def ElectronEblAbsorbedSynIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = 10**pars[0] / u.eV
e_break = (10**pars[1]) * u.TeV
alpha1 = pars[2]
alpha2 = pars[3]
B = pars[4] * u.uG
# Define the redshift of the source, and absorption model
redshift = pars[5] * u.dimensionless_unscaled
EBL_transmitance = EblAbsorptionModel(redshift, "Dominguez")
# Initialize instances of the particle distribution and radiative models
BPL = BrokenPowerLaw(amplitude, 1.0 * u.TeV, e_break, alpha1, alpha2)
# Compute IC on a CMB component
IC = InverseCompton(BPL, seed_photon_fields=["CMB"], Eemin=10 * u.GeV)
SYN = Synchrotron(BPL, B=B)
# compute flux at the energies given in data['energy']
model = EBL_transmitance.transmission(data) * IC.flux(
data, distance=1.0 * u.kpc) + SYN.flux(data, distance=1.0 * u.kpc)
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stored in the sampler metadata
# blobs.
return model, IC.compute_We(Eemin=1 * u.TeV)
def ElectronIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = pars[0] / u.eV
alpha = pars[1]
e_cutoff = (10 ** pars[2]) * u.TeV
# Initialize instances of the particle distribution and radiative model
ECPL = ExponentialCutoffPowerLaw(amplitude, 10.0 * u.TeV, alpha, e_cutoff)
# Compute IC on CMB and on a FIR component with values from GALPROP for the
# position of RXJ1713
IC = InverseCompton(
ECPL,
seed_photon_fields=[
"CMB",
["FIR", 26.5 * u.K, 0.415 * u.eV / u.cm ** 3],
],
Eemin=100 * u.GeV,
)
# compute flux at the energies given in data['energy'], and convert to units
# of flux data
model = IC.flux(data, distance=1.0 * u.kpc).to(data["flux"].unit)
# Save this realization of the particle distribution function
elec_energy = np.logspace(11, 15, 100) * u.eV
nelec = ECPL(elec_energy)
# Compute and save total energy in electrons above 1 TeV
We = IC.compute_We(Eemin=1 * u.TeV)
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stores in the sampler metadata
# blobs.
return model, (elec_energy, nelec), We
def ElectronSynIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = 10 ** pars[0] / u.eV
alpha = pars[1]
e_cutoff = (10 ** pars[2]) * u.TeV
B = pars[3] * u.uG
# Initialize instances of the particle distribution and radiative models
ECPL = ExponentialCutoffPowerLaw(amplitude, 10.0 * u.TeV, alpha, e_cutoff)
# Compute IC on CMB and on a FIR component with values from GALPROP for the
# position of RXJ1713
IC = InverseCompton(
ECPL,
seed_photon_fields=[
"CMB",
["FIR", 26.5 * u.K, 0.415 * u.eV / u.cm ** 3],
],
Eemin=100 * u.GeV,
)
SYN = Synchrotron(ECPL, B=B)
# compute flux at the energies given in data['energy']
model = IC.flux(data, distance=1.0 * u.kpc) + SYN.flux(
data, distance=1.0 * u.kpc
)
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stored in the sampler metadata
# blobs.
return model, IC.compute_We(Eemin=1 * u.TeV)
def ElectronIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = pars[0] / u.eV
alpha = pars[1]
e_cutoff = (10**pars[2]) * u.TeV
# Initialize instances of the particle distribution and radiative model
ECPL = ExponentialCutoffPowerLaw(amplitude, 10. * u.TeV, alpha, e_cutoff)
IC = InverseCompton(ECPL,
seed_photon_fields=[
'CMB', ['FIR', 26.5 * u.K, 0.415 * u.eV / u.cm**3]
])
# compute flux at the energies given in data['energy'], and convert to
# units of flux data
model = IC.flux(data, distance=1.0 * u.kpc)
# Save this realization of the particle distribution function
elec_energy = np.logspace(11, 15, 100) * u.eV
nelec = ECPL(elec_energy)
# Compute and save total energy in electrons above 1 TeV
We = IC.compute_We(Eemin=1 * u.TeV)
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stores in the sampler metadata
