diff --git a/jaxpm/growth.py b/jaxpm/growth.py new file mode 100644 index 0000000..0be4718 --- /dev/null +++ b/jaxpm/growth.py @@ -0,0 +1,608 @@ +import jax.numpy as np + +from jax_cosmo.scipy.interpolate import interp +from jax_cosmo.scipy.ode import odeint +from jax_cosmo.background import * + +def E(cosmo, a): + r"""Scale factor dependent factor E(a) in the Hubble + parameter. + Parameters + ---------- + a : array_like + Scale factor + Returns + ------- + E : ndarray, or float if input scalar + Square of the scaling of the Hubble constant as a function of + scale factor + Notes + ----- + The Hubble parameter at scale factor `a` is given by + :math:`H^2(a) = E^2(a) H_o^2` where :math:`E^2` is obtained through + Friedman's Equation (see :cite:`2005:Percival`) : + .. math:: + E^2(a) = \Omega_m a^{-3} + \Omega_k a^{-2} + \Omega_{de} a^{f(a)} + where :math:`f(a)` is the Dark Energy evolution parameter computed + by :py:meth:`.f_de`. + """ + return np.power(Esqr(cosmo, a), 0.5) + + +def df_de(cosmo, a, epsilon=1e-5): + r"""Derivative of the evolution parameter for the Dark Energy density + f(a) with respect to the scale factor. + Parameters + ---------- + cosmo: Cosmology + Cosmological parameters structure + a : array_like + Scale factor + epsilon: float value + Small number to make sure we are not dividing by 0 and avoid a singularity + Returns + ------- + df(a)/da : ndarray, or float if input scalar + Derivative of the evolution parameter for the Dark Energy density + with respect to the scale factor. + Notes + ----- + The expression for :math:`\frac{df(a)}{da}` is: + .. math:: + \frac{df}{da}(a) = =\frac{3w_a \left( \ln(a-\epsilon)- + \frac{a-1}{a-\epsilon}\right)}{\ln^2(a-\epsilon)} + """ + return ( + 3 + * cosmo.wa + * (np.log(a - epsilon) - (a - 1) / (a - epsilon)) + / np.power(np.log(a - epsilon), 2) + ) + + +def dEa(cosmo, a): + r"""Derivative of the scale factor dependent factor E(a) in the Hubble + parameter. + Parameters + ---------- + a : array_like + Scale factor + Returns + ------- + dE(a)/da : ndarray, or float if input scalar + Derivative of the scale factor dependent factor in the Hubble + parameter with respect to the scale factor. + Notes + ----- + The expression for :math:`\frac{dE}{da}` is: + .. math:: + \frac{dE(a)}{da}=\frac{-3a^{-4}\Omega_{0m} + -2a^{-3}\Omega_{0k} + +f'_{de}\Omega_{0de}a^{f_{de}(a)}}{2E(a)} + Notes + ----- + The Hubble parameter at scale factor `a` is given by + :math:`H^2(a) = E^2(a) H_o^2` where :math:`E^2` is obtained through + Friedman's Equation (see :cite:`2005:Percival`) : + .. math:: + E^2(a) = \Omega_m a^{-3} + \Omega_k a^{-2} + \Omega_{de} a^{f(a)} + where :math:`f(a)` is the Dark Energy evolution parameter computed + by :py:meth:`.f_de`. + """ + return ( + 0.5 + * ( + -3 * cosmo.Omega_m * np.power(a, -4) + - 2 * cosmo.Omega_k * np.power(a, -3) + + df_de(cosmo, a) * cosmo.Omega_de * np.power(a, f_de(cosmo, a)) + ) + / np.power(Esqr(cosmo, a), 0.5) + ) + + +def growth_factor(cosmo, a): + """Compute linear growth factor D(a) at a given scale factor, + normalized such that D(a=1) = 1. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + D: ndarray, or float if input scalar + Growth factor computed at requested scale factor + + Notes + ----- + The growth computation will depend on the cosmology parametrization, for + instance if the $\gamma$ parameter is defined, the growth will be computed + assuming the $f = \Omega^\gamma$ growth rate, otherwise the usual ODE for + growth will be solved. + """ + if cosmo._flags["gamma_growth"]: + return _growth_factor_gamma(cosmo, a) + else: + return _growth_factor_ODE(cosmo, a) + + +def growth_factor_second(cosmo, a): + """Compute second order growth factor D2(a) at a given scale factor, + normalized such that D(a=1) = 1. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + D2: ndarray, or float if input scalar + Growth factor computed at requested scale factor + + Notes + ----- + The growth computation will depend on the cosmology parametrization, + as for the linear growth. Currently the second order growth + factor is not implemented with $\gamma$ parameter. + """ + if cosmo._flags["gamma_growth"]: + raise NotImplementedError( + "Gamma growth rate is not implemented for second order growth!" + ) + return None + else: + return _growth_factor_second_ODE(cosmo, a) + + +def growth_rate(cosmo, a): + """Compute growth rate dD/dlna at a given scale factor. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + f: ndarray, or float if input scalar + Growth rate computed at requested scale factor + + Notes + ----- + The growth computation will depend on the cosmology parametrization, for + instance if the $\gamma$ parameter is defined, the growth will be computed + assuming the $f = \Omega^\gamma$ growth rate, otherwise the usual ODE for + growth will be solved. + + The LCDM approximation to the growth rate :math:`f_{\gamma}(a)` is given by: + + .. math:: + + f_{\gamma}(a) = \Omega_m^{\gamma} (a) + + with :math: `\gamma` in LCDM, given approximately by: + .. math:: + + \gamma = 0.55 + + see :cite:`2019:Euclid Preparation VII, eqn.32` + """ + if cosmo._flags["gamma_growth"]: + return _growth_rate_gamma(cosmo, a) + else: + return _growth_rate_ODE(cosmo, a) + + +def growth_rate_second(cosmo, a): + """Compute second order growth rate dD2/dlna at a given scale factor. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + f2: ndarray, or float if input scalar + Second order growth rate computed at requested scale factor + + Notes + ----- + The growth computation will depend on the cosmology parametrization, + as for the linear growth rate. Currently the second order growth + rate is not implemented with $\gamma$ parameter. + """ + if cosmo._flags["gamma_growth"]: + raise NotImplementedError( + "Gamma growth factor is not implemented for second order growth!" + ) + return None + else: + return _growth_rate_second_ODE(cosmo, a) + + +def _growth_factor_ODE(cosmo, a, log10_amin=-3, steps=128, eps=1e-4): + """Compute linear growth factor D(a) at a given scale factor, + normalised such that D(a=1) = 1. + + Parameters + ---------- + a: array_like + Scale factor + + amin: float + Mininum scale factor, default 1e-3 + + Returns + ------- + D: ndarray, or float if input scalar + Growth factor computed at requested scale factor + """ + # Check if growth has already been computed + if not "background.growth_factor" in cosmo._workspace.keys(): + # Compute tabulated array + atab = np.logspace(log10_amin, 0.0, steps) + + def D_derivs(y, x): + q = ( + 2.0 + - 0.5 + * ( + Omega_m_a(cosmo, x) + + (1.0 + 3.0 * w(cosmo, x)) * Omega_de_a(cosmo, x) + ) + ) / x + r = 1.5 * Omega_m_a(cosmo, x) / x / x + + g1, g2 = y[0] + f1, f2 = y[1] + dy1da = [f1, -q * f1 + r * g1] + dy2da = [f2, -q * f2 + r * g2 - r * g1 ** 2] + return np.array([[dy1da[0], dy2da[0]], [dy1da[1], dy2da[1]]]) + + y0 = np.array([[atab[0], -3.0 / 7 * atab[0] ** 2], [1.0, -6.0 / 7 * atab[0]]]) + y = odeint(D_derivs, y0, atab) + + # compute second order derivatives growth + dyda2 = D_derivs(np.transpose(y, (1, 2, 0)), atab) + dyda2 = np.transpose(dyda2, (2, 0, 1)) + + # Normalize results + y1 = y[:, 0, 0] + gtab = y1 / y1[-1] + y2 = y[:, 0, 1] + g2tab = y2 / y2[-1] + # To transform from dD/da to dlnD/dlna: dlnD/dlna = a / D dD/da + ftab = y[:, 1, 0] / y1[-1] * atab / gtab + f2tab = y[:, 1, 1] / y2[-1] * atab / g2tab + # Similarly for second order derivatives + # Note: these factors are not accessible as parent functions yet + # since it is unclear what to refer to them with. + htab = dyda2[:, 1, 0] / y1[-1] * atab / gtab + h2tab = dyda2[:, 1, 1] / y2[-1] * atab / g2tab + + cache = { + "a": atab, + "g": gtab, + "f": ftab, + "h": htab, + "g2": g2tab, + "f2": f2tab, + "h2": h2tab, + } + cosmo._workspace["background.growth_factor"] = cache + else: + cache = cosmo._workspace["background.growth_factor"] + return np.clip(interp(a, cache["a"], cache["g"]), 0.0, 1.0) + + +def _growth_rate_ODE(cosmo, a): + """Compute growth rate dD/dlna at a given scale factor by solving the linear + growth ODE. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + f: ndarray, or float if input scalar + Growth rate computed at requested scale factor + """ + # Check if growth has already been computed, if not, compute it + if not "background.growth_factor" in cosmo._workspace.keys(): + _growth_factor_ODE(cosmo, np.atleast_1d(1.0)) + cache = cosmo._workspace["background.growth_factor"] + return interp(a, cache["a"], cache["f"]) + + +def _growth_factor_second_ODE(cosmo, a): + """Compute second order growth factor D2(a) at a given scale factor, + normalised such that D(a=1) = 1. + + Parameters + ---------- + a: array_like + Scale factor + + amin: float + Mininum scale factor, default 1e-3 + + Returns + ------- + D2: ndarray, or float if input scalar + Second order growth factor computed at requested scale factor + """ + # Check if growth has already been computed, if not, compute it + if not "background.growth_factor" in cosmo._workspace.keys(): + _growth_factor_ODE(cosmo, np.atleast_1d(1.0)) + cache = cosmo._workspace["background.growth_factor"] + return interp(a, cache["a"], cache["g2"]) + + +def _growth_rate_ODE(cosmo, a): + """Compute growth rate dD/dlna at a given scale factor by solving the linear + growth ODE. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + f: ndarray, or float if input scalar + Second order growth rate computed at requested scale factor + """ + # Check if growth has already been computed, if not, compute it + if not "background.growth_factor" in cosmo._workspace.keys(): + _growth_factor_ODE(cosmo, np.atleast_1d(1.0)) + cache = cosmo._workspace["background.growth_factor"] + return interp(a, cache["a"], cache["f"]) + + +def _growth_rate_second_ODE(cosmo, a): + """Compute second order growth rate dD2/dlna at a given scale factor by solving the linear + growth ODE. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a: array_like + Scale factor + + Returns + ------- + f2: ndarray, or float if input scalar + Second order growth rate computed at requested scale factor + """ + # Check if growth has already been computed, if not, compute it + if not "background.growth_factor" in cosmo._workspace.keys(): + _growth_factor_ODE(cosmo, np.atleast_1d(1.0)) + cache = cosmo._workspace["background.growth_factor"] + return interp(a, cache["a"], cache["f2"]) + + +def _growth_factor_gamma(cosmo, a, log10_amin=-3, steps=128): + r"""Computes growth factor by integrating the growth rate provided by the + \gamma parametrization. Normalized such that D( a=1) =1 + + Parameters + ---------- + a: array_like + Scale factor + + amin: float + Mininum scale factor, default 1e-3 + + Returns + ------- + D: ndarray, or float if input scalar + Growth factor computed at requested scale factor + + """ + # Check if growth has already been computed, if not, compute it + if not "background.growth_factor" in cosmo._workspace.keys(): + # Compute tabulated array + atab = np.logspace(log10_amin, 