def dscM(l, en, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density,
and update the state-transition matrix modVAC to the current time/position.
"""
global lCache, aMSW, modVAC
# if l did not change, the update is unnecessary
if l == lCache:
return
# modVAC is the time-dependent state-transition matrix that brings a
# state vector to the interaction basis, i.e., to the basis where
# the vacuum oscillations are flat
if isAnti:
modVAC = dot(svdVAC0a * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2a)
else:
modVAC = dot(svdVAC0n * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2n)
# <==> modVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*(L-l)))), svdVAC2)
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= rICore:
aMSW = aMSWWoRhoICore * profInt(r)
elif r <= rOCore:
aMSW = aMSWWoRhoOCore * profInt(r)
else:
aMSW = aMSWWoRho * profInt(r)
lCache = l
def dscM(l, en, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density,
and update the state-transition matrix modVAC to the current time/position.
"""
global lCache, aMSW, modVAC
# if l did not change, the update is unnecessary
if l == lCache:
return
# modVAC is the time-dependent state-transition matrix that brings a state
# vector to the interaction basis, i.e., to the basis where the vacuum
# oscillations are flat; see calcProb docstring for magic-number explanation
if isAnti:
modVAC = dot(svdVAC0a * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2a)
else:
modVAC = dot(svdVAC0n * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2n)
# <==> modVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*(L-l)))), svdVAC2)
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= rICore:
aMSW = aMSWWoRhoICore * profInt(r)
elif r <= rOCore:
aMSW = aMSWWoRhoOCore * profInt(r)
else:
aMSW = aMSWWoRho * profInt(r)
lCache = l
def __get_normal_order(self, key, op):
l1, l2 = key
# assert(l1 != l2)
if l1 == l2:
print('wrong position for two body gate.')
if isinstance(op, tuple):
# assert(len(op)==2 and op[0].rank==3 and op[1].rank==3)
# assert((l1[0] == l2[0] and l1[1]+1==l2[1]) or (l1[0]+1==l2[0] and l1[1]==l2[1]))
if not (len(op) == 2 and op[0].rank == 3 and op[1].rank == 3):
raise ValueError('wrong input op for two body gate.')
if not ((l1[0] == l2[0] and l1[1] + 1 == l2[1]) or
(l1[0] + 1 == l2[0] and l1[1] == l2[1])):
raise ValueError('wrong position for two body gate.')
else:
op = astensor(op)
# assert(len(l1)==2 and len(l2)==2)
if not (len(l1) == 2 and len(l2) == 2):
raise ValueError('wrong position for two body gate.')
if op.rank == 2:
# assert(op.shape==(4,4