__author__ = "sibirrer"
# this file contains a class to compute the truncated Navaro-Frank-White function (Baltz et al 2009)in mass/kappa space
# the potential therefore is its integral
import numpy as np
from lenstronomy.LensModel.Profiles.base_profile import LensProfileBase
from lenstronomy.LensModel.Profiles.nfw import NFW
__all__ = ["TNFW"]
[docs]
class TNFW(LensProfileBase):
"""This class contains functions concerning the truncated NFW profile with a
truncation function (r_trunc^2)*(r^2+r_trunc^2)
density equation is:
.. math::
\\rho(r) = \\frac{r_\\text{trunc}^2}{r^2+r_\\text{trunc}^2}\\frac{\\rho_0(\\alpha_{R_s})}{r/R_s(1+r/R_s)^2}
relation are: R_200 = c * Rs
"""
profile_name = "TNFW"
param_names = ["Rs", "alpha_Rs", "r_trunc", "center_x", "center_y"]
lower_limit_default = {
"Rs": 0,
"alpha_Rs": 0,
"r_trunc": 0,
"center_x": -100,
"center_y": -100,
}
upper_limit_default = {
"Rs": 100,
"alpha_Rs": 10,
"r_trunc": 100,
"center_x": 100,
"center_y": 100,
}
[docs]
def __init__(self):
""""""
self._s = 0.001
super(LensProfileBase, self).__init__()
[docs]
def function(self, x, y, Rs, alpha_Rs, r_trunc, center_x=0, center_y=0):
"""
:param x: angular position
:param y: angular position
:param Rs: angular turn over point
:param alpha_Rs: deflection at Rs
:param r_trunc: truncation radius
:param center_x: center of halo
:param center_y: center of halo
:return: lensing potential
"""
rho0_input = self.alpha2rho0(alpha_Rs=alpha_Rs, Rs=Rs)
x_ = x - center_x
y_ = y - center_y
R = np.sqrt(x_**2 + y_**2)
R = np.maximum(R, self._s * Rs)
f_ = self.nfw_potential(R, Rs, rho0_input, r_trunc)
return f_
def _L(self, x, tau):
"""Logarithm that appears frequently.
:param x: r/Rs
:param tau: t/Rs
:return:
"""
x = np.maximum(x, self._s)
return np.log(x * (tau + np.sqrt(tau**2 + x**2)) ** -1)
[docs]
def F(self, x):
"""Classic NFW function in terms of arctanh and arctan.
:param x: r/Rs
:return:
"""
if isinstance(x, np.ndarray):
x = np.maximum(x, self._s)
nfwvals = np.zeros_like(x)
inds1 = np.where(x < 1)
inds2 = np.where(x > 1)
inds3 = np.where(x == 1)
nfwvals[inds1] = (1 - x[inds1] ** 2) ** -0.5 * np.arctanh(
(1 - x[inds1] ** 2) ** 0.5
)
nfwvals[inds2] = (x[inds2] ** 2 - 1) ** -0.5 * np.arctan(
(x[inds2] ** 2 - 1) ** 0.5
)
nfwvals[inds3] = 1
return nfwvals
elif isinstance(x, float) or isinstance(x, int):
x = np.maximum(x, 0)
if x == 1:
return 1
elif x == 0:
return 0
elif x < 1:
return (1 - x**2) ** -0.5 * np.arctanh((1 - x**2) ** 0.5)
else:
return (x**2 - 1) ** -0.5 * np.arctan((x**2 - 1) ** 0.5)
[docs]
def derivatives(self, x, y, Rs, alpha_Rs, r_trunc, center_x=0, center_y=0):
"""Returns df/dx and df/dy of the function (integral of TNFW), which are the
deflection angles.
:param x: angular position (normally in units of arc seconds)
:param y: angular position (normally in units of arc seconds)
:param Rs: turn over point in the slope of the NFW profile in angular unit
:param alpha_Rs: deflection (angular units) at projected Rs
:param r_trunc: truncation radius (angular units)
:param center_x: center of halo (in angular units)
:param center_y: center of halo (in angular units)
:return: deflection angle in x, deflection angle in y
"""
rho0_input = self.alpha2rho0(alpha_Rs=alpha_Rs, Rs=Rs)
x_ = x - center_x
y_ = y - center_y
R = np.sqrt(x_**2 + y_**2)
R = np.maximum(R, self._s * Rs)
f_x, f_y = self.nfw_alpha(R, Rs, rho0_input, r_trunc, x_, y_)
return f_x, f_y
[docs]
def hessian(self, x, y, Rs, alpha_Rs, r_trunc, center_x=0, center_y=0):
"""Returns d^2f/dx^2, d^2f/dxdy, d^2f/dydx, d^2f/dy^2 of the TNFW potential f.
