In-Class Assignment 9#
Exploring Brown Dwarfs & Planets with MESA#
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
Download the following model files locally.
\(0.03 M_\odot/1 R_{\rm{Jup}}\): 0.03Msun_1RJup_history.data; 0.03Msun_1RJup_profile.data;
\(0.97 M_\rm{Jup}/ 2 R_{\rm{Jup}}\): planet_1.0_MJ_10.0_ME_2.0_RJ_0_irr_flux.data; planet_1.0_MJ_10.0_ME_2.0_RJ_1e6_irr_flux.data; planet_1.0_MJ_10.0_ME_2.0_RJ_1e8_irr_flux.data;
Brown Dwarf#
Using the 0.03\(M_\odot\) model MESA profile:
a.#
Compare the opacity
profile with the approximate opacity due to \(\rm{H}^{-}\) from HKT 4.65.
## a results here
b.#
Using the dominant nuclear energy generation rate (\(\epsilon\)), luminosity and other necessary variables, compute the estimate lifetime from HKT eq. 1.89. Consider plotting \(^{2}\)H as a function of time, how far through the stars lifetime is this model?
## b results here
Planet#
Using the \(0.97 M_\rm{Jup}/ 2 R_{\rm{Jup}}\) model MESA history data:
Each of these models uses a set value of irradiation flux of 0, \(1\times10^{6}\), or \(1\times10^{8}\) (\(\rm{erg \ cm^{2} \ s^{-1}}\)) at a fixed column density of 300 (\(\rm{cm^{2} \ g^{-1}}\))
c.#
Plot the pressure vs radius for all 3 models. Which model has the largest radius? Why?
## c results here
d.#
Shallower atmospheric \(T\)-gradient leads to slower interior cooling, and larger radius at a given age.
Plot the pressure vs temperature (x-axis) profiles for all 3 models. Which model has the flattest \(T-\)gradient?
## d results here