Ph.D. Thesis Defense

University of Chicago
Department of Astronomy & Astrophysics

Transcript

1. Young Stellar and Planetary Systems from the UV to the IR University of Chicago March 21, 2023 Adina Feinstein 
 NSF Graduate Research Fellow PhD Advisor: Jacob Bean
2. 2 Thousands of exoplanets have been discovered via the transit method. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%]
3. 2 Thousands of exoplanets have been discovered via the transit method. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%]
4. 3 The transit depth allows us to measure the radius of a given planet. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%] ( Rp R⋆ ) 2
5. 4 Kepler revealed two distinct populations of transiting exoplanets: Neptune-Earth sized planets & hot Jupiters.
6. 5 The young planets (< 100 Myr) don’t look like the rest of the older population.
7. 5 The young planets (< 100 Myr) don’t look like the rest of the older population.
8. 6 It’s thought that photoevaporation and core-powered mass- loss are the two primary mechanisms driving atmospheric removal. Ginzburg et al. 2017 
 Rogers et al. 2021 Lammer et al. 2003 
 Baraffe et al. 2004 
 Owen & Wu, 2017
9. 6 It’s thought that photoevaporation and core-powered mass- loss are the two primary mechanisms driving atmospheric removal. Ginzburg et al. 2017 
 Rogers et al. 2021 Lammer et al. 2003 
 Baraffe et al. 2004 
 Owen & Wu, 2017
10. 6 It’s thought that photoevaporation and core-powered mass- loss are the two primary mechanisms driving atmospheric removal. Ginzburg et al. 2017 
 Rogers et al. 2021 Lammer et al. 2003 
 Baraffe et al. 2004 
 Owen & Wu, 2017
11. 6 It’s thought that photoevaporation and core-powered mass- loss are the two primary mechanisms driving atmospheric removal. Ginzburg et al. 2017 
 Rogers et al. 2021 Lammer et al. 2003 
 Baraffe et al. 2004 
 Owen & Wu, 2017
12. 6 It’s thought that photoevaporation and core-powered mass- loss are the two primary mechanisms driving atmospheric removal. t < 100 Myr t < 1 Gyr Ginzburg et al. 2017 
 Rogers et al. 2021 Lammer et al. 2003 
 Baraffe et al. 2004 
 Owen & Wu, 2017
13. 7 Photoevaporation strongly relies on the high- energy (X-ray to UV) luminosity of the host star. t < 100 Myr Owen & Wu, 2017 · M = ηR3 p LHE 4a2GMcore
14. 8 Young planets live in highly irradiated environments compared to old planets. M stars G stars K stars The Sun Garcés, Catalán & Ribas, 2011 
 Lammer et al. 2003 
 Baraffe et al. 2004
15. 8 Young planets live in highly irradiated environments compared to old planets. M stars G stars K stars The Sun Garcés, Catalán & Ribas, 2011 
 Lammer et al. 2003 
 Baraffe et al. 2004
16. 9 NASA SDO 
 March 11, 2015 Flares are the radiation component to magnetic reconnection events.
17. 9 NASA SDO 
 March 11, 2015 Flares are the radiation component to magnetic reconnection events.
18. 10 What, if any, is the role of stellar flares in removing atmospheric mass for close-in giant planets? What do the atmospheres of young planets look like? And what can they tell us about planet formation?
19. 11 What, if any, is the role of stellar flares in removing atmospheric mass for close-in giant planets? What do the atmospheres of young planets look like? And what can they tell us about planet formation?
20. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 12 Constraining young flare rates in the optical/NIR
21. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 13 Constraining young flare rates in the optical/NIR Measuring fl are rates and energies of young stars to understand our priors
22. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 14 Constraining young flare rates in the optical/NIR Looking for evidence of extended primordial H/He envelopes
23. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 15 Constraining young flare rates in the optical/NIR Testing the performance of JWST
24. Stellar flares with TESS 16 01
25. 17 TESS is an all-sky satellite that observes nearly any given star for 27-351 days, depending on where the star is located. Image credit: Ethan Kruse
26. 18 Stellar flares have a characteristic shape in any given light curve. Walkowicz et al. 2011 
 Davenport et al. 2014
27. 19 Previous methods have relied on identifying flares based on how many sigma above the baseline the peak of the flare is. Chang, Byun, & Hartman, 2015
28. 19 Previous methods have relied on identifying flares based on how many sigma above the baseline the peak of the flare is. Chang, Byun, & Hartman, 2015
29. 19 Previous methods have relied on identifying flares based on how many sigma above the baseline the peak of the flare is. Chang, Byun, & Hartman, 2015
30. 19 Previous methods have relied on identifying flares based on how many sigma above the baseline the peak of the flare is. Chang, Byun, & Hartman, 2015 :(
31. 20 Young stellar light curves are much harder to identify flares on. Octans Columba
32. 20 Young stellar light curves are much harder to identify flares on. Octans Columba
33. Machine learning can solve all* problems. *some 21
34. 22 Neural networks can be trained to identify characteristic features in a data set. Walkowicz et al. 2011 
 Davenport et al. 2014 
 Pearson et al. 2017
35. 22 Neural networks can be trained to identify characteristic features in a data set. Walkowicz et al. 2011 
 Davenport et al. 2014 
 Pearson et al. 2017
36. 23 The neural network, stella, is used as a sliding box detector, and takes ~1s to run on any light curve. Feinstein et al. 2020a,b GitHub: afeinstein20/stella Normalized Flux Probability Probability
37. 23 The neural network, stella, is used as a sliding box detector, and takes ~1s to run on any light curve. Feinstein et al. 2020a,b GitHub: afeinstein20/stella Normalized Flux Probability Probability
38. 24 We selected a sample of ~3200 young stars observed at TESS 2-minute cadence in Sectors 1-19.
39. 25 The observations identified as flare events “light up” across the data. Feinstein et al. 2020a,b GitHub: afeinstein20/stella
40. 26 There is a clear flare rate dependence as a function of effective temperature. Cooler than 4000 K Hotter than 4000 K Feinstein et al. 2020b
41. 27 Flare energies and rates are higher for cool stars across all ages. Age ≤ 50 Myr Age > 50 Myr
42. 28 We find no dependence of where flares occur with respect to the rotational phase of the stars. Flare Amplitude < 5% Flare Amplitude ≥ 5%
43. 28 We find no dependence of where flares occur with respect to the rotational phase of the stars. Flare Amplitude < 5% Flare Amplitude ≥ 5%
44. 29 No phase-flare dependence places informs us that active regions are located on both hemispheres of these young stars. What we think we’re seeing:
45. 29 No phase-flare dependence places informs us that active regions are located on both hemispheres of these young stars. What we think we’re seeing:
46. 29 No phase-flare dependence places informs us that active regions are located on both hemispheres of these young stars. What we think we’re seeing: What a flare-phase relationship would’ve looked like:
47. 30 We applied the neural network to 200,000 stars observed with TESS from 
 2018 - 2020. Flare Rate [hour -1] 0 0.002 0.004 0.006 0.008 0.010 0.012 Feinstein et al. 2022a
48. 31 We find stars with larger convective regions exhibit more high-energy flares.
49. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). 01 Summary of Results 32 Constraining young flare rates in the optical/NIR Developed a new machine learning technique to identify stellar fl ares Identi fi ed a correlation between fl are rates and the effective temperature of the star Shown there is minimal evolution in fl are rate for cool stars as they age out to 800 Myr Measured a similar fl are frequency distribution for 200,000 stars observed in Years 1 & 2 of TESS
50. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 33 Constraining young flare rates in the optical/NIR
51. AU Mic in the Far Ultraviolet with Hubble 34 02
52. 35 AU Mic — 
 22 ± 3 Myr 
 3700 K 
 0.5 M☉; 0.75 R☉ AU Mic b — 
 4.2 Rp/R⨁ 8.463 day orbital period AU Mic c — 
 3.24 Rp/R⨁ 18.859 day orbital period Evolved circumstellar disk Turnbull et al. 2015 Plavchan et al. 2020 Martioli et al. 2021 Liu et al. 2009
53. 36 2 HST/COS visits to AU Mic PI: Wilson Cauley • Goal: Three transits of AU Mic b using the Cosmic Origins 
 Spectrograph (COS) • G130M grating from 1060-1360 Å, with masked Ly-ɑ • R ~ 12,000-17,000 • Ability to create high-resolution light curves using the COS 
 time-tag feature
54. 37 AU Mic has an incredibly rich FUV spectrum. Feinstein et al. 2022b
55. 38 The “white light” curve reveals a plethora of stellar flares. Feinstein et al. 2022b
56. 38 The “white light” curve reveals a plethora of stellar flares. Feinstein et al. 2022b
57. 39 Spectroscopic light curves can be used to probe flare properties as a function of atmospheric location. C III N V Si III C II Fe XXI Feinstein et al. 2022b
58. 40 Emission lines form at different temperature, tracing different regions of the stellar atmosphere. C III N V Si III C II Fe XXI Feinstein et al. 2022b
59. 40 Emission lines form at different temperature, tracing different regions of the stellar atmosphere. C III N V Si III C II Fe XXI Feinstein et al. 2022b Corona (T~105-8K) N V, Fe XXI Transition Zone (T~104-5K) Si II, C III Chromosphere (T~103-4K) C II
60. 41 The same flare observed from specific emission lines has different morphologies and absolute energies. Feinstein et al. 2022b * all light curves for Flare B CII
61. 42 The majority of the flare energy comes from the chromosphere & transition region. Feinstein et al. 2022b Flare B Flare D Flare J Flare K Flare M Normalized energy [%]
62. 43 Coronal mass ejections can be inferred from coronal dimming after a flare event.
