Source code for gammapy.astro.darkmatter.spectra

# 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)