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 [%]
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 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
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
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
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
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
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
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
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
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
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
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 :(
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
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
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:
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
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
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
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
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)
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
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 [%]
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)
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
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
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)
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
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
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 [%]
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 [%]
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 [%]
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
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
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
• 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
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