Measuring fundamental properties of young stars

Talk at Columbia University Stellar and Planetary lunch talk on Friday, November 18, 2016. Hosted by Stephanie Douglas.

We measured the starspot temperature and coverage fraction using IGRINS spectra and spectroscopic inference. Starspots are a confounding factor in assigning temperatures and therefore ages to young stars.

The Figure on Slide 42 has been updated with revised calculations, please see the arXiv paper or ApJ paper for the most up-to-date, downloadable figures and data.

Transcript

1. Measuring fundamental properties of young stars Michael Gully-Santiago postdoctoral work at Kavli Institute for Astronomy & Astrophysics Friday, November 18, 2016 at Columbia University Collaborators: Greg Herczeg (KIAA), Ian Czekala (CfA/KICAP), Garrett Somers (OSU/Vanderbilt), J.F. Donati (CNRS), Konstantin Grankin (CrAO), Kevin Covey (WWU), G. Mace (UTexas), MATYSSE team, ASASSN team, ++
2. We want to know the ages and masses of young stars so that we can understand how star and planet formation proceed in time.
3. We want to know the ages and masses of young stars so that we can understand how star and planet formation proceed in time. Age is not a direct observable. Mass is sometimes a direct observable, but only in rare eclipsing binary systems or resolved gas disk systems.
4. Ages are estimated by placing a young star on a pre-main sequence HR diagram.
5. Ages are estimated by placing a young star on a pre-main sequence HR diagram.
6. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why?
7. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why? - Observational uncertainties - True age spreads - Episodic accretion - Physics beyond the standard evolutionary models - Magnetic fields - Starspots
8. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why? - Observational uncertainties - True age spreads - Episodic accretion - Physics beyond the standard evolutionary models - Magnetic fields - Starspots
9. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why? - Observational uncertainties - True age spreads - Episodic accretion - Physics beyond the standard evolutionary models - Magnetic fields - Starspots
10. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why? - Observational uncertainties - True age spreads - Episodic accretion - Physics beyond the standard evolutionary models - Magnetic fields - Starspots
11. Observed star clusters (~1 Myr) show large age spreads of 1-10 Myr. Why? - Observational uncertainties - True age spreads - Episodic accretion - Physics beyond the standard evolutionary models - Magnetic fields - Starspots
12. Starspots inhibit convective efficiency. Somers & Pinnsoneault 2015 Less efficient energy transport means stars get larger (R increases) but cooler (T decreases) Postdoc at Vanderbilt
13. Starspots confound measurements of L and Teff. Tamb=Teff 0th order assumption No starspots Tamb
14. Starspots confound measurements of L and Teff. Tamb=Teff 0th order assumption No starspots 1st order correction Non-emitting starspots Tamb Tspot = 0 K fspot Tamb
15. Starspots confound measurements of L and Teff. Tamb=Teff 0th order assumption No starspots 1st order correction Non-emitting starspots Tamb Tspot > 0 K fspot Tamb Tspot = 0 K fspot Tamb 2nd order correction Emitting starspots
16. Starspots confound measurements of L and Teff. Tamb=Teff 0th order assumption No starspots 1st order correction Non-emitting starspots Tamb Tspot > 0 K fspot Tamb Tspot = 0 K fspot Tamb 2nd order correction Emitting starspots Teff < Tamb
17. Starspots confound measurements of L and Teff. Tamb Tspot fspot 1-fspot My Research - We directly detect the spectrum arising from starspots. - That should probably surprise you... T4 is steep! - Not only that, but starspots are on Wien side of BB curve. - We benefit from moving to the infrared and high res. - Still: You need large covering fraction of spots to make up for T4