63. 43 Coronal mass ejections can be inferred from coronal dimming after a flare event.
64. 43 Coronal mass ejections can be inferred from coronal dimming after a flare event.
65. 43 Coronal mass ejections can be inferred from coronal dimming after a flare event.
66. 43 Coronal mass ejections can be inferred from coronal dimming after a flare event.
67. 44 The effects of coronal mass ejections on exoplanet atmospheres has been thoroughly studied.
68. 44 The effects of coronal mass ejections on exoplanet atmospheres has been thoroughly studied. Destruction of ozone layer (Tilley et al. 2019)
69. 44 The effects of coronal mass ejections on exoplanet atmospheres has been thoroughly studied. Destruction of ozone layer (Tilley et al. 2019) Harmful atmospheric chemical processes (Yamashiki et al. 2019)
70. 44 The effects of coronal mass ejections on exoplanet atmospheres has been thoroughly studied. Destruction of ozone layer (Tilley et al. 2019) Compress planetary magnetosphere (Cohen et al. 2014) Harmful atmospheric chemical processes (Yamashiki et al. 2019)
71. 44 The effects of coronal mass ejections on exoplanet atmospheres has been thoroughly studied. Strip the atmosphere (Lammer et al. 2007) Destruction of ozone layer (Tilley et al. 2019) Compress planetary magnetosphere (Cohen et al. 2014) Harmful atmospheric chemical processes (Yamashiki et al. 2019)
72. 45 Veronig et al. 2021 A light curve of the Sun during a flare + CMA shows direct evidence of both events.
73. 46 We find no statistically significant evidence of an affiliated CME with Flare D. Feinstein et al. 2022b
74. 46 We find no statistically significant evidence of an affiliated CME with Flare D. Flare C pre-flare D post-flare D Flare D Feinstein et al. 2022b
75. 47 We can model the photoevaporative mass loss for AU Mic b using these newly identified flares as priors. · M = ηR3 p LHE 4a2GMcore Owen & Wu (2017)
76. 47 We can model the photoevaporative mass loss for AU Mic b using these newly identified flares as priors. · M = ηR3 p LHE 4a2GMcore X-ray - UV luminosity Owen & Wu (2017)
77. 48 We constructed the SED of AU Mic from the X-ray to the IR. PHOENIX Model XMM-Newton FUSE & HST/COS/STIS IUE HARPS-N Feinstein et al. 2022b
78. 49 Several masses have been measured for AU Mic b using radial velocities. · M = ηR3 p LHE 4a2GMcore Estimates from RVs?
