petitRADTRANS.temperature_profiles ================================== .. py:module:: petitRADTRANS.temperature_profiles Submodules ---------- .. toctree:: :maxdepth: 1 /autoapi/petitRADTRANS/temperature_profiles/gradient/index /autoapi/petitRADTRANS/temperature_profiles/guillot/index /autoapi/petitRADTRANS/temperature_profiles/isothermal/index /autoapi/petitRADTRANS/temperature_profiles/madhusudhan/index /autoapi/petitRADTRANS/temperature_profiles/molliere/index /autoapi/petitRADTRANS/temperature_profiles/power_law/index /autoapi/petitRADTRANS/temperature_profiles/spline/index Functions --------- .. autoapisummary:: petitRADTRANS.temperature_profiles.zhang_2023_temperature_profile petitRADTRANS.temperature_profiles.guillot_temperature_profile petitRADTRANS.temperature_profiles.guillot_dayside_temperature_profile petitRADTRANS.temperature_profiles.guillot_global_temperature_profile petitRADTRANS.temperature_profiles.guillot_global_ret_temperature_profile petitRADTRANS.temperature_profiles.guillot_metallic_temperature_profile petitRADTRANS.temperature_profiles.guillot_modif_temperature_profile petitRADTRANS.temperature_profiles.isothermal_temperature_profile petitRADTRANS.temperature_profiles.madhusudhan_seager_temperature_profile petitRADTRANS.temperature_profiles.molliere_2020_temperature_profile petitRADTRANS.temperature_profiles.power_law_temperature_profile petitRADTRANS.temperature_profiles.linear_spline_temperature_profile petitRADTRANS.temperature_profiles.cubic_spline_temperature_profile Package Contents ---------------- .. py:function:: zhang_2023_temperature_profile(pressures: jax.typing.ArrayLike, num_layer: int, layer_pt_slopes: jax.typing.ArrayLike, t_bottom: float, top_of_atmosphere_pressure: float = -3, bottom_of_atmosphere_pressure: float = 3) -> jax.Array This function takes the temperature gradient at a set number of spline points and interpolates a temperature profile as a function of pressure. Based on the method described in Zhang et al. (2023). Args: pressures: The pressure array in bar. num_layer: The number of layers. Default for covering 10^3 to 10^-3 bar as in Zhang 2023 is 6. To cover 10^3 to 10^-6 bar 10 is recommended. layer_pt_slopes: The temperature gradient (d(ln T) / d(ln P)) at the spline points. t_bottom: The temperature at the bottom of the atmosphere. top_of_atmosphere_pressure: Minimum atmospheric pressure in log bar. If the pressure array extends beyond this value, the temperature structure at lower pressures will be isothermal. bottom_of_atmosphere_pressure: Maximum atmospheric pressure in log bar. Returns: The temperature profile in K. .. py:function:: guillot_temperature_profile(pressures: jax.typing.ArrayLike, infrared_mean_opacity: float, gamma: float, gravities: jax.typing.ArrayLike, intrinsic_temperature: float, equilibrium_temperature: float, redistribution_coefficient: float = 0.25) -> jax.Array Returns a temperature array, in units of K, of the same dimensions as the pressure P (in bar). For this the temperature model of Guillot (2010) is used (his Equation 29). Source: https://doi.org/10.1051/0004-6361/200913396 Args: pressures: Array of pressures in bar. infrared_mean_opacity: The infrared mean opacity in units of cm^2/g. gamma: The ratio between the visual and infrared mean opacities. gravities: The planetary gravity at the given pressures in units of cm/s^2. intrinsic_temperature: The planetary intrinsic temperature in K. equilibrium_temperature: The planetary equilibrium temperature in K. redistribution_coefficient: The redistribution coefficient of the irradiance. A value of 1 corresponds to the substellar point, 1/2 for the day-side average and 1/4 for the global average. Returns: The temperature profile in K. .. py:function:: guillot_dayside_temperature_profile(pressures: jax.typing.ArrayLike, infrared_mean_opacity: float, gamma: float, gravities: jax.typing.ArrayLike, intrinsic_temperature: float, equilibrium_temperature: float) -> jax.Array Returns a dayside temperature array, in units of K, using the Guillot (2010) model. This is a wrapper for `guillot_temperature_profile` with `redistribution_coefficient` set to 0.5, which corresponds to an average over the day side of the planet. Args: pressures: Array of pressures in bar. infrared_mean_opacity: The infrared mean opacity in units of cm^2/g. gamma: The ratio between the visual and infrared mean opacities. gravities: The planetary gravity at the given pressures in units of cm/s^2. intrinsic_temperature: The planetary intrinsic temperature in K. equilibrium_temperature: The planetary equilibrium temperature in K. Returns: The temperature profile in K. .. py:function:: guillot_global_temperature_profile(pressures: jax.typing.ArrayLike, infrared_mean_opacity: float, gamma: float, gravities: jax.typing.ArrayLike, intrinsic_temperature: float, equilibrium_temperature: float) -> jax.Array Returns a global average temperature array, in units of K, using the Guillot (2010) model. This is a wrapper for `guillot_temperature_profile` with `redistribution_coefficient` set to 0.25, which corresponds to an average over the whole planetary surface. Args: pressures: Array of pressures in bar. infrared_mean_opacity: The infrared mean opacity in units of cm^2/g. gamma: The ratio between the visual and infrared mean opacities. gravities: The planetary gravity at the given pressures in units of cm/s^2. intrinsic_temperature: The planetary intrinsic temperature in K. equilibrium_temperature: The planetary equilibrium temperature in K. Returns: The temperature profile in K. .. py:function:: guillot_global_ret_temperature_profile(pressures: jax.typing.ArrayLike, delta: float, gamma: float, intrinsic_temperature: float, equilibrium_temperature: float) -> jax.Array Global Guillot P-T formula for retrievals, with kappa/gravity replaced by delta. This function is a variation of the Guillot (2010) temperature profile, where the ratio of the mean infrared opacity to gravity (kappa/g) is replaced by a single parameter, delta. This is useful for retrieval applications where gravity is fixed and opacity is a parameter. Args: pressures: Array of pressures in bar. delta: Proportionality factor for optical depth, equal to kappa_ir / g, where kappa_ir is the infrared mean opacity (cm^2/g) and g is the gravity (cm/s^2). gamma: The ratio between the visual and infrared mean opacities. intrinsic_temperature: The planetary intrinsic temperature in K. equilibrium_temperature: The planetary equilibrium temperature in K. Returns: The temperature profile in K. .. py:function:: guillot_metallic_temperature_profile(pressures: jax.typing.ArrayLike, gamma: float, reference_gravity: jax.typing.ArrayLike, intrinsic_temperature: float, equilibrium_temperature: float, infrared_mean_opacity_solar_metallicity: float, metallicity: Optional[float] = None) -> jax.Array Get a Guillot temperature profile depending on metallicity. This function calculates a global average Guillot temperature profile, where the infrared mean opacity is scaled with metallicity. Args: pressures: Array of pressures in bar. gamma: Ratio between visual and infrared opacity. reference_gravity: Surface gravity in cm/s^2. intrinsic_temperature: Intrinsic temperature in K. equilibrium_temperature: Equilibrium temperature in K. infrared_mean_opacity_solar_metallicity: Infrared mean opacity for a solar metallicity (Z=1) atmosphere, in cm^2/g. metallicity: Ratio of heavy elements abundance over H abundance with respect to the solar ratio. If None, solar metallicity is assumed. Returns: The temperature profile in K. .. py:function:: guillot_modif_temperature_profile(pressures: jax.typing.ArrayLike, delta: float, gamma: float, intrinsic_temperature: float, equilibrium_temperature: float, ptrans: float, alpha: float) -> jax.Array Modified Guillot P-T formula for retrievals. This function uses the `guillot_global_ret_temperature_profile` and applies a modifying factor to the temperature profile. The modification is controlled by `alpha` and `ptrans`, which can shape the profile around a transition pressure. Args: pressures: Array of pressures in bar. delta: Proportionality factor for optical depth, equal to kappa_ir / g. gamma: The ratio between the visual and infrared mean opacities. intrinsic_temperature: The planetary intrinsic temperature in K. equilibrium_temperature: The planetary equilibrium temperature in K. ptrans: Transition pressure in bar, where the modification is centered. alpha: A parameter controlling the strength and shape of the temperature modification. Returns: The modified temperature profile in K. .. py:function:: isothermal_temperature_profile(pressures: jax.typing.ArrayLike, temperature: float) -> jax.Array Returns an isothermal temperature profile. Args: pressures: An array of pressures. The shape is preserved for the output temperatures. temperature: The constant temperature value for the profile. Returns: An array of temperatures with the same shape as `pressures`, all set to the input `temperature`. .. py:function:: madhusudhan_seager_temperature_profile(pressures: jax.typing.ArrayLike, log_pressure_points: tuple[float], temperature_reference: float, alpha_points: tuple[float], beta_points: tuple[float]) -> jax.Array Calculate temperatures based on the Madhusudhan and Seager (2009) parameterization. This function computes temperatures using the Madhu and Seager (2009) parameterization for a given set of pressure