18. Starspot emission Tamb Tspot fspot 1-fspot Tspot = 2800 K Tamb = 4100 K fspot = 0.5 (!) Example Key insight: - In the visible, starspot flux is 5-20x weaker than the ambient photosphere. - In the near-IR, starspot flux is only 2.5-4x weaker than ambient
19. Starspot emission Tamb Tspot fspot 1-fspot Tspot = 2800 K Tamb = 4100 K fspot = 0.5 (!) Example Key insight: - In the visible, starspot flux is 5-20x weaker than the ambient photosphere. - In the near-IR, starspot flux is only 2.5-4x weaker than ambient IGRINS ESPaDOnS
20. IGRINS: Immersion Grating Infrared Spectrograph Park et al. 2014 - R = λ/δλ = 45,000 - Δλ = 1.4 - 2.4 μm - 2.7 m HJST at McDonald Observatory (*now 4.3 m DCT at Lowell Observatory) - Single slit echelle spectrograph: ~28 H-band orders and 25 K-band orders Silicon Immersion Grating (diffraction grating) Gully-Santiago et al. 2012
21. ~28 H-band orders and 25 K-band orders
22. LkCa 4 is an ideal target for detecting starspot emission. Vrba et al. 1993 1. Associated with nearby (~140 pc) Taurus young (~1 Myr) star cluster 2. No mid-IR to sub-mm excess that would indicate a circumstellar disk 3. Weak-lined T-Tauri Star (no ongoing accretion based on UV excess). 4. No evidence for a nearby companion from AO imaging, and spec. monitoring 5. Large amplitude of photometric variability 6. Availability of >20 years of polychromatic photometric monitoring 7. Recent spectropolarimetric tomography Hartigan+ 1995, Andrews & Williams 2005, Edwards+ 2006, Kraus+ 2011, Nguyen+ 2012, Donati+ 2014, Grankin+ 2008
23. LkCa 4 is an ideal target for detecting starspot emission. Vrba et al. 1993 1. Associated with nearby (~140 pc) Taurus young (~1 Myr) 2. No mid-IR to sub-mm excess that would indicate a circumstellar disk 3. Weak-lined T-Tauri Star (no ongoing accretion based on UV excess). 4. No evidence for a nearby companion from AO imaging, and spec. monitoring 5. Large amplitude of photometric variability 6. Availability of >20 years of polychromatic photometric monitoring 7. Recent spectropolarimetric tomography Hartigan+ 1995, Andrews & Williams 2005, Edwards+ 2006, Kraus+ 2011, Nguyen+ 2012, Donati+ 2014, Grankin+ 2008 LkCa 4 spectrum should be devoid of complicating factors, and should have a large starspot signal in its spectrum.
24. LkCa 4 spectrum should be devoid of complicating factors, and should have a large starspot signal in its spectrum. How to figure out which lines are attributable to starspots or ambient photosphere? portion of LkCa 4 IGRINS spectrum from November 2015
25. We forward  model the IGRINS spectra. 0.0 0.2 0.4 0.6 0.8 1.0 raw 5164 5165 5166 5167 5168 5169 5170 [˚ A] 0.0 0.2 0.4 0.6 0.8 1.0 convolved and resampled f ⇥ 107 [erg cm 2 s 1 ˚ A 1 ] Synthetic spectra from pre-computed PHOENIX model grids in Teff, logg, [Fe/H] rameter space of the grid. Variable Range Step size Teff [K] 2300–7000 100 7000–12 000 200 log g 0.0–+6.0 0.5 [Fe/H] −4.0−−2.0 1.0 –2.0–+1.0 0.5 [α/Fe] –0.2–+1.2 0.2 ha element abundances [α/Fe] 0 are only available for eff ≤ 8000 K and −3 ≤ [Fe/H] ≤ 0. mpling of the spectra in the grid. Range [Å] Sampling 500–3000 ∆λ = 0.1Å 3000–25 000 R ≈ 500 000 25 000–55 000 R ≈ 100 000 Husser et al. 2013 Czekala et al. 2015
26. We forward  model the IGRINS spectra. Starfish takes into account the uncertainty introduced by discrete models. Czekala et al. 2015 Emulator Eigenspectra modified by extrinsic parameters emulator covariance matrix Gaussian process models eigenspectra weights as function of reconstruction of mean model spectrum delivers probability distribution of weights as function of
27. We forward  model the IGRINS spectra. Starfish is an open source spectral inference framework for stellar spectra. github.com/iancze/Starfish
28. We forward  model the IGRINS spectra. Czekala et al. 2015 0.6 1.2 1.8 2.4 data model 5140 5150 5160 5170 5180 5190 5200 [˚ A] 0.5 0.0 0.5 residuals f ⇥ 10 13 [erg cm 2 s 1 ˚ A 1 ] Starfish parameters: 1. Teff 2. logg 3. [Fe/H] 4. v sini 5. vz 6. Ω 7-9. c0, c1, c2... 10. GP scale 11. GP amplitude 12. σ scale 13. Tspot 14. fspot fits for all stellar and nuisance parameters simultaneously.
