# Mixed Modes in Theory and Practice

AMNH Astronomy Seminar

September 28 2021 | Slides at http://hyad.es/talks

# I. Background

Animation: NASA

Power spectra of MDI dopplergrams

Data: $y_\text{obs} \in Y$

Models: $x_i \in X$;$F: X \to Y$

Best-fitting model: $x = \mathop{\mathrm{argmax}}_{x_j \in X}\ \mathcal{L}\left(x_j\right)$

$F: \underbrace{\left(M, t, Y_0, Z_0, \alpha_\text{mlt}, \ldots\right)}_{x \in X} \mapsto \underbrace{\left(L, T_\text{eff}, [\text{M/H}], \log g, \ldots\right)}_{y \in Y}$

$\color{red} \text{and } \Delta\nu, \nu_{\text{max}}, \left\{\nu_{n,l}\right\}$

## The Forward Problem: Global Parameter Estimation

16 Cyg B: from Ong, Basu, McKeever (2021)

Precise measurements of field stars: ${\sigma_R \over R} \lesssim 2 \%; {\sigma_M \over M} \lesssim 5 \%$

## Mixed Modes

Pure p-modes: $\nu_{n,l} \sim \Delta\nu \left(n + {l \over 2} + \epsilon_{n,l}\right)$

Pure g-modes: ${1 \over \nu_{n,l}} \sim \Delta\Pi_l \left(n + \epsilon_{n,l}\right)$

Mixed modes exhibit avoided crossings
between underlying p- and g-modes.

# II. Understanding Mixed Modes

(Coupling between oscillators)

Relationship between $(\omega_i, \alpha_i)$ and stellar structure unclear…

${k_r^2 \sim {\omega^2 \over c_s^2} \left(1 - {{\color{blue} S_l}^2 \over \omega^2}\right)\left(1 - {{\color{orange}N}^2 \over \omega^2}\right)}$

$\small\color{orange}N^2 = {- g}\left.{\partial \log \rho \over \partial s}\right|_P{\mathrm d s \over \mathrm d r}$

$\small\color{blue}S_l^2 = {l(l+1) c_s^2 \over r^2}$

${\color{gray} \omega_p > S_l, N}$

${\color{red} \omega_g < N, S_l}$

${k_r^2 \sim {\omega^2 \over c_s^2} \left(1 - {{\color{blue} S_l}^2 \over \omega^2}\right)\left(1 - {{\color{orange}N}^2 \over \omega^2}\right)}$

$\tiny {\psi(r) \sim {1 \over \sqrt{k_r}}} \left(A \sin \left[\int^r k_r\ \mathrm d r\right] + B \cos \left[\int^r k_r\ \mathrm d r\right]\right)$

## LCAOs give Molecular Orbitals

$\Large \hat H \psi_n = \left(\hat T + \hat V\right)\psi_n = E_n \psi_n$

$\large {\color{blue}{\hat H_1}} \psi_n = \left(\hat T + \hat V_1\right)\psi_n = {\color{blue}E_n \psi_n}$

$\large {\color{orange}{\hat H_2}} \psi_n = \left(\hat T + \hat V_2\right)\psi_n = {\color{orange}E_n \psi_n}$

$\huge \hat H = \hat T + \hat V_1 + \hat V_2 = {\color{blue}{\hat H_1}} + \hat V_2 = \hat V_1 + {\color{orange}{\hat H_2}}$

$\Large\psi \sim {1 \over \sqrt{2}} \left({\color{blue}\psi_1} + {\color{orange}\psi_2}\right)$ $\Large E \sim E_1 - \left|\int {\color{blue}\psi_1^*} \hat H {\color{orange}\psi_2}\ \mathrm dV\right|$

$\Large\psi \sim {1 \over \sqrt{2}} \left({\color{blue}\psi_1} - {\color{orange}\psi_2}\right)$ $\Large E \sim E_1 + \left|\int {\color{blue}\psi_1^*} \hat H {\color{orange}\psi_2}\ \mathrm dV\right|$

## Energies and Mixing Coefficients of Molecular Orbitals

$\psi_\text{mol} = {\color{blue}\sum_i c_{1,i} \psi_{1,i}} + {\color{orange}\sum_j c_{2,j} \psi_{2,j}}.$