79. 50 We evaluated how the mass-loss rate for AU Mic b would change without and with flares. Feinstein et al. 2022b
80. 51 The current models are consistent with upper limits on the mass-loss rate placed by observations. Hirano et al. 2020
81. 52 The presence of super flares (> 1033 erg/s) can increase instantaneous mass-loss rates by 6 orders of magnitude. Feinstein et al. 2022b
82. Summary of Results 53 AU Mic has an FUV fl are rate of 2.5 hour-1, compared to an optical fl are rate of 2 day-1. Through spectroscopic light curves, we traced the fl are morphology and energy as a function of line formation temperature. We fi nd no evidence of an af fi liated coronal mass ejection with Flare D. Instantaneous mass-loss rates for exoplanet atmospheres can increase by 6 orders of magnitude in the presence of super fl ares. Constraining flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 02
83. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 54 Constraining young flare rates in the optical/NIR
84. V1298 Tau c in the optical with Gemini-N 55 03
85. 56 V1298 Tau, a 30-40 Myr solar analogue with 4 transiting exoplanets. V1298 Tau b 
 9.53 Rp/R⨁ P = 24.14 days V1298 Tau d 
 6.13 Rp/R⨁ P = 12.36 days V1298 Tau e 
 9.94 Rp/R⨁ P > 42 days V1298 Tau c 
 5.05 Rp/R⨁ P = 8.24 days David et al. 2019 
 David et al. 2020 
 Feinstein et al. 2022c V1298 Tau 
 30-40Myr 
 1.33 R☉ 
 1.09 M☉
86. 57 V1298 Tau, a 30-40 Myr solar analogue with 4 transiting exoplanets. David et al. 2019 
 David et al. 2020 
 Feinstein et al. 2022c V1298 Tau c 
 5.05 Rp/R⨁ P = 8.24 days
87. 58 Excess absorption in Hɑ was seen throughout the transit observations of V1298 Tau c. Feinstein et al. 2021
88. 59 If you really squint, you could convince yourself there’s a transit + long term trend in Hɑ. 1.28 RJ
89. 60 8 months later, we saw the same trend in Hɑ. Coincidence? TBD! Schlawin, Ilyn, Feinstein et al. 2021
90. 61 The excess absorption in Hɑ can be modeled my stellar inhomogeneities. Feinstein et al. 2021
91. 61 The excess absorption in Hɑ can be modeled my stellar inhomogeneities. Feinstein et al. 2021
92. Next steps for young planetary atmospheres 62 FUV transits Low- resolution NIR High- resolution NIR Multi- wavelength Searching for escaping metal lines Chemical inventory and cloud properties Measuring the carbon- to-oxygen ratio of the atmosphere Long term monitoring of the host star GO 2149, 2498 
 Proposed for Cycle 2 (of course) 3 transits of AU Mic b (PI Cauley) 
 3 transits of V1298 Tau c 1 transit of HIP 67522b (PI Feinstein) 
 1 transit of DS Tuc Ab (PI Mansfield)
93. Summary of Results 63 We found very tentative evidence of an extended hydrogen envelope for the 23 Myr planet V1298 Tau c. The trend in H⍺ can be explained away by the presence of stellar inhomogeneities. The activity of the young host star is challenging and therefore many transits need to be observed to draw any de fi nite conclusions. Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). 03
94. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 64 Constraining young flare rates in the optical/NIR
95. 65 04 WASP-39b in the near-infrared with JWST
96. 66 WASP-39b 
 1.27 Rp / RJ 
 88 Mp / M⨁ 
 4.055 days An ideal target to test atmospheric characterization with JWST. WASP-39 
 5400 K 
 0.92 M☉ 
 1.01 R☉ Faedi et al. 2011
97. 67 Measuring the transit depth at different wavelengths can tell us what absorbers are in the planet’s atmosphere. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%]
98. 67 Measuring the transit depth at different wavelengths can tell us what absorbers are in the planet’s atmosphere. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%]
99. 67 Measuring the transit depth at different wavelengths can tell us what absorbers are in the planet’s atmosphere. 100.0 99.8 99.6 99.4 99.2 99.0 -0.10 -0.05 0.00 0.05 0.10 Time from Mid-Transit [days] Flux from Star [%]
100. 68 Using all 5 instruments aboard JWST, we now have a complete NIR view of WASP-39b.