29. We forward  model the IGRINS spectra. Czekala et al. 2015 0.6 1.2 1.8 2.4 data model 5140 5150 5160 5170 5180 5190 5200 [˚ A] 0.5 0.0 0.5 residuals f ⇥ 10 13 [erg cm 2 s 1 ˚ A 1 ] Starfish parameters: 1. Teff 2. logg 3. [Fe/H] 4. v sini 5. vz 6. Ω 7-9. c0, c1, c2... 10. GP scale 11. GP amplitude 12. σ scale 13. Tspot 14. fspot fits for all stellar and nuisance parameters simultaneously. Intrinsic Extrinsic Nuisance
30. We forward  model the IGRINS spectra. Czekala et al. 2015 0.6 1.2 1.8 2.4 data model 5140 5150 5160 5170 5180 5190 5200 [˚ A] 0.5 0.0 0.5 residuals f ⇥ 10 13 [erg cm 2 s 1 ˚ A 1 ] Starfish parameters: 1. Tamb 2. logg 3. [Fe/H] 4. v sini 5. vz 6. Ω 7-9. c0, c1, c2... 10. GP scale 11. GP amplitude 12. σ scale 13. Tspot 14. fspot fits for all stellar and nuisance parameters simultaneously. Intrinsic Extrinsic Nuisance Starspots
31. We forward  model the IGRINS spectra. Starfish parameters: 1. Tamb 2. logg 3. [Fe/H] 4. v sini 5. vz 6. Ω 7-9. c0, c1, c2... 10. GP scale 11. GP amplitude 12. σ scale 13. Tspot 14. fspot Intrinsic Starspots Tspot = 2800 K Tamb = 4100 K Ambient Starspot
32. We forward  model the IGRINS spectra. Starfish is an open source spectral inference framework for stellar spectra. Starfish parameters: 1. Tamb 2. logg 3. [Fe/H] 4. v sini 5. vz 6. Ω 7-9. c0, c1, c2... 10. GP scale 11. GP amplitude 12. σ scale 13. Tspot 14. fspot Intrinsic Starspots = + Composite Ambient Starspot Tspot = 2800 K Tamb = 4100 K **Lots  of  assump,ons  embedded  here
33. The spectrum has features from both ambient photosphere and starspots. λ (Angstrom) The constraint on filling factor comes from the range of flux ratios.
34. Each spectral order yields an estimate for Tamb, Tspot, fspot The models provide a range of credibility, with some orders more informative than others.
35. The data are most consistent with Tamb = 4100 K, Tspot = 2750 K, fspot = 0.8
36. fspot = 80%?! That means 1-fspot = 0.2! Wait, isn't that actually a hotspot? All previous optical measurements of LkCa 4 mark the 4100 K component as photosphere.
37. Photometric modulation only probes longitudinally asymmetric spots. ΔV LkCa 4 ΔV 2015: 0.5 2004: 0.8 1986: 0.2 LkCa 4 light curve
38. You can find a minimum coverage of starspots for LkCa 4 ΔV LkCa 4 ΔV 2015: 0.5 2004: 0.8 1986: 0.2
39. You can find a minimum coverage of starspots for LkCa 4 ΔV LkCa 4 ΔV 2015: 0.5 2004: 0.8 1986: 0.2
42. LkCa 4 in the HR diagram - Teff 4100 K --> ~3300 - 3500 K depending on adopted parameters - Inferred LkCa 4 mass decreases by 2-3x, assuming  same  tracks**   - Inferred LkCa 4 age decreases by ~2x, assuming  same  tracks** - **assuming same stellar evolutionary tracks does not make sense-- we have just shown that this source has a much larger opacity source than what is assumed in the Baraffe et al. 2015 tracks.