Energy eigenvalues and mixing coefficients are solutions to the
Generalised Hermitian Eigenvalue Problem

$\mathbf{H} \begin{bmatrix} {\color{blue}\mathbf{c}_1} \\ {\color{orange}\mathbf{c}_2} \end{bmatrix} = E \cdot \mathbf{D} \begin{bmatrix} {\color{blue}\mathbf{c}_1} \\ {\color{orange}\mathbf{c}_2} \end{bmatrix}$ $\small H_{{\color{blue}i}{\color{orange}j}} = \langle {\color{blue}\psi_i}|\hat{H}|{\color{orange}\psi_j}\rangle;~~~~D_{{\color{blue}i}{\color{orange}j}} = \langle {\color{blue}\psi_i}|{\color{orange}\psi_j}\rangle$

$\Large \hat{\mathcal{L}} \xi_n = -\omega_n^2 \xi_n$

$\Large \hat{\mathcal{L}} = {\color{red}\hat{\mathcal{L}}_\gamma} + \hat{\mathcal{R}}_\gamma$

$\Large {\color{red}\hat{\mathcal{L}}_\gamma \xi_{\gamma,n} = -\omega^2_{\gamma,n}\xi_{\gamma,n}}$

$\Large \hat{\mathcal{L}} = \hat{\mathcal{R}}_\pi + {\color{grey}\hat{\mathcal{L}}_\pi}$

$\Large {\color{grey}\hat{\mathcal{L}}_\pi \xi_{\pi,n} = -\omega^2_{\pi,n}\xi_{\pi,n}}$

$\Large \hat{\mathcal{L}} = {\color{grey}\hat{\mathcal{L}}_\pi} + \hat{\mathcal{R}}_\pi = \hat{\mathcal{R}}_\gamma + {\color{red}\hat{\mathcal{L}}_\gamma}$

$\Large \xi_\text{mixed} \sim {\color{grey}c_\pi \xi_\pi} + {\color{red}c_\gamma \xi_\gamma}$

## Mixed Modes as Acoustic “Molecular Orbitals”

$\xi_\text{mixed} \sim {\color{grey} \sum_i c_{\pi, i} \xi_{\pi,i}} + {\color{red} \sum_j c_{\gamma, j} \xi_{\gamma,j}}$ Mixed mode frequencies and mixing coefficients can likewise be found by solving the
Generalised Hermitian Eigenvalue Problem:
$\begin{bmatrix} {\color{grey}\mathbf{L}_{\pi\pi}} & \mathbf{L}_{\pi\gamma} \\ \mathbf{L}_{\pi\gamma}^T & {\color{red}\mathbf{L}_{\gamma\gamma}} \end{bmatrix} \begin{bmatrix} {\color{grey}\mathbf{c}_\pi} \\ {\color{red}\mathbf{c}_\gamma} \end{bmatrix} = -\omega^2 \begin{bmatrix} \mathbb{1} & \mathbf{D} \\ \mathbf{D}^T & \mathbb{1} \end{bmatrix} \begin{bmatrix} {\color{grey}\mathbf{c}_\pi} \\ {\color{red}\mathbf{c}_\gamma} \end{bmatrix}.$ $\small L_{{\color{grey}i}{\color{red}j}} = \langle {\color{grey}\xi_i}, \hat{\mathcal{L}}{\color{red}\xi_j}\rangle;~~~~D_{{\color{grey}i}{\color{red}j}} = \langle {\color{grey}\xi_i}, {\color{red}\xi_j}\rangle$

(Ong & Basu 2020; now also in GYRE v6)

Explicit numerical evaluation of isolated $\pi$ and $\gamma$-mode
frequencies and coupling strengths!

# III. The Surface Term

For the Sun, even standard solar models don’t give the right frequencies!

The asteroseismic “surface term”

## The Surface Term as a Structural Perturbation

Consider two stars with identical $M$ and $R$,
differing only in the near surface layers: $\hat{\mathcal{L}}_0\xi_{0,n} = -\omega_{0,n}^2 \xi_{0,n};~~~~\hat{\mathcal{L}}\xi_{n} = -\omega_{n}^2 \xi_{n}.$ We write $\hat{\mathcal{L}} = \hat{\mathcal{L}}_0 + \lambda {\hat{\mathcal{V}}},$ so that $\lambda$ interpolates linearly between the two structures.

