 2.5 ⇒ harder to explode ⇒ BH formation • “Small” ξ 2.5 ⇒ easier to explode ⇒ NS formation 13 / 16
Results 2: ξ 2.5 @ Oxygen Depletion (Reduced grid) Legend: • η = 0.1 x η = 0.33 + η = 1.0 Post O burning evolution ⇐ Core contraction ⇐ Amplification of the differences. 14 / 16
Outline Importance of Massive Stars... • ... and their mass loss Stellar Winds • Outline of the Theory • Treatment in Evolutionary Codes Preliminary Results • Final Masses • Impact on the core structure Conclusions 15 / 16
Conclusions: • η has a larger influence on the final mass than the wind algorithm; • Early (“hot phase”) mass loss influences the further evolution; • Uncertainties in stellar winds prevent to go back in time and infer M ZAMS of observed evolved stars; • Different algorithmic representations of stellar winds ⇒ Qualitatively different evolutionary tracks, and predicted final fate; (...Cartesius still crunching numbers for post-O burning evolution...) Thank you! 16 / 16
Outline Backup slides 17 / 16
Supernova Taxonomy Back 18 / 16
Roche Lobe OverFlow Back Mass Transfer in Binaries 19 / 16
Wind Oservational Diagnostics • P Cygni line profiles Back • Optical and near UV lines (e.g. H α ) • Radio and IR continuum excess • IR spectrum of molecules (e.g. CO) • Maser lines (for low density winds) Assumptions commonly needed: � β � r • Velocity structure: v ( r ) ≃ 1 − with β ≃ 1 R ∗ • Chemical composition and ionization fraction ˙ M = 4 π r 2 ρ v ( r ) • Spherical symmetry: • Steadiness and (often) homogeneity ˙ M derived from fit of (a few) spectral lines. No theoretical guaranties coefficients are constant. 20 / 16
Wolf-Rayet Stars Back Observational Definition: Based on spectral features indicating a Strong Wind : • Hydrogen Depletion ( � = Lack of Hydrogen) • Broad Emission Lines • Steep Velocity Gradients Sub-categories: WN,WC,WO,WNL, etc. Computational Definition ( ): • X s < 0.4 Impossible to distinguish sub-categories without spectra! 21 / 16
Why Impulsive Mass Loss? Observational Evidence: • LBVs • Progenitors of H-poor core collapse SNe ( ∼ 30% ) • Dense CSM for Type IIn SNe Theory: Dynamical Events ⇒ not ready • Pulsational Instabilities • Roche Lobe Overflow in binaries • Catastrophic Eruption(s) ∆ M wind ≪ ∆ M impulsive (?) 22 / 16
The Stripping Process 5.2 unstripped 5.1 M = 15 M ⊙ , Z = Z ⊙ 5.0 MCE Remove mass in steps of 1 M ⊙ , 4.9 max { ∆ M impulsive } = 7 M ⊙ . log 10 ( L / L ⊙ ) 4.8 4.7 4.6 mSGB 4.5 4.4 4.3 hMR 4.2 4.5 4.4 4.3 4.2 4.1 4.0 3.9 3.8 3.7 3.6 log 10 ( T eff / [ K ]) Red dot : T eff = 10 4 [ K ] ; Yellow Triangle : R ≥ R max /2 = 375 R ⊙ ; Cyan Diamond : Maximum Extent Convective Envelope. 23 / 16
Chosen Stripping Points 5.2 unstripped 5.1 M = 15 M ⊙ , Z = Z ⊙ 5.0 MCE 4.9 log 10 ( L / L ⊙ ) 4.8 4.7 4.6 mSGB 4.5 4.4 4.3 hMR 4.2 4.5 4.4 4.3 4.2 4.1 4.0 3.9 3.8 3.7 3.6 log 10 ( T eff / [ K ]) t ( MCE ) − t ( mSGB ) ≃ 10 4 [ yr ] ≪ 14.13 × 10 6 [ yr ] 24 / 16
Stripped series on the HR diagram Evolutionary tracks depend only on ∆ M impulsive 5.2 5.0 MCE log 10 ( L / L ⊙ ) 4.8 4.6 4.4 mSGB hMR 4.2 4.4 4.2 4.0 3.8 3.6 4.4 4.2 4.0 3.8 3.6 4.4 4.2 4.0 3.8 3.6 log 10 ( T eff / [ K ]) 25 / 16
Evolution toward Higher T eff 5.2 E unstripped G 5.1 MCE 7 M ⊙ F 5.0 MCE 7 M ⊙ , η = 0 D A 4.9 log 10 ( L / L ⊙ ) 4.8 C 4.7 B 4.6 4.5 4.4 3.75 3.70 3.65 3.60 3.55 log 10 ( T eff / [ K ]) Impulsive + wind mass loss drives blueward evolution 26 / 16
pre-SN Stripped Structures Si core CO core He core 10 hMR 3 M ⊙ unstripped mSGB 1 M ⊙ hMR 7 M ⊙ 8 mSGB 2 M ⊙ hMR 5 M ⊙ mSGB 3 M ⊙ MCE 1 M ⊙ 6 mSGB 4 M ⊙ MCE 2 M ⊙ 4 mSGB 5 M ⊙ MCE 3 M ⊙ log 10 ( ρ / [ g cm − 3 ]) mSGB 6 M ⊙ MCE 4 M ⊙ 2 mSGB 7 M ⊙ MCE 5 M ⊙ hMR 1 M ⊙ MCE 6 M ⊙ 0 6 hMR 2 M ⊙ MCE 7 M ⊙ -2 5 -4 4 -6 3 -8 2 2.0 2.5 3.0 3.5 -10 0 1 2 3 4 5 6 7 8 9 10 11 12 M [ M ⊙ ] 27 / 16
Light Curves from Stripped Models Comparison of three progenitor grids 43 Figure: Morozova et al. – ApJ,814,63M mSGB hMR log 10 L [erg s − 1 ] MCE 1 M ⊙ stripped 2 M ⊙ stripped 3 M ⊙ stripped 42 4 M ⊙ stripped 5 M ⊙ stripped 6 M ⊙ stripped 7 M ⊙ stripped 0 50 100 Time [days] 28 / 16
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