43. Big Picture / Why does this matter? 1. Stars are probably more spotted than we previously thought 2. Polar spots would have evaded most conventional methods of detecting and characterizing starspots, since they induce zero photometric modulation. 3. If LkCa 4 is representative of other young stars, the masses and ages of all young stars are considerably biased. 4. The stellar age biases change timescale available for planet formation. 5. What matters is the starspot coverage history, which is generally unobservable. 6. Teff measurement is hindered for highly inclined young spotted stars.
44. Big Picture / Why does this matter? 1. Stars are probably more spotted than we previously thought 2. Polar spots would have evaded most conventional methods of detecting and characterizing starspots, since they induce zero photometric modulation. 3. If LkCa 4 is representative of other young stars, the masses and ages of all young stars are considerably biased. 4. The stellar age biases change timescale available for planet formation. 5. What matters is the starspot coverage history, which is generally unobservable. 6. Teff measurement is hindered for highly inclined young spotted stars.
45. Big Picture / Why does this matter? 1. Stars are probably more spotted than we previously thought 2. Polar spots would have evaded most conventional methods of detecting and characterizing starspots, since they induce zero photometric modulation. 3. If LkCa 4 is representative of other young stars, the masses and ages of all young stars are considerably biased. 4. The stellar age biases change timescale available for planet formation. 5. What matters is the starspot coverage history, which is generally unobservable. 6. Teff measurement is hindered for highly inclined young spotted stars.
46. Recent evidence for large spot coverage in Pleiades 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 2600 3000 3500 4000 4500 5000 5500 6000 6500 TiO2n Teff (K) Inactive dwarfs PHOENIX(4.5) PHOENIX(5.0) Cubic splines fits Estimate of Tamb, Tspot, fspot in 304 LAMOST spectra 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 3000 3500 3800 4000 4500 5000 5500 6000 6500 fs Teff (K) Pleiades? Pleiades
47. Conclusions - We have measured a large covering fraction of starspots on the surface of the large-amplitude variable WTTS LkCa 4. - Our technique employs forward modeling IGRINS spectra. - Recent results (Fang+2016, Roettenbacher+2016, Covey+ 2016) suggest that large / polar starspots could be common. - Estimates of masses and ages of stars have probably been systematically biased, but more work is needed
48. Extras
50. Single component Two components Whole spectrum fitting Czekala et al. 2015. + probabilistic - slow mixing Sampling issue. Chunking order- by-order What I originally did. Robust against systematics, but heuristic. Amount of spectrum fit at once. Sampling method. I have altered the Czekala et al. 2015 spectroscopic framework.
51. Sampling  issue: How  to  sample  with  strongly  correlated  parameters   in  many  dimensions,  without  emcee?
52. A fit to a single IGRINS spectral order: m = 85 + nuisances Before: 50,000 samples After: 40 x 4,000 samples
53. A fit to a single IGRINS spectral order: m = 85 + nuisances Before: 50,000 samples After: 40 x 4,000 samples
54. A fit to a single IGRINS spectral order: m = 85 + nuisances Before: 50,000 samples After: 40 x 4,000 samples
55. A fit to a single IGRINS spectral order: m = 85 Before: 50,000 samples After: 40 x 4,000 samples + nuisances
56. Starspots confound measurements of L and Teff. Tamb Tspot fspot 1-fspot Tspot > 0 K
57. IGRINS  has  high  throughput. VPH Immersion  grating KECK+  NIRSPEC,   S/N  80  in  16  min HJST  +  IGRINS,   S/N  140  in  40  min G.  Mace Gully-Santiago et al. 2012 Gully-Santiago et al. unpublished