:param x: angular position (normally in units of arc seconds)
:param y: angular position (normally in units of arc seconds)
:param Rs: turn over point in the slope of the NFW profile in angular unit
:param alpha_Rs: deflection (angular units) at projected Rs
:param r_trunc: truncation radius (angular units)
:param center_x: center of halo (in angular units)
:param center_y: center of halo (in angular units)
:return: Hessian matrix of function d^2f/dx^2, d^f/dy^2, d^2/dxdy
"""
rho0_input = self.alpha2rho0(alpha_Rs=alpha_Rs, Rs=Rs)
x_ = x - center_x
y_ = y - center_y
R = np.sqrt(x_**2 + y_**2)
R = np.maximum(R, self._s * Rs)
kappa = self.density_2d(x_, y_, Rs, rho0_input, r_trunc)
gamma1, gamma2 = self.nfw_gamma(R, Rs, rho0_input, r_trunc, x_, y_)
f_xx = kappa + gamma1
f_yy = kappa - gamma1
f_xy = gamma2
return f_xx, f_xy, f_xy, f_yy
[docs]
@staticmethod
def density(r, Rs, rho0, r_trunc):
"""Three dimensional truncated NFW profile.
:param r: radius of interest
:type r: float/numpy array
:param Rs: scale radius
:type Rs: float > 0
:param r_trunc: truncation radius (angular units)
:type r_trunc: float > 0
:return: rho(r) density
"""
return (
(r_trunc**2 * (r_trunc**2 + r**2) ** -1)
* rho0
/ (r / Rs * (1 + r / Rs) ** 2)
)
[docs]
def density_2d(self, x, y, Rs, rho0, r_trunc, center_x=0, center_y=0):
"""Projected two dimensional NFW profile (kappa*Sigma_crit)
:param R: projected radius of interest
:type R: float/numpy array
:param Rs: scale radius
:type Rs: float
:param rho0: density normalization (characteristic density)
:type rho0: float
:param r_trunc: truncation radius (angular units)
:type r_trunc: float > 0
:return: Epsilon(R) projected density at radius R
"""
x_ = x - center_x
y_ = y - center_y
R = np.sqrt(x_**2 + y_**2)
x = R * Rs**-1
tau = float(r_trunc) * Rs**-1
Fx = self._F(x, tau)
return 2 * rho0 * Rs * Fx
[docs]
def mass_3d(self, r, Rs, rho0, r_trunc):
"""Mass enclosed a 3d sphere or radius r.
:param r: 3d radius
:param Rs: scale radius
:param rho0: density normalization (characteristic density)
:param r_trunc: truncation radius (angular units)
:return: M(<r)
"""
x = r * Rs**-1
x = np.maximum(x, self._s)
func = (
r_trunc**2
* (
-2 * x * (1 + r_trunc**2)
+ 4 * (1 + x) * r_trunc * np.arctan(x / r_trunc)
- 2 * (1 + x) * (-1 + r_trunc**2) * np.log(Rs)
+ 2 * (1 + x) * (-1 + r_trunc**2) * np.log(Rs * (1 + x))
+ 2 * (1 + x) * (-1 + r_trunc**2) * np.log(Rs * r_trunc)
- (1 + x)
* (-1 + r_trunc**2)
* np.log(Rs**2 * (x**2 + r_trunc**2))
)
) / (2.0 * (1 + x) * (1 + r_trunc**2) ** 2)
m_3d = 4 * np.pi * Rs**3 * rho0 * func
return m_3d
[docs]
def nfw_potential(self, R, Rs, rho0, r_trunc):
"""Lensing potential of truncated NFW profile.
:param R: radius of interest
:type R: float/numpy array
:param Rs: scale radius
:type Rs: float
:param rho0: density normalization (characteristic density)
:type rho0: float
:param r_trunc: truncation radius (angular units)
:type r_trunc: float > 0
:return: lensing potential
"""
x = R / Rs
x = np.maximum(x, self._s)
tau = float(r_trunc) / Rs
hx = self._h(x, tau)
return 2 * rho0 * Rs**3 * hx
[docs]
def nfw_alpha(self, R, Rs, rho0, r_trunc, ax_x, ax_y):
"""Deflection angle of NFW profile along the projection to coordinate axis.
:param R: radius of interest
:type R: float/numpy array
:param Rs: scale radius
:type Rs: float
:param rho0: density normalization (characteristic density)
:type rho0: float
:param r_trunc: truncation radius (angular units)
:type r_trunc: float > 0
:param axis: projection to either x- or y-axis
:type axis: same as R
:return:
"""
R = np.maximum(R, self._s * Rs)
x = R / Rs
x = np.maximum(x, self._s)
tau = float(r_trunc) / Rs
gx = self._g(x, tau)
a = 4 * rho0 * Rs * gx / x**2
return a * ax_x, a * ax_y
[docs]
def nfw_gamma(self, R, Rs, rho0, r_trunc, ax_x, ax_y):
"""Shear gamma of NFW profile (times Sigma_crit) along the projection to
coordinate 'axis'.