values, pressure breakpoints, temperature breakpoints, alpha values, and beta values. Based off of the POSEIDON implementation: https://github.com/MartianColonist/POSEIDON/blob/main/POSEIDON/atmosphere.py Parameters: pressures : (numpy.ndarray) An array of pressure values (in bar) at which to calculate temperatures. log_pressure_points : (list) A list of log10 pressure breakpoints defining different temperature regimes. The zeroth element is the minimum pressure, should be log10(press[0]). The first element is the 1-2 boundary The second element is the level of the inversion The third element is the 2-3 boundary. The fourth element is the pressure at which the temperature is set (P_set). temperature_reference : (float) A temperature at log_pressure_points[4] used to constrain the temperature profile. alpha_points : (list) A list of alpha values used in the parameterization for different regimes. Must have length 2. beta_points : (list) A list of beta values used in the parameterization for different regimes. By default, b[0] == b[1] == 0.5, unclear how well this will work if these aren't used! Must have length 2. Returns: temperatures : (numpy.ndarray) An array of calculated temperatures (in K) corresponding to the input pressure values. Reference: - Madhusudhan, N., & Seager, S. (2009). A Temperature and Abundance Retrieval Method for Exoplanet Atmospheres. The Astrophysical Journal, 707(1), 24-39. https://doi.org/10.1088/0004-637X/707/1/24 .. py:function:: molliere_2020_temperature_profile(temperature_nodes, delta, alpha, t_internal, pressures, metallicity, co_ratio, conv) Self-luminous retrieval P-T model. Args: temperature_nodes : jnp.array([t1, t2, t3]) temperature points to be added on top radiative Eddington structure (above tau = 0.1). Use spline interpolation, t1 < t2 < t3 < tconnect as prior. delta : float proportionality factor in tau = delta * pressures_cgs**alpha alpha : float power law index in tau = delta * pressures_cgs**alpha For the tau model: use proximity to kappa_rosseland photosphere as prior. t_internal : float internal temperature of the Eddington model pressures : jnp.ndarray input pressure profile in bar conv : bool enforce convective adiabat yes/no co_ratio : float C/O for the nabla_ad interpolation metallicity : float metallicity for the nabla_ad interpolation Returns: Tret : jnp.ndarray The temperature as a function of atmospheric pressure. .. py:function:: power_law_temperature_profile(pressures: jax.typing.ArrayLike, alpha: float, T0: float) -> jax.Array Compute a power law profile for temperature; log(T) = a*log(P) + b. This function computes a cubic spline profile for temperature using pressure and temperature data points, along with a curvature prior. Args: pressures (array-like): An array or list of pressure data points. alpha (float): power law exponent (how steep is the profile) T0 (float): multiplicative factor (offsets the profile) Returns: temperatures (array): temperature values for each pressure value .. py:function:: linear_spline_temperature_profile(pressures: jax.typing.ArrayLike, temperature_points: jax.typing.ArrayLike, gamma: float, nnodes: int = 0) -> tuple[jax.typing.ArrayLike, float] Compute a linear spline profile for temperature based on pressure points. This function computes a linear spline profile for temperature using pressure and temperature data points, along with a curvature prior. Args: pressures: An array of pressure data points. temperature_points: An array of temperature data points. gamma: A parameter controlling the curvature of the spline. nnodes: Number of nodes to use in the spline interpolation. Defaults to 0, which means automatic determination of nodes. Returns: A tuple containing: - interpolated_temperatures: Interpolated temperature values based on the linear spline. - prior: Curvature prior value calculated for the spline. .. py:function:: cubic_spline_temperature_profile(pressures: jax.typing.ArrayLike, temperature_points: jax.typing.ArrayLike, gamma: float, nnodes: int = 0) -> tuple[jax.Array, float] Compute a cubic spline profile for temperature based on pressure points. This function computes a cubic spline profile for temperature using pressure and temperature data points, along with a curvature prior. Args: pressures: An array of pressure data points. temperature_points: An array of temperature data points. gamma: A parameter controlling the curvature of the spline. nnodes: Number of nodes to use in the spline interpolation. Defaults to 0, which means automatic determination of nodes. Returns: A tuple containing: - interpolated_temperatures: Interpolated temperature values based on the cubic spline. - prior: Curvature prior value calculated for the spline.