## The Surface Term as a Matrix Perturbation

From operator perturbation problem, $\hat{\mathcal{L}} = \hat{\mathcal{L}}_0 + \lambda {\hat{\mathcal{V}}},$ construct corresponding matrix perturbation problem by evaluating $V_{ij} = \int \rho\ \vec{\xi}_{\pi,i} \cdot \hat{\mathcal{V}}\vec{\xi}_{\pi,j}\ \mathrm d^3 x.$

$\text{Perturbation theory: }\delta\omega_i^2 \sim \lambda V_{ii} + \mathcal{O}(\lambda^2)$

$\Large \hat{\mathcal{V}}{\color{red}\xi_\gamma} \to 0$

${\color{red}\gamma\text{-modes}}$ are confined to the stellar interior,
so unaffected by surface term

## Surface Term Corrections and Mixed Modes

The surface term acts on the bare ${\color{grey}\pi\text{-mode}}$ system, but is measured by the effect this has on mixed modes.

1. All surface term corrections in the literature work backwards from mixed-mode frequencies, from assumed perturbations on ${\color{grey}\pi\text{-modes}}$: $\small\delta\nu_{\pi, \text{surf}} \sim f(\nu_{nl}) / I_\pi\left(\nu_{nl}\right) \iff \delta\nu_{\text{surf}} \sim f(\nu_{nl}) / I_{nl} \equiv \delta\nu_{\pi,\text{surf}} {I_{\pi,nl}\over I_{nl}}$
2. Should perturb the bare ${\color{grey}\pi\text{-mode}}$ system, and then solve for the perturbed eigenvalues.

## Order of Operations matters!

These two operations do not necessarily commute.

Subgiant: $\Delta\nu = 67.5\ \mu\text{Hz}$
Full matrix coupling

Subgiant: $\Delta\nu = 67.5\ \mu\text{Hz}$

Subgiant: $\Delta\nu = 67.5\ \mu\text{Hz}$

Young red giant: $\Delta\nu = 17.2\ \mu\text{Hz}$

Evolved red giant: $\Delta\nu = 3.9\ \mu\text{Hz}$

(Ong, Basu, Roxburgh 2021)

perturbative series diverges

???

Ignore mixing altogether? (a la Ball et al. 2018)

## First-order vs. Full Mode Coupling

First-order approximation yields
systematically lower stellar masses!
(population-level systematic error)

(two different
correction techniques)

## Single-target Systematics

Joint posterior distributions for TOI 197
(reference values: Huber+ 2019)

(Ong+ 2021c)

## Mixed Modes and the Surface Term

Analysis of mixed modes in terms of the decoupled $\pi$- and $\gamma$-mode basis is necessary to avoid systematic errors in determining
global properties from asteroseismology,
for both single-target measurements and population statistics.

# IV. Rotation

## Spherical Harmonics

Three quantum numbers $n, l, m$: \begin{aligned} l &= 0, 1, 2, \ldots \\ m &= -l, -l+1, \ldots, l-1, l \end{aligned}

Zonal ($m = 0$)

($m = +l$)

($m = -l$)

## Rotational Splitting

For slow rotators ($\Omega \ll 2\pi\Delta\nu$),

$\boxed{\delta\omega_{nlm} \sim m \beta_{nl} \int \Omega(r) K_{nl}(r) \mathrm d r}$

($\equiv m \Omega \beta_{nl}$ for solid-body rotation).

$\beta_i(r) = \beta_i \int_0^r K_i(r') \mathrm d r'$

Sensitivity of pure p-modes is distributed
throughout entire stellar structure
(but concentrated at surface)

$\beta_i(r) = \beta_i \int_0^r K_i(r') \mathrm d r'$

Mixed modes probe radial differential rotation:
many implications for stellar astrophysics

Zonal + $\text{\color{orange}prograde}$ and $\text{\color{blue}retrograde}$ sectoral
$\pi$-modes and $\gamma$-modes

$\text{Asymmetry: }\psi = {(\nu_+ - \nu_0) - (\nu_0 - \nu_-) \over \nu_+ - \nu_-} = 0$

Dipole modes ($l = 1$)

$\Delta\nu = 17\ \mu$Hz; $\Omega_\text{core}/\Omega_\text{surf} = 10$

Quadrupole modes ($l = 2$)

Dipole modes ($l = 1$)

$\Delta\nu = 5\ \mu$Hz; $\Omega_\text{core}/\Omega_\text{surf} = 10$

Buried B-field: $\psi = 0.28$
(from Bugnet+ 2021)

## Mixed Modes and Rotation

Avoided crossings must be accounted for
to make credible statements about stellar rotation
and magnetic fields in evolved stars.