:param R: radius of interest
:type R: float/numpy array
:param Rs: scale radius
:type Rs: float
:param rho0: density normalization (characteristic density)
:type rho0: float
:param r_trunc: truncation radius (angular units)
:type r_trunc: float > 0
:param axis: projection to either x- or y-axis
:type axis: same as R
:return:
"""
R = np.maximum(R, self._s * Rs)
x = R / Rs
tau = float(r_trunc) * Rs**-1
gx = self._g(x, tau)
Fx = self._F(x, tau)
a = 2 * rho0 * Rs * (2 * gx / x**2 - Fx)
return a * (ax_y**2 - ax_x**2) / R**2, -a * 2 * (ax_x * ax_y) / R**2
[docs]
def mass_2d(self, R, Rs, rho0, r_trunc):
"""Analytic solution of the projection integral (convergence)
:param R: projected radius
:param Rs: scale radius
:param rho0: density normalization (characteristic density)
:param r_trunc: truncation radius (angular units)
:return: mass enclosed 2d projected cylinder
"""
x = R / Rs
x = np.maximum(x, self._s)
tau = r_trunc / Rs
gx = self._g(x, tau)
m_2d = 4 * rho0 * Rs * R**2 * gx / x**2 * np.pi
return m_2d
def _F(self, X, tau):
"""Analytic solution of the projection integral (convergence)
:param X: R/Rs
:type X: float >0
"""
t2 = tau**2
X = np.maximum(X, self._s)
_F = self.F(X)
a = t2 * (t2 + 1) ** -2
if isinstance(X, np.ndarray):
# b = (t2 + 1) * (X ** 2 - 1) ** -1 * (1 - _F)
b = np.ones_like(X)
b[X == 1] = (t2 + 1) * 1.0 / 3
b[X != 1] = (t2 + 1) * (X[X != 1] ** 2 - 1) ** -1 * (1 - _F[X != 1])
elif isinstance(X, float) or isinstance(X, int):
if X == 1:
b = (t2 + 1) * 1.0 / 3
else:
b = (t2 + 1) * (X**2 - 1) ** -1 * (1 - _F)
else:
raise ValueError(
"The variable type is not compatible with the function, please use float,"
" int or ndarray's."
)
c = 2 * _F
d = -np.pi * (t2 + X**2) ** -0.5
e = (t2 - 1) * (tau * (t2 + X**2) ** 0.5) ** -1 * self._L(X, tau)
result = a * (b + c + d + e)
return result
def _g(self, x, tau):
"""Analytic solution of integral for NFW profile to compute deflection angel and
gamma.
:param x: R/Rs
:type x: float >0
"""
x = np.maximum(x, self._s)
return (
tau**2
* (tau**2 + 1) ** -2
* (
(tau**2 + 1 + 2 * (x**2 - 1)) * self.F(x)
+ tau * np.pi
+ (tau**2 - 1) * np.log(tau)
+ np.sqrt(tau**2 + x**2)
* (-np.pi + self._L(x, tau) * (tau**2 - 1) * tau**-1)
)
)
@staticmethod
def _cos_function(x):
if isinstance(x, np.ndarray) or isinstance(x, list):
out = np.empty_like(x)
inds1 = np.where(x < 1)
inds2 = np.where(x >= 1)
out[inds1] = -np.arccosh(1 / x[inds1]) ** 2
out[inds2] = np.arccos(1 / x[inds2]) ** 2
elif isinstance(x, float) or isinstance(x, int):
if x < 1:
out = -np.arccosh(1 / x) ** 2
else:
out = np.arccos(1 / x) ** 2
else:
raise Exception("x data type %s not recognized." % x)
return out
def _h(self, x, tau):
"""Expression for the integral to compute potential.
:param x: R/Rs
:param tau: r_trunc/Rs
:type x: float >0
"""
x = np.maximum(x, self._s)
u = x**2
t2 = tau**2
Lx = self._L(x, tau)
Fx = self.F(x)
return (t2 + 1) ** -2 * (
2
* t2
* np.pi
* (tau - (t2 + u) ** 0.5 + tau * np.log(tau + (t2 + u) ** 0.5))
+ 2 * (t2 - 1) * tau * (t2 + u) ** 0.5 * Lx
+ t2 * (t2 - 1) * Lx**2
+ 4 * t2 * (u - 1) * Fx
+ t2 * (t2 - 1) * self._cos_function(x)
+ t2 * ((t2 - 1) * np.log(tau) - t2 - 1) * np.log(u)
- t2
* (
(t2 - 1) * np.log(tau) * np.log(4 * tau)
+ 2 * np.log(0.5 * tau)
- 2 * tau * (tau - np.pi) * np.log(tau * 2)
)
)
[docs]
@staticmethod
def alpha2rho0(alpha_Rs, Rs):
"""Convert angle at Rs into rho0; neglects the truncation.
:param alpha_Rs: deflection angle at RS
:param Rs: scale radius
:return: density normalization (characteristic density)
"""
return NFW.alpha2rho0(alpha_Rs, Rs)
[docs]
@staticmethod
def rho02alpha(rho0, Rs):
"""Convert rho0 to angle at Rs; neglects the truncation.
:param rho0: density normalization (characteristic density)
:param Rs: scale radius
:return: deflection angle at RS
"""
return NFW.rho02alpha(rho0, Rs)