0.0, steps) + + def integrand(y, loga): + xa = np.exp(loga) + return _growth_rate_gamma(cosmo, xa) + + gtab = np.exp(odeint(integrand, np.log(atab[0]), np.log(atab))) + gtab = gtab / gtab[-1] # Normalize to a=1. + cache = {"a": atab, "g": gtab} + cosmo._workspace["background.growth_factor"] = cache + else: + cache = cosmo._workspace["background.growth_factor"] + return np.clip(interp(a, cache["a"], cache["g"]), 0.0, 1.0) + + +def _growth_rate_gamma(cosmo, a): + r"""Growth rate approximation at scale factor `a`. + + Parameters + ---------- + cosmo: `Cosmology` + Cosmology object + + a : array_like + Scale factor + + Returns + ------- + f_gamma : ndarray, or float if input scalar + Growth rate approximation at the requested scale factor + + Notes + ----- + The LCDM approximation to the growth rate :math:`f_{\gamma}(a)` is given by: + + .. math:: + + f_{\gamma}(a) = \Omega_m^{\gamma} (a) + + with :math: `\gamma` in LCDM, given approximately by: + .. math:: + + \gamma = 0.55 + + see :cite:`2019:Euclid Preparation VII, eqn.32` + """ + return Omega_m_a(cosmo, a) ** cosmo.gamma + + + +def Gf(cosmo, a): + r""" + FastPM growth factor function + + Parameters + ---------- + cosmo: dict + Cosmology dictionary. + + a : array_like + Scale factor. + + Returns + ------- + Scalar float Tensor : FastPM growth factor function. + + Notes + ----- + + The expression for :math:`Gf(a)` is: + + .. math:: + Gf(a)=D'_{1norm}*a**3*E(a) + """ + f1 = growth_rate(cosmo, a) + g1 = growth_factor(cosmo, a) + D1f = f1*g1/ a + return D1f * np.power(a, 3) * np.power(Esqr(cosmo, a), 0.5) + + +def Gf2(cosmo, a): + r""" FastPM second order growth factor function + + Parameters + ---------- + cosmo: dict + Cosmology dictionary. + + a : array_like + Scale factor. + + Returns + ------- + Scalar float Tensor : FastPM second order growth factor function. + + Notes + ----- + + The expression for :math:`Gf_2(a)` is: + + .. math:: + Gf_2(a)=D'_{2norm}*a**3*E(a) + """ + f2 = growth_rate_second(cosmo, a) + g2 = growth_factor_second(cosmo, a) + D2f = f2*g2/ a + return D2f * np.power(a, 3) * np.power(Esqr(cosmo, a), 0.5) + + +def dGfa(cosmo, a): + r""" Derivative of Gf against a + + Parameters + ---------- + cosmo: dict + Cosmology dictionary. + + a : array_like + Scale factor. + + Returns + ------- + Scalar float Tensor : the derivative of Gf against a. + + Notes + ----- + + The expression for :math:`gf(a)` is: + + .. math:: + gf(a)=\frac{dGF}{da}= D^{''}_1 * a ** 3 *E(a) +D'_{1norm}*a ** 3 * E'(a) + + 3 * a ** 2 * E(a)*D'_{1norm} + + """ + f1 = growth_rate(cosmo, a) + g1 = growth_factor(cosmo, a) + D1f = f1*g1/ a + cache = cosmo._workspace['background.growth_factor'] + f1p = cache['h'] / cache['a'] * cache['g'] + f1p = interp(np.log(a), np.log(cache['a']), f1p) + Ea = E(cosmo, a) + return (f1p * a**3 * Ea + D1f * a**3 * dEa(cosmo, a) + + 3 * a**2 * Ea * D1f) + + +def dGf2a(cosmo, a): + r""" Derivative of Gf2 against a + + Parameters + ---------- + cosmo: dict + Cosmology dictionary. + + a : array_like + Scale factor. + + Returns + ------- + Scalar float Tensor : the derivative of Gf2 against a. + + Notes + ----- + + The expression for :math:`gf2(a)` is: + + .. math:: + gf_2(a)=\frac{dGF_2}{da}= D^{''}_2 * a ** 3 *E(a) +D'_{2norm}*a ** 3 * E'(a) + + 3 * a ** 2 * E(a)*D'_{2norm} + + """ + f2 = growth_rate_second(cosmo, a) + g2 = growth_factor_second(cosmo, a) + D2f = f2*g2/ a + cache = cosmo._workspace['background.growth_factor'] + f2p = cache['h2'] / cache['a'] * cache['g2'] + f2p = interp(np.log(a), np.log(cache['a']), f2p) + E = E(cosmo, a) + return (f2p * a**3 * E + D2f * a**3 * dEa(cosmo, a) + + 3 * a**2 * E * D2f) \ No newline at end of file