# V. Works In Progress

## Subgiants Dominate the TESS ATL

$T_\text{eff}$

$R/R_\odot$

e.g. Measuring $Y_0$ from the TESS CVZs

## Automated mode identification with coupling matrices Generative modelling of coupling matrices for automated ID of dipole mixed modes (Nielsen et al., in prep.)

## The Future

$\beta_i(r) = \beta_i \int_0^r K_i(r') \mathrm d r'$

Even the most p-dominated mixed modes
are sensitive to core rotation!

Rotational kernel for p-dominated mixed mode

\small \begin{aligned} \delta\omega_i = m \beta_i \int_0^R \Omega(r) K_i(r) \mathrm d r &\sim \sum_j A_{ij} \Omega_j \\ \implies \Omega_j &\sim \sum_i A^{+}_{ji} \delta\omega_i? \end{aligned}

# Summary

## Decoupling of Mixed Modes:

Decomposition of wave operator into purely acoustic/buoyant propagation terms and their remainder operators
permits closed-form evaluation of coupling matrix elements.

Ong and Basu (2020)

## Mixed Modes and the Surface Term:

Traditional surface term corrections handle mode coupling
only to first order, if at all.

More sophisticated techniques are required for evolved stars,
to avoid systematic errors in global properties.

Ong, Basu, Roxburgh (2021); Ong, Basu, Lund, Viani, Bieryla, Latham (2021)

## Mixed Modes and Rotation:

asymmetric rotational splitting on mixed modes.

Symmetrisation in $\pi/\gamma$ basis is mandatory
for accurate interpretation of observed splitting
(e.g. correct diagnosis of magnetic fields).

Ong & Basu (in prep.)

## Summary

We analytically decouple mixed modes into $\pi$- and $\gamma$-like components. This permits the analysis and interpretation of both the surface term, as well as of rotational splitting, in evolved stars.

$\mathrm{j}\mathrm{o}\mathrm{e}\mathrm{l}.\mathrm{o}\mathrm{n}\mathrm{g}\ \text{@}\ \text{yale}.\text{edu}$

# Backup Slides I: Surface Corrections (see Basu+ 2018, Jørgensen+ 2020 for review)

## (Fully) calibrated corrections

$\nu_\text{model} \mapsto \nu_\text{corr} = \nu_\text{model} + \delta\nu_{nl,\text{surf}},$ with corrections depending only on the model as $\delta\nu_{nl,\text{surf}} \sim f(\nu_{nl}; x)$.

## Parametric corrections

Corrections with free parameters $\theta \in \Theta$ as $\delta\nu_{nl,\text{surf}} \sim f(\nu_{nl}; x; \theta)$.

$\tiny {\text{e.g. Ball \& Gizon (2014) correction: }\delta\nu_{nl,\text{surf}} \sim \left(a_{-1} \left(\nu_{nl}\right)^{-1} + a_{3} \left(\nu_{nl}\right)^{3}\right) / I_{nl}}$

## Alternative Approach I: Separation Ratios

\begin{aligned} \text{e.g. } r_{02, n} = {\nu_{n,0} - \nu_{n-1,2} \over \nu_{n,1} - \nu_{n-1,1}} \end{aligned}

Interpretation as surface-independent functions of frequency:
use these to constrain model directly (Otí Floranes et al. 2005)

\begin{aligned} r_{02, n} & \sim \delta_2(\nu_{n,0})\\ r_{01, n} \sim \delta_1(\nu_{n,0})&; ~~~ r_{10, n} \sim \delta_1(\nu_{n,1}) \end{aligned}

## Alternative Approach II: $\epsilon$-matching

$\nu_{nl} \sim \Delta\nu\left(n + {l \over 2} + \epsilon_{nl}\right), \implies \epsilon_{nl} = {\nu_{nl} \over \Delta\nu} - n - {l \over 2} \equiv{\epsilon_l(\nu_{nl})}$ $\text{Compute } \mathcal{E}_l(\nu^\text{obs}_{nl}) = \epsilon^\text{obs}_{l}(\nu^\text{obs}_{nl}) - \epsilon^\text{model}_{l}(\nu^\text{obs}_{nl}).$

All of the $\mathcal{E}_l$ should collapse to a single function if the structural differences are localised to the surface (Roxburgh 2016).