101. 69 We clearly resolve multiple water bands along with potassium, which agrees with previous HST data. H2O H2O H2O H2O H2O K
102. 69 We clearly resolve multiple water bands along with potassium, which agrees with previous HST data. H2O H2O H2O H2O H2O K
103. 70 NIRISS is a challenging instrument given the shape and overlap of the spectral traces. Order 1 Order 2
104. 71 This was truly a huge community effort. Louis-Philippe Coulombe 
 Néstor Espinoza 
 Catriona Murray 
 Michael Radica 
 Zafar Rustamkulov 
 Arianna Saba 
 Angelos Tsiaras Feinstein et al. 2023
105. 72 We find WASP-39b has a sub-solar C/O and a metallicity of 
 10 - 30x solar. 0.2 Carbon-to-oxygen ratio (C/O) 0.55 0.70 0.80 1.38 Metallicity [M/H] 0.0 1.0 2.0 2.25 Feinstein et al. 2023
106. 73 While cloudy models generally fit the spectrum well, none of these pre- computed grids couldn’t fit the shallowed transit depth at λ > 2μm. Model Generation & Fitting: Kazumasa Ohno 2.25 2.20 2.15 2.10 2.05 2.25 2.20 2.15 2.10 2.05 Transit Depth [%] Wavelength [μm] 0.6 0.88 1.16 1.44 1.72 2.0 2.3 2.8 Feinstein et al. 2023
107. 73 While cloudy models generally fit the spectrum well, none of these pre- computed grids couldn’t fit the shallowed transit depth at λ > 2μm. Model Generation & Fitting: Kazumasa Ohno 2.25 2.20 2.15 2.10 2.05 2.25 2.20 2.15 2.10 2.05 Transit Depth [%] Wavelength [μm] 0.6 0.88 1.16 1.44 1.72 2.0 2.3 2.8 Feinstein et al. 2023
108. 74 By invoking inhomogeneous cloud coverage, the shallower transit depth at λ > 2μm could be fit better. ɸnon-grey ɸclear Model Generation & Fitting: Luis Welbanks Feinstein et al. 2023
109. 75 We resolve a potassium absorption feature at 0.77μm, which was hinted at with previous HST data. Feinstein et al. 2023
110. 75 We resolve a potassium absorption feature at 0.77μm, which was hinted at with previous HST data. [K/O] = -1.0 [K/O] = 0.0 [K/O] = 0.2 [K/O] = 0.4 [K/O] = 0.6 [K/O] = 0.8 [K/O] = 1.0 Feinstein et al. 2023
111. 75 We resolve a potassium absorption feature at 0.77μm, which was hinted at with previous HST data. [K/O] = -1.0 [K/O] = 0.0 [K/O] = 0.2 [K/O] = 0.4 [K/O] = 0.6 [K/O] = 0.8 [K/O] = 1.0 Feinstein et al. 2023
112. Summary of Results 76 We resolved 5 broad water absorption features and the potassium doublet at 0.77μm in the atmosphere of WASP-39b with JWST/NIRISS. We fi nd an atmospheric composition consistent with sub-solar carbon-to- oxygen ratio and 10-30x solar metallicity. We fi nd λ > 2μm can be fi t with a model incorporating inhomogeneous cloud coverage long the terminator. We fi nd a solar-to-super-solar K/O ratio. Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 04
113. Feinstein, Montet, Ansdell et al. AJ, 160, 5 (2020). Feinstein, Montet, & Ansdell, JOSS, 5, 2347 (2020). Feinstein, Seligman, Günther, & Adams, ApJL, 925, L9 (2022). Measuring flare rates and energies in the FUV Feinstein, France, Youngblood et al. AJ, 164, 110 (2022). 01 02 Young atmospheric properties in the optical Feinstein, Montet, Johnson et al. AJ, 162, 213 (2021). Atmospheric characterization in the NIR with JWST Feinstein, Radica, Welbanks et al. Nature, 614, 670–675 (2023). 03 04 Outline 77 Constraining young flare rates in the optical/NIR
114. 78 Stellar flares could play a critical role in atmospheric removal at young ages. 
 Transmission spectroscopy for young planets is challenging, but necessary, to understand the early stages of planet evolution.
115. 79 Stellar flares could play a critical role in atmospheric removal at young ages. 
 Transmission spectroscopy for young planets is challenging, but necessary, to understand the early stages of planet evolution.
116. Acknowledgements • Jacob Bean & the Bean team (past and present) • My committee — Hsiao-Wen Chen, Fred Ciesla, Ben Montet, Brian Nord • Family — Mom, Dad, Adam, Jeremy, Tali, Laurel, Aunt Thalia, Aunt Susan, Uncle Marty, Gaby, Yoni, Lindsay • Incredible support system & Friends — Fred Adams, Eva-Maria Ahrer, Lili Alderson, Megan Andsell, Megan Barnett, Jenny Bergner, Elyssa Brooks, Fausto Cattaneo, Chihway Chang, Celeste Keith, Megan Mansfield, Leslie Rogers, Zafar Rustamkulov, Darryl Seligman • Wonderful co-authors — Trevor David, Dan Foreman-Mackey, Kevin France, Michael Gully-Santiago, Max Günther, Marshall Johnson, John Livingston, Rodrigo Luger, Kazumasa Ohno, Michael Radica, Luis Welbanks, Allison Youngblood • Past Mentors — Phil Arras, Jonathan Lunine, Danilo Marchesini, Joshua Schlieder • Cats — Rex & Slinky 80