def __init__(self,
log10MeV,
g=1,
m=1,
nsim=1,
B0=10.,
seed=None,
ppb=10,
lambda_min=0.7,
lambda_max=35.,
q=-2.80):
self.log10MeV = log10MeV
self.B0 = B0
self.nsim = nsim
self.g = g
self.m = m
self.seed = seed
self._seed = seed
self.ppb = ppb
self.pin = np.diag((1.0, 1.0, 0.)) * 0.5
self.q = q
self.kL = 2. * np.pi / lambda_max
self.kH = 2. * np.pi / lambda_min
# self.set_up_energy()
self.alp = ALP(self.m, self.g)
self.source = Source(z=0.017559, ra='03h19m48.1s', dec='+41d30m42s')
def propagation(self, EGeV, m=1., g=1., B0=10., seed=None, nsim=1):
'''Runs the propagation in magnetic fields, copied from me-manu, NGC1257 example notebook.
Returns: Probabilities of finding photon (transversal1, 2) and ALP.
Currently not used. Rather use read_probs() to use pre-computed probabilities saving time and thus
being able to run on standard BIRD-computation slots.
'''
alp = ALP(m, g)
ngc1275 = Source(z=0.017559, ra='03h19m48.1s', dec='+41d30m42s')
pin = np.diag((1., 1., 0.)) * 0.5
lambda_max = 35.
lambda_min = 0.7
kL = 2. * np.pi / lambda_max
kH = 2. * np.pi / lambda_min
m = ModuleList(alp, ngc1275, pin=pin, EGeV=EGeV)
print('m:'), m.alp.m
print('g:'), m.alp.g
print('B:'), B0
m.add_propagation(
"ICMGaussTurb",
0, # position of module counted from the source.
nsim=nsim, # number of random B-field realizations
B0=B0, # rms of B field
n0=39., # normalization of electron density
n2=
4.05, # second normalization of electron density, see Churazov et al. 2003, Eq. 4
r_abell=500., # extension of the cluster
r_core=
80., # electron density parameter, see Churazov et al. 2003, Eq. 4
r_core2=
280., # electron density parameter, see Churazov et al. 2003, Eq. 4
beta=
1.2, # electron density parameter, see Churazov et al. 2003, Eq. 4
beta2=
0.58, # electron density parameter, see Churazov et al. 2003, Eq. 4
eta=0.5, # scaling of B-field with electron denstiy
kL=
kL, # maximum turbulence scale in kpc^-1, taken from A2199 cool-core cluster, see Vacca et al. 2012
kH=
kH, # minimum turbulence scale, taken from A2199 cool-core cluster, see Vacca et al. 2012
q=-2.80, # turbulence spectral index, taken from A2199 cool-core cluster, see Vacca et al. 2012
seed=
seed # random seed for reproducability, set to None for random seed.
)
m.add_propagation(
"EBL", 1, model='dominguez'
) # EBL attenuation comes second, after beam has left cluster
m.add_propagation(
"GMF", 2, model='jansson12',
model_sum='ASS') # finally, the beam enters the Milky Way Field
px, py, pa = m.run()
self.px = px
self.py = py
self.pa = pa
self.p = px + py
def __init__(self,
walkerfile,
Mprog=10.,
cosmo=FlatLambdaCDM(H0=0.7 * 100. * u.km / u.s / u.Mpc,
Tcmb0=2.725 * u.K,
Om0=0.3)):
"""
Init the class
Parameters
----------
walkerfile: str
path to MOSFIT results file which contains the walkers
{options}
Mprog: float
mass of progenitor in solar masses, currently only 10. and 18. solar masses
are implemented
cosmo: `astropy.cosmology.FlatLambdaCDM`
the chosen cosmology. Default: 737
"""
with open(walkerfile, 'r') as f:
data = json.loads(f.read())
if 'name' not in data:
data = data[list(data.keys())[0]]
# SN coordinates
self._c = SkyCoord(ra=data['ra'][0]['value'],
dec=data['dec'][0]['value'],
unit=(u.hourangle, u.deg))
self._z = np.mean([
float(data['redshift'][i]['value'])
for i in range(len(data['redshift']))
])
self._src = Source(z=self._z,
ra=float(self._c.ra.value),
dec=float(self._c.dec.value))
self._cosmo = cosmo
# class to compute ALP flux
self._Mprog = Mprog
self._alp = ALPSNSignal(Mprog=Mprog)
# constant to calculate flux:
dl = self._cosmo.luminosity_distance(self._z)
self.fluxconstant = 1. / 4. / np.pi / dl.to('cm').value**2.
