# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Dark matter spectra."""
import numpy as np
import astropy.units as u
from astropy.table import Table
from gammapy.modeling import Parameter
from gammapy.modeling.models import (
SPECTRAL_MODEL_REGISTRY,
SpectralModel,
TemplateSpectralModel,
)
from gammapy.utils.interpolation import LogScale
from gammapy.utils.scripts import make_path
__all__ = ["PrimaryFlux", "DarkMatterAnnihilationSpectralModel"]
[docs]class PrimaryFlux:
"""DM-annihilation gamma-ray spectra.
Based on the precomputed models by Cirelli et al. (2016). All available
annihilation channels can be found there. The dark matter mass will be set
to the nearest available value. The spectra will be available as
`~gammapy.modeling.models.TemplateSpectralModel` for a chosen dark matter mass and
annihilation channel.
References
----------
* `2011JCAP...03..051 <https://ui.adsabs.harvard.edu/abs/2011JCAP...03..051C>`_
* Cirelli et al (2016): http://www.marcocirelli.net/PPPC4DMID.html
"""
channel_registry = {
"eL": "eL",
"eR": "eR",
"e": "e",
"muL": r"\[Mu]L",
"muR": r"\[Mu]R",
"mu": r"\[Mu]",
"tauL": r"\[Tau]L",
"tauR": r"\[Tau]R",
"tau": r"\[Tau]",
"q": "q",
"c": "c",
"b": "b",
"t": "t",
"WL": "WL",
"WT": "WT",
"W": "W",
"ZL": "ZL",
"ZT": "ZT",
"Z": "Z",
"g": "g",
"gamma": r"\[Gamma]",
"h": "h",
"nu_e": r"\[Nu]e",
"nu_mu": r"\[Nu]\[Mu]",
"nu_tau": r"\[Nu]\[Tau]",
"V->e": "V->e",
"V->mu": r"V->\[Mu]",
"V->tau": r"V->\[Tau]",
}
table_filename = "$GAMMAPY_DATA/dark_matter_spectra/AtProduction_gammas.dat"
def __init__(self, mDM, channel):
self.table_path = make_path(self.table_filename)
if not self.table_path.exists():
raise FileNotFoundError(
f"\n\nFile not found: {self.table_filename}\n"
"You may download the dataset needed with the following command:\n"
"gammapy download datasets --src dark_matter_spectra"
)
else:
self.table = Table.read(
str(self.table_path),
format="ascii.fast_basic",
guess=False,
delimiter=" ",
)
self.mDM = mDM
self.channel = channel
@property
def mDM(self):
"""Dark matter mass."""
return self._mDM
@mDM.setter
def mDM(self, mDM):
mDM_vals = self.table["mDM"].data
mDM_ = u.Quantity(mDM).to_value("GeV")
interp_idx = np.argmin(np.abs(mDM_vals - mDM_))
self._mDM = u.Quantity(mDM_vals[interp_idx], "GeV")
@property
def allowed_channels(self):
"""List of allowed annihilation channels."""
return list(self.channel_registry.keys())
@property
def channel(self):
"""Annihilation channel (str)."""
return self._channel
@channel.setter
def channel(self, channel):
if channel not in self.allowed_channels:
raise ValueError(
f"Invalid channel: {channel}\nAvailable: {self.allowed_channels}\n"
)
else:
self._channel = channel
@property
def table_model(self):
"""Spectrum as `~gammapy.modeling.models.TemplateSpectralModel`."""
subtable = self.table[self.table["mDM"] == self.mDM.value]
energies = (10 ** subtable["Log[10,x]"]) * self.mDM
channel_name = self.channel_registry[self.channel]
dN_dlogx = subtable[channel_name]
dN_dE = dN_dlogx / (energies * np.log(10))
return TemplateSpectralModel(
energy=energies,
values=dN_dE,
interp_kwargs={"fill_value": np.log(LogScale.tiny)},
)
[docs]class DarkMatterAnnihilationSpectralModel(SpectralModel):
r"""Dark matter annihilation spectral model.
The gamma-ray flux is computed as follows:
.. math::
\frac{\mathrm d \phi}{\mathrm d E} =
\frac{\langle \sigma\nu \rangle}{4\pi k m^2_{\mathrm{DM}}}
\frac{\mathrm d N}{\mathrm dE} \times J(\Delta\Omega)
Parameters
----------
mass : `~astropy.units.Quantity`
Dark matter mass
channel : str
Annihilation channel for `~gammapy.astro.darkmatter.PrimaryFlux`
scale : float
Scale parameter for model fitting
jfactor : `~astropy.units.Quantity`
Integrated J-Factor needed when `~gammapy.modeling.models.PointSpatialModel`
spatial model is used
z: float
Redshift value
k: int
Type of dark matter particle (k:2 Majorana, k:4 Dirac)
Examples
--------
This is how to instantiate a `DarkMatterAnnihilationSpectralModel` model::
from astropy import units as u
from gammapy.astro.darkmatter import DarkMatterAnnihilationSpectralModel
channel = "b"
massDM = 5000*u.Unit("GeV")
jfactor = 3.41e19 * u.Unit("GeV2 cm-5")
modelDM = DarkMatterAnnihilationSpectralModel(mass=massDM, channel=channel, jfactor=jfactor) # noqa: E501
References
----------
* `2011JCAP...03..051 <https://ui.adsabs.harvard.edu/abs/2011JCAP...03..051C>`_
"""
THERMAL_RELIC_CROSS_SECTION = 3e-26 * u.Unit("cm3 s-1")
"""Thermally averaged annihilation cross-section"""
scale = Parameter(
"scale",
1,
unit="",
interp="log",
is_norm=True,
)
tag = ["DarkMatterAnnihilationSpectralModel", "dm-annihilation"]
def __init__(self, mass, channel, scale=scale.quantity, jfactor=1, z=0, k=2):
self.k = k
self.z = z
self.mass = u.Quantity(mass)
self.channel = channel
self.jfactor = u.Quantity(jfactor)
self.primary_flux = PrimaryFlux(mass, channel=self.channel).table_model
super().__init__(scale=scale)
[docs] def evaluate(self, energy, scale):
"""Evaluate dark matter annihilation model."""
flux = (
scale
* self.jfactor
* self.THERMAL_RELIC_CROSS_SECTION
* self.primary_flux(energy=energy * (1 + self.z))
/ self.k
/ self.mass
/ self.mass
/ (4 * np.pi)
)
return flux
[docs] def to_dict(self, full_output=False):
data = super().to_dict(full_output=full_output)
data["spectral"]["channel"] = self.channel
data["spectral"]["mass"] = self.mass.to_string()
data["spectral"]["jfactor"] = self.jfactor.to_string()
data["spectral"]["z"] = self.z
data["spectral"]["k"] = self.k
return data
[docs] @classmethod
def from_dict(cls, data):
"""Create spectral model from dict
Parameters
----------
data : dict
Dict with model data
Returns
-------
model : `DarkMatterAnnihilationSpectralModel`
Dark matter annihilation spectral model
"""
data = data["spectral"]
data.pop("type")
parameters = data.pop("parameters")
scale = [p["value"] for p in parameters if p["name"] == "scale"][0]
return cls(scale=scale, **data)
SPECTRAL_MODEL_REGISTRY.append(DarkMatterAnnihilationSpectralModel)