"""Parameter-Space definitions for holodeck libraries.
"""
import holodeck as holo
from holodeck.constants import GYR, PC, MSOL
from holodeck.librarian.libraries import _Param_Space, PD_Uniform, PD_Normal
# Define a new Parameter-Space class by subclassing the base class:
# :py:class:`holodeck.librarian.libaries._Param_Space`. The names of all parameter-space subclasses
# should typically be prefixed by `PS_` to denote that they are parameter-spaces.
[docs]
class PS_Test(_Param_Space):
"""Simple Test Parameter Space: SAM with strongly astrophysically-motivated parameters.
This model uses a double-Schechter GSMF, an Illustris-derived galaxy merger rate, a Kormendy+Ho
M-MBulge relationship, and a phenomenology binary evolution model.
"""
# The `DEFAULTS` attribute is a dictionary of default parameter values. These are automatically
# copied over to the `params` arguments that are passed into the `_init_sam` and `_init_hard`
# methods. Specifying these is strongly recommended to ensure that parameters are set
# consistently, by setting them explicitly.
# Notice that each group of parameters is named with a common prefix, e.g. 'hard_' or 'gsmf_'.
# This is not required, but simply used to more easily organize/identify parameters.
DEFAULTS = dict(
hard_time=3.0, # [Gyr]
hard_sepa_init=1e4, # [pc]
hard_rchar=100.0, # [pc]
hard_gamma_inner=-1.0,
hard_gamma_outer=+2.5,
# Galaxy stellar-mass Function (``GSMF_Schechter``)
gsmf_phi0_log10=-2.77,
gsmf_phiz=-0.6,
gsmf_mchar0_log10=11.24,
gsmf_mcharz=0.11,
gsmf_alpha0=-1.21,
gsmf_alphaz=-0.03,
# Galaxy merger rate (``GMR_Illustris``)
# Parameters are taken directly from [Rodriguez-Gomez2015]_
gmr_norm0_log10=-2.2287, # -2.2287 ± 0.0045 A0 [log10(A*Gyr)]
gmr_normz=+2.4644, # +2.4644 ± 0.0128 eta
gmr_malpha0=+0.2241, # +0.2241 ± 0.0038 alpha0
gmr_malphaz=-1.1759, # -1.1759 ± 0.0316 alpha1
gmr_mdelta0=+0.7668, # +0.7668 ± 0.0202 delta0
gmr_mdeltaz=-0.4695, # -0.4695 ± 0.0440 delta1
gmr_qgamma0=-1.2595, # -1.2595 ± 0.0026 beta0
gmr_qgammaz=+0.0611, # +0.0611 ± 0.0021 beta1
gmr_qgammam=-0.0477, # -0.0477 ± 0.0013 gamma
# M-MBulge Relationship (``MMBulge_KH2013``)
# From [KH2013]_
mmb_mamp=0.49e9, # 0.49e9 + 0.06 - 0.05 [Msol]
mmb_plaw=1.17, # 1.17 ± 0.08
mmb_scatter_dex=0.28, # no uncertainties given
)
# The initialization method should typically include the below arguments, which are passed
# directly to the parent/super ``_Param_Space`` constructor. These arguments could be passed
# along using ``**kwargs``, but they are included explicitly for clarity and for convenience
# when examining the function signature.
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None, **kwargs):
# NOTE: this is where the parameter-space is actually defined:
parameters = [
# The names of the parameters passed to the parameter distribution constructors
# MUST match the variable names expected in the parameter space methods (``_init_sam``
# and ``_init_hard``).
PD_Uniform("hard_time", 0.1, 11.0, default=3.0), # [Gyr]