58. We could look for known, clean, temperature-sensitive lines. O'Neal & Neff 1997
59. We could look for known, clean, temperature-sensitive lines. O'Neal & Neff 1997
60. All  of  the  so6ware  development  is  done  in  the  open.
61. The spectrum has features from both ambient photosphere and starspots. But - The gross appearance is dominated by temperature variation - Large bandwidth offers resilience We expect the model fits will be imperfect: - Bad oscillator strengths - Zeeman splitting - Assumptions about shared extrinsic properties. - Starspots will probe higher pressure regions, mimicking logg effects
62. LkCa 4 has photometric monitoring going back 31 years. May 6, 1985 Nov. 16, 2016
63. P = 3.375 days The LkCa 4 IGRINS spectrum was acquired somewhere near the middle of its variability.
64. P = 3.375 days There is multi-epoch spectropolarimetry data from ESPaDOnS: High resolution optical echelle spectrograph on CFHT.
65. P = 3.375 days We examined the spectral energy distribution (SED) at the 2MASS, DBLSpec, and TripleSpec epochs
66. LkCa 4 varies between ~74-86% coverage fraction of cool spots. - We can scale V magnitude to spot coverage, assuming the spot temperature is constant. Some  starspots  on  the  stellar  surface  always  face  the  observer.   This  geometry  can  arise  from  polar  starspots. - Safe to assume all of the V-band flux comes from the ambient photosphere.
67. Spectral Energy Distribution assuming Tamb = 4100 K, Tspot = 2750 K, fspot = f2MASS Consistent with large coverage fraction of starspots
68. Flux-calibrated, near-contemporaneous low-res optical and near-IR data from DoubleSpec and TripleSpec. Consistent with large coverage fraction of starspots
69. ESPaDOnS tomographic modeling provides a surface brightness map. Donati et al. 2014 There is evidence for polar spots. But tomography is only sensitive to large features; small features can "hide", biasing the coverage fraction estimates.
70. Observed TiO lines are consistent with large coverage fraction of starspots. 12 12.5 13 13.5 1.25 1.3 1.35 1.4 1.45 1.5 1.55 Vmag V−R (mag) Observed V-R is consistent with large coverage fraction of starspots. Further evidence for large coverage fraction of spots on LkCa 4
71. Is LkCa 4 merely an extreme source? K2  Cycle  2  light  curves  for     1658  candidate  or  confirmed  young   stars  towards  Oph/Sco.   compared  to     everything  else  in  that  Cycle.   (Young  stars  are  usually  more   variable  everything  else.)   -­‐ InterquarKle  Range  (IQR:  Q3-­‐Q1)   -­‐ Standard  DeviaKon  (σ).   (IQR  vs.  σ  separates  bursty  and   smooth  lightcurve  morphologies.) LkCa 4
72. Is LkCa 4 merely an extreme source? K2  Cycle  2  light  curves  for     1658  candidate  or  confirmed  young   stars  towards  Oph/Sco.   compared  to     everything  else  in  that  Cycle.   (Young  stars  are  usually  more   variable  everything  else.)   -­‐ InterquarKle  Range  (IQR:  Q3-­‐Q1)   -­‐ Standard  DeviaKon  (σ).   (IQR  vs.  σ  separates  bursty  and   smooth  lightcurve  morphologies.) LkCa 4
73. Recent evidence for large spot coverage in Pleiades Estimate of Tamb, Tspot, fspot in 304 LAMOST spectra 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 3000 3500 3800 4000 4500 5000 5500 6000 6500 fs Teff (K) Pleiades? Pleiades - Tamb fixed from V-I - TiO band index scale from many inactive dwarfs - Tspot taken as value that minimizes fspot - Evidence for trends with Rossby number, Tamb and Tspot Fang et al. 2016 arXiv:1608.05452 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2500 3000 3500 4000 4500 fs Ts (K) 5118 K 4722 K 4224 K Tq = 3609 K + 50 K + 100 K - 50 K - 100 K 3399 K PELS 162 HII 1883 HII 335 HCG 101 HCG 219
75. APOGEE spectra of thousands of young stars show large disagreement Cottaar et al. 2014 Un-accounted for starspots are probably responsible for systematic differences in stellar properties derived between the optical and near-IR