# blobs.
return model, (elec_energy, nelec), We
def ElectronSynIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = 10**pars[0] / u.eV
alpha = pars[1]
e_cutoff = (10**pars[2]) * u.TeV
B = pars[3] * u.uG
# Initialize instances of the particle distribution and radiative models
ECPL = ExponentialCutoffPowerLaw(amplitude, 10. * u.TeV, alpha, e_cutoff)
# Compute IC on CMB and on a FIR component with values from GALPROP for the
# position of RXJ1713
IC = InverseCompton(ECPL,
seed_photon_fields=[
'CMB', ['FIR', 26.5 * u.K, 0.415 * u.eV / u.cm**3]
],
Eemin=100 * u.GeV)
SYN = Synchrotron(ECPL, B=B)
# compute flux at the energies given in data['energy']
model = (IC.flux(data, distance=1.0 * u.kpc) +
SYN.flux(data, distance=1.0 * u.kpc))
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stored in the sampler metadata
# blobs.
return model, IC.compute_We(Eemin=1 * u.TeV)
def ElectronEblAbsorbedSynIC(pars, data):
# Match parameters to ECPL properties, and give them the appropriate units
amplitude = 10**pars[0] / u.eV
e_break = (10**pars[1]) * u.TeV
alpha1 = pars[2]
alpha2 = pars[3]
B = pars[4] * u.uG
# Define the redshift of the source, and absorption model
redshift = pars[5] * u.dimensionless_unscaled
EBL_transmitance = EblAbsorptionModel(redshift, 'Dominguez')
# Initialize instances of the particle distribution and radiative models
BPL = BrokenPowerLaw(amplitude, 1. * u.TeV, e_break, alpha1, alpha2)
# Compute IC on a CMB component
IC = InverseCompton(
BPL,
seed_photon_fields=['CMB'],
Eemin=10 * u.GeV)
SYN = Synchrotron(BPL, B=B)
# compute flux at the energies given in data['energy']
model = (EBL_transmitance.transmission(data) * IC.flux(data, distance=1.0 * u.kpc) +
SYN.flux(data, distance=1.0 * u.kpc))
# The first array returned will be compared to the observed spectrum for
# fitting. All subsequent objects will be stored in the sampler metadata
# blobs.
return model, IC.compute_We(Eemin=1 * u.TeV)
def flare_rad(index, LE_cutoff, Ee_syn_max, B_flare, Ecut_0):
ECPL = ExponentialCutoffPowerLaw(amplitude=amp0 / u.eV,
e_0=1 * u.TeV,
alpha=index,
e_cutoff=Ecut_0)
SYN = Synchrotron(ECPL, B=B_flare, Eemin=LE_cutoff, Eemax=Ee_syn_max)
amp_cor = fitfactor(data_flare, SYN) # Fit particle distribution prefactor
# Fit particle cutoff, with analytic initial value
Ecut_flare = fitcutoff(Ecut_0, data_flare, amp0 * amp_cor, index, B_flare,
LE_cutoff, Ee_syn_max)
print('Correct ecut: ', Ecut_flare.to(u.PeV))
# Final particle spectrum and synchrotron
ECPL = ExponentialCutoffPowerLaw(amplitude=amp0 * amp_cor / u.eV,
e_0=1 * u.TeV,
alpha=index,
e_cutoff=Ecut_flare)
SYN = Synchrotron(ECPL, B=B_flare, Eemin=LE_cutoff, Eemax=Ee_syn_max)
if flarename == '2011':
Rflare = 2.8e-4 * u.pc ## 3.2 * u.pc, 2.8e-4, 1.7e-4
elif flarename == '2013':
Rflare = 1.7e-4 * u.pc
else:
Rflare == 3.2 * u.pc
Esy = np.logspace(0.0, 12, 100) * u.eV #np.exp(14)
Lsy = SYN.flux(Esy, distance=0 * u.cm) # use distance 0 to get luminosity
phn_sy = Lsy / (4 * np.pi * Rflare**2 * c) * 2.24
fields = [
'CMB', ['FIR', 70 * u.K, 0.5 * u.eV / u.cm**3],
['NIR', 5000 * u.K, 1 * u.eV / u.cm**3], ['SSC', Esy, phn_sy]
]
IC = InverseCompton(ECPL,
seed_photon_fields=fields,
Eemin=LE_cutoff,
Eemax=Ee_syn_max)
We = IC.compute_We(Eemin=1 * u.TeV)
print('Estoy aqui: ', We)
return SYN, IC, amp_cor, We, Ecut_flare