## Nonparametric Treatments

Use of transformed variables such that $O_{nl,\text{surf}} \sim f(\nu_{nl})$

(where the structure of $f$ is left underspecified)

Interpolation required to compare
$f^\text{obs}(\nu_\text{obs})$ vs. $f^\text{model}(\nu_\text{obs})$ (instead of $f^\text{model}(\nu_\text{model})$).

# Backup Slides II: Comparing Surface Corrections

## Differences between surface corrections

For each parameter $P$, we consider normalised differences $z_{P, \text{BG14 vs. other}} = {\mu_{P, \text{other}} - \mu_{P, \text{BG14}} \over \sqrt{\sigma^2_{P, \text{BG14}} + \sigma^2_{P, \text{other}}}}$

We examine the distribution of these differences
over a large* sample of stars, ceteris paribus

*Not actually very large

## I.

Main-sequence stars

$\tiny{(\text{Kepler LEGACY sample}: N = 66)}$

General agreement on the
inferred masses…

$z$-score for mass

$z$-score for radius

Parameter estimates generally
agree quite robustly…

$z$-score for age

… but not for all parameters.

$z$-score for initial helium abundance

## II.

First-ascent red giants

$\tiny{(\text{NGC 6791}: N = 29; l=0,2\text{ only})}$

Nonparametric methods appear
to agree with each other…

$z$-score for initial helium abundance

…but not with our
fiducial parameterisation…

$z$-score for mass

…and these offsets appear
to be systematic.

$z$-score for age

## What’s going on?

NGC 6791 is an open cluster — what about the
actual distribution of stellar properties?

Stars should be coeval, so red giants should be of similar mass and age.

Disagreements on the age scale?

Disagreements on the mass distribution?

Other parametric methods yield comparable internal scatter!

Different treatments of the surface term exhibit qualitative systematic differences for main-sequence stars vs. red giants.

What happens in between?

# Backup Slides IV: Generalising Classical Parameterisations

## The Surface Term as a Matrix Perturbation

From operator perturbation problem, $\hat{\mathcal{L}} = \hat{\mathcal{L}}_0 + \lambda {\hat{\mathcal{V}}},$ construct corresponding matrix perturbation problem by evaluating $V_{ij} = \int \rho\ \vec{\xi}_{\pi,i} \cdot \hat{\mathcal{V}}\vec{\xi}_{\pi,j}\ \mathrm d^3 x.$

$\text{Variational" expression: }\delta\omega_i^2 \sim {\int \rho\ \vec \xi_i\ \delta\hat{\mathcal{L}} (\vec \xi_i)\ \mathrm d^3 x \over \int \rho\ |\vec \xi_i|^2\ \mathrm d^3 x}$

## Matrix Parametrisations for the Surface Term

So long as the off-diagonal entries of the matrix $\mathbf{V}$ can be specified, existing parametrisations can adapted as (e.g. for BG14): $\large \begin{bmatrix} {\color{grey}\mathbf{L}_{\pi\pi}} + \mathbf{V}_{(a_{-1}, a_{3})} & \mathbf{L}_{\pi\gamma} \\ \mathbf{L}_{\pi\gamma}^T & {\color{red}\mathbf{L}_{\gamma\gamma}} \end{bmatrix} \begin{bmatrix} {\color{grey}\mathbf{c}_\pi} \\ {\color{red}\mathbf{c}_\gamma} \end{bmatrix} = -\omega^2 \begin{bmatrix} \mathbb{1} & \mathbf{D} \\ \mathbf{D}^T & \mathbb{1} \end{bmatrix} \begin{bmatrix} {\color{grey}\mathbf{c}_\pi} \\ {\color{red}\mathbf{c}_\gamma} \end{bmatrix}.$