# For the "hard_time" and "hard_gamma_inner" parameters, default values are specified
# explicitly because the fiducial parameters are not the central/average values. If no
# ``default`` value was specified, then the central/average value would be used, for
# example :math:`(11.0 + 0.1)/2 = 5.5` in the case of "hard_time" above.
PD_Uniform("hard_gamma_inner", -1.5, +0.0, default=-1.0),
# This specifies a normal distribution with the given mean and standard-deviation. In
# this case, no ``default`` value is specified, so the value returned from an input of
# 0.5 will be used which, for a normal distribution, is by definition the mean (0.49e9
# in this case).
PD_Normal("mmb_mamp", 0.49e9, 0.055e9),
]
# Call the parent/super constructor, passing in these parameters to define the domain of
# the parameter space.
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
**kwargs
)
return
# Define the function which actually constructs the SAM, using a dictionary of model parameters.
# This is not intended as an API function, but an internal method used to build the SAM model.
# The call signature of this function should *not* be changed, and the function must always
# return a single object: the instance of :py:class:`holodeck.sams.sam.Semi_Analytic_Model`.
def _init_sam(self, sam_shape, params):
# Schechter Galaxy Stellar-Mass Function
gsmf = holo.sams.GSMF_Schechter(
phi0=params['gsmf_phi0_log10'],
phiz=params['gsmf_phiz'],
mchar0_log10=params['gsmf_mchar0_log10'],
mcharz=params['gsmf_mcharz'],
alpha0=params['gsmf_alpha0'],
alphaz=params['gsmf_alphaz'],
)
# Illustris Galaxy Merger Rate
gmr = holo.sams.GMR_Illustris(
norm0_log10=params['gmr_norm0_log10'],
normz=params['gmr_normz'],
malpha0=params['gmr_malpha0'],
malphaz=params['gmr_malphaz'],
mdelta0=params['gmr_mdelta0'],
mdeltaz=params['gmr_mdeltaz'],
qgamma0=params['gmr_qgamma0'],
qgammaz=params['gmr_qgammaz'],
qgammam=params['gmr_qgammam'],
)
# Notice that a unit-conversion is being performed here, in the M-Mbulge constructor. The
# parameter space is defined such that the normalization is in units of solar-masses, while
# the M-Mbulge class itself is defined such that the normalization is in units of grams.
# This is a very easy place to make mistakes, and so any/all units (and particularly unit
# conversions) should be described carefully in docstrings.
mmbulge = holo.host_relations.MMBulge_KH2013(
mamp=params['mmb_mamp']*MSOL,
mplaw=params['mmb_plaw'],
scatter_dex=params['mmb_scatter_dex'],
)
sam = holo.sams.Semi_Analytic_Model(
gsmf=gsmf, gmr=gmr, mmbulge=mmbulge, shape=sam_shape,
)
return sam
# Define the function which constructs the hardening model, used by the SAM.
# This is not intended as an API function, but an internal method used to build the SAM model.
# The call signature of this function should *not* be changed, and the function must always
# return a single object: an instance of a subclass of
# :py:class:`holodeck.hardening._Hardening`.
def _init_hard(self, sam, params):
hard = holo.hardening.Fixed_Time_2PL_SAM(
sam,
params['hard_time']*GYR,
sepa_init=params['hard_sepa_init']*PC,
rchar=params['hard_rchar']*PC,
gamma_inner=params['hard_gamma_inner'],
gamma_outer=params['hard_gamma_outer'],
)
return hard
class _PS_Astro_Strong(_Param_Space):
"""SAM Model with strongly astrophysically-motivated parameters.
This model uses a double-Schechter GSMF, an Illustris-derived galaxy merger rate, a Kormendy+Ho
M-MBulge relationship, and a phenomenology binary evolution model.
"""
__version__ = "0.1"
DEFAULTS = dict(
# Hardening model (phenom 2PL)
hard_time=3.0, # [Gyr]
hard_sepa_init=1e4, # [pc]
hard_rchar=10.0, # [pc]
hard_gamma_inner=-1.0,
hard_gamma_outer=+2.5,
# Galaxy stellar-mass Function (``GSMF_Double_Schechter``)
# Parameters are based on `double-schechter.ipynb` conversions from [Leja2020]_
gsmf_log10_phi_one_z0=-2.383, # - 2.383 ± 0.028
gsmf_log10_phi_one_z1=-0.264, # - 0.264 ± 0.072
gsmf_log10_phi_one_z2=-0.107, # - 0.107 ± 0.031
gsmf_log10_phi_two_z0=-2.818, # - 2.818 ± 0.050
gsmf_log10_phi_two_z1=-0.368, # - 0.368 ± 0.070
gsmf_log10_phi_two_z2=+0.046, # + 0.046 ± 0.020
gsmf_log10_mstar_z0=+10.767, # +10.767 ± 0.026
gsmf_log10_mstar_z1=+0.124, # + 0.124 ± 0.045
gsmf_log10_mstar_z2=-0.033, # - 0.033 ± 0.015
gsmf_alpha_one=-0.28, # - 0.280 ± 0.070
gsmf_alpha_two=-1.48, # - 1.480 ± 0.150
# Galaxy merger rate (``GMR_Illustris``)
# Parameters are taken directly from [Rodriguez-Gomez2015]_
gmr_norm0_log10=-2.2287, # -2.2287 ± 0.0045 A0 [log10(A*Gyr)]
gmr_normz=+2.4644, # +2.4644 ± 0.0128 eta
gmr_malpha0=+0.2241, # +0.2241 ± 0.0038 alpha0
gmr_malphaz=-1.1759, # -1.1759 ± 0.0316 alpha1
gmr_mdelta0=+0.7668, # +0.7668 ± 0.0202 delta0
gmr_mdeltaz=-0.4695, # -0.4695 ± 0.0440 delta1
gmr_qgamma0=-1.2595, # -1.2595 ± 0.0026 beta0
gmr_qgammaz=+0.0611, # +0.0611 ± 0.0021 beta1
gmr_qgammam=-0.0477, # -0.0477 ± 0.0013 gamma
# M-MBulge Relationship (``MMBulge_KH2013``)
# From [KH2013]_
mmb_mamp=0.49e9, # 0.49e9 + 0.06 - 0.05 [Msol]
mmb_plaw=1.17, # 1.17 ± 0.08
mmb_scatter_dex=0.28, # no uncertainties given
)
@classmethod
def _init_sam(cls, sam_shape, params):
log10_phi_one = [
params['gsmf_log10_phi_one_z0'],
params['gsmf_log10_phi_one_z1'],
params['gsmf_log10_phi_one_z2'],
]
log10_phi_two = [
params['gsmf_log10_phi_two_z0'],
params['gsmf_log10_phi_two_z1'],
params['gsmf_log10_phi_two_z2'],
]
log10_mstar = [
params['gsmf_log10_mstar_z0'],
params['gsmf_log10_mstar_z1'],
params['gsmf_log10_mstar_z2'],
]
gsmf = holo.sams.GSMF_Double_Schechter(
log10_phi1=log10_phi_one,
log10_phi2=log10_phi_two,
log10_mstar=log10_mstar,
alpha1=params['gsmf_alpha_one'],
alpha2=params['gsmf_alpha_two'],
)
# Illustris Galaxy Merger Rate
gmr = holo.sams.GMR_Illustris(
norm0_log10=params['gmr_norm0_log10'],
normz=params['gmr_normz'],
malpha0=params['gmr_malpha0'],
malphaz=params['gmr_malphaz'],
mdelta0=params['gmr_mdelta0'],
mdeltaz=params['gmr_mdeltaz'],
qgamma0=params['gmr_qgamma0'],
qgammaz=params['gmr_qgammaz'],
qgammam=params['gmr_qgammam'],
)
mmbulge = holo.host_relations.MMBulge_KH2013(
mamp=params['mmb_mamp']*MSOL,
mplaw=params['mmb_plaw'],
scatter_dex=params['mmb_scatter_dex'],
)
sam = holo.sams.Semi_Analytic_Model(
gsmf=gsmf, gmr=gmr, mmbulge=mmbulge, shape=sam_shape,
)
return sam
@classmethod
def _init_hard(cls, sam, params):
hard = holo.hardening.Fixed_Time_2PL_SAM(
sam,
params['hard_time']*GYR,
sepa_init=params['hard_sepa_init']*PC,
rchar=params['hard_rchar']*PC,
gamma_inner=params['hard_gamma_inner'],
gamma_outer=params['hard_gamma_outer'],
)
return hard
[docs]
class PS_Astro_Strong_All(_PS_Astro_Strong):
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None):
parameters = [
# Hardening model (phenom 2PL)
PD_Uniform("hard_time", 0.1, 11.0, default=3.0), # [Gyr]
PD_Uniform("hard_gamma_inner", -1.5, +0.0, default=-1.0),
# GSMF
PD_Normal('gsmf_log10_phi_one_z0', -2.383, 0.028), # - 2.383 ± 0.028
PD_Normal('gsmf_log10_phi_one_z1', -0.264, 0.072), # - 0.264 ± 0.072
PD_Normal('gsmf_log10_phi_one_z2', -0.107, 0.031), # - 0.107 ± 0.031
PD_Normal('gsmf_log10_phi_two_z0', -2.818, 0.050), # - 2.818 ± 0.050
PD_Normal('gsmf_log10_phi_two_z1', -0.368, 0.070), # - 0.368 ± 0.070
PD_Normal('gsmf_log10_phi_two_z2', +0.046, 0.020), # + 0.046 ± 0.020
PD_Normal('gsmf_log10_mstar_z0', +10.767, 0.026), # +10.767 ± 0.026
PD_Normal('gsmf_log10_mstar_z1', +0.124, 0.045), # + 0.124 ± 0.045
PD_Normal('gsmf_log10_mstar_z2', -0.033, 0.015), # - 0.033 ± 0.015
PD_Normal('gsmf_alpha_one', -0.28, 0.070), # - 0.280 ± 0.070
PD_Normal('gsmf_alpha_two', -1.48, 0.150), # - 1.480 ± 0.150
# GMR
PD_Normal('gmr_norm0_log10', -2.2287, 0.0045), # -2.2287 ± 0.0045 A0 [log10(A*Gyr)]
PD_Normal('gmr_normz', +2.4644, 0.0128), # +2.4644 ± 0.0128 eta
PD_Normal('gmr_malpha0', +0.2241, 0.0038), # +0.2241 ± 0.0038 alpha0
PD_Normal('gmr_malphaz', -1.1759, 0.0316), # -1.1759 ± 0.0316 alpha1
PD_Normal('gmr_mdelta0', +0.7668, 0.0202), # +0.7668 ± 0.0202 delta0
PD_Normal('gmr_mdeltaz', -0.4695, 0.0440), # -0.4695 ± 0.0440 delta1
PD_Normal('gmr_qgamma0', -1.2595, 0.0026), # -1.2595 ± 0.0026 beta0
PD_Normal('gmr_qgammaz', +0.0611, 0.0021), # +0.0611 ± 0.0021 beta1
PD_Normal('gmr_qgammam', -0.0477, 0.0013), # -0.0477 ± 0.0013 gamma
# From [KH2013]_
PD_Normal('mmb_mamp', 0.49e9, 0.055e9), # 0.49e9 + 0.06 - 0.05 [Msol]
PD_Normal('mmb_plaw', 1.17, 0.08), # 1.17 ± 0.08
]
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
)
return
[docs]
class PS_Astro_Strong_Hard(_PS_Astro_Strong):
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None):
parameters = [
# Hardening model (phenom 2PL)
PD_Uniform("hard_time", 0.1, 11.0, default=3.0), # [Gyr]