def __init__(self,
walkerfile=None,
ra=None,
dec=None,
Mprog=10.,
z=None,
cosmo=FlatLambdaCDM(H0=0.7 * 100. * u.km / u.s / u.Mpc,
Tcmb0=2.725 * u.K,
Om0=0.3)):
"""
Init the class
Parameters
----------
walkerfile: str or None
path to MOSFIT results file which contains the walkers
if None, ra, dec, and z have to be provided
ra: str or None
Right Ascension as string in degrees
dec: str or None
Declination as string in degrees
z: float or None
Redshift
{options}
Mprog: float
mass of progenitor in solar masses, currently only 10. and 18. solar masses
are implemented
cosmo: `astropy.cosmology.FlatLambdaCDM`
the chosen cosmology. Default: 737
"""
if walkerfile is not None:
with open(walkerfile, 'r') as f:
data = json.loads(f.read())
if 'name' not in data:
data = data[list(data.keys())[0]]
self._c = SkyCoord(ra=data['ra'][0]['value'],
dec=data['dec'][0]['value'],
unit=(u.hourangle, u.deg))
self._z = np.mean([
float(data['redshift'][i]['value'])
for i in range(len(data['redshift']))
])
else:
if ra is None or dec is None or z is None:
raise ValueError(
"No walkerfile given and no ra and dec provided!")
self._c = SkyCoord(ra=ra, dec=dec, unit=(u.deg, u.deg))
self._z = z
# SN coordinates
self._src = Source(z=self._z,
ra=float(self._c.ra.value),
dec=float(self._c.dec.value))
self._cosmo = cosmo
# class to compute ALP flux
self._Mprog = Mprog
self._alp = ALPSNSignal(Mprog=Mprog)
# constant to calculate flux:
dl = self._cosmo.luminosity_distance(self._z)
self.fluxconstant = 1. / 4. / np.pi / dl.to('cm').value**2.
g_space = np.logspace(-1., 2., num=30, base=10.0,
endpoint=True) # in 1e-11 1/GeV
m_space = np.logspace(-1., 2., num=30, base=10.0, endpoint=True) # in neV
grid = np.zeros((g_space.shape[0], m_space.shape[0], 2))
for i in range(g_space.shape[0]):
for j in range(m_space.shape[0]):
grid[i, j, :] = g_space[i], m_space[j]
grid = grid.reshape((m_space.shape[0] * g_space.shape[0], 2))
# prob dont need those two, later done in for loop
#g = grid[input_num, 0]
#m = grid[input_num, 1]
'''Set up ALP'''
ngc1275 = Source(z=0.017559, ra='03h19m48.1s', dec='+41d30m42s')
pin = np.diag((1., 1., 0.)) * 0.5
lambda_max = 35.
lambda_min = 0.7
kL = 2. * np.pi / lambda_max
kH = 2. * np.pi / lambda_min
'''Energy binning related stuff goes here'''
log10MeV = np.loadtxt(cwd + '/energy_bins.dat')
# full_length = log10MeV.shape[0]
# half_length = int(np.ceil(full_length / 2))
# if part == 1:
# log10MeV = log10MeV[0:half_length]
# elif part == 2:
# log10MeV = log10MeV[half_length:]
EGeV = np.power(10., log10MeV - 3.)
nbins = EGeV.shape[0]
# initial polarization
pin = np.diag((0.,0.,1.))
# cosmology
cosmo = FlatLambdaCDM(H0 = 70., Om0 = 0.3)
# loop over the sntable and ALP masses
c = OrderedDict() # columns for new table
c['name'] = tsn['name'].data
c['time'] = []
for t in tsn:
src = Source(z = float(t['z']),
ra = float(t['ra']),
dec = float(t['dec']))
mod = ModuleList(ALP(m=1.,g=args.gref), src, pin = pin, EGeV = EMeV / 1e3)
mod.add_propagation("GMF",0, model = 'jansson12', model_sum = 'ASS')
c['time'].append(ts)
for i,m in enumerate(mneV):
if not '{0:.3f}'.format(m) in c.keys():
c['{0:.3f}'.format(m)] = []
mod.alp.m = m
px,py,pa = mod.run(multiprocess=2)
# calculate photon flux in photons / MeV / s / cm^2:
d = cosmo.luminosity_distance(t['z'])