PD_Uniform("hard_gamma_inner", -1.5, +0.0, default=-1.0),
]
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
)
return
[docs]
class PS_Astro_Strong_GSMF(_PS_Astro_Strong):
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None):
parameters = [
# GSMF
PD_Normal('gsmf_log10_phi_one_z0', -2.383, 0.028), # - 2.383 ± 0.028
PD_Normal('gsmf_log10_phi_one_z1', -0.264, 0.072), # - 0.264 ± 0.072
PD_Normal('gsmf_log10_phi_one_z2', -0.107, 0.031), # - 0.107 ± 0.031
PD_Normal('gsmf_log10_phi_two_z0', -2.818, 0.050), # - 2.818 ± 0.050
PD_Normal('gsmf_log10_phi_two_z1', -0.368, 0.070), # - 0.368 ± 0.070
PD_Normal('gsmf_log10_phi_two_z2', +0.046, 0.020), # + 0.046 ± 0.020
PD_Normal('gsmf_log10_mstar_z0', +10.767, 0.026), # +10.767 ± 0.026
PD_Normal('gsmf_log10_mstar_z1', +0.124, 0.045), # + 0.124 ± 0.045
PD_Normal('gsmf_log10_mstar_z2', -0.033, 0.015), # - 0.033 ± 0.015
PD_Normal('gsmf_alpha_one', -0.28, 0.070), # - 0.280 ± 0.070
PD_Normal('gsmf_alpha_two', -1.48, 0.150), # - 1.480 ± 0.150
]
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
)
return
[docs]
class PS_Astro_Strong_GMR(_PS_Astro_Strong):
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None):
parameters = [
# GMR
PD_Normal('gmr_norm0_log10', -2.2287, 0.0045), # -2.2287 ± 0.0045 A0 [log10(A*Gyr)]
PD_Normal('gmr_normz', +2.4644, 0.0128), # +2.4644 ± 0.0128 eta
PD_Normal('gmr_malpha0', +0.2241, 0.0038), # +0.2241 ± 0.0038 alpha0
PD_Normal('gmr_malphaz', -1.1759, 0.0316), # -1.1759 ± 0.0316 alpha1
PD_Normal('gmr_mdelta0', +0.7668, 0.0202), # +0.7668 ± 0.0202 delta0
PD_Normal('gmr_mdeltaz', -0.4695, 0.0440), # -0.4695 ± 0.0440 delta1
PD_Normal('gmr_qgamma0', -1.2595, 0.0026), # -1.2595 ± 0.0026 beta0
PD_Normal('gmr_qgammaz', +0.0611, 0.0021), # +0.0611 ± 0.0021 beta1
PD_Normal('gmr_qgammam', -0.0477, 0.0013), # -0.0477 ± 0.0013 gamma
]
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
)
return
[docs]
class PS_Astro_Strong_MMBulge(_PS_Astro_Strong):
def __init__(self, log=None, nsamples=None, sam_shape=None, seed=None):
parameters = [
# MMbulge - from [KH2013]_
PD_Normal('mmb_mamp', 0.49e9, 0.055e9), # 0.49e9 + 0.06 - 0.05 [Msol]
PD_Normal('mmb_plaw', 1.17, 0.08), # 1.17 ± 0.08
]
_Param_Space.__init__(
self, parameters,
log=log, nsamples=nsamples, sam_shape=sam_shape, seed=seed,
)
return
_param_spaces_dict = {
'PS_Astro_Strong_All': PS_Astro_Strong_All,
'PS_Astro_Strong_Hard': PS_Astro_Strong_Hard,
'PS_Astro_Strong_GSMF': PS_Astro_Strong_GSMF,
'PS_Astro_Strong_GMR': PS_Astro_Strong_GMR,
'PS_Astro_Strong_MMBulge': PS_Astro_Strong_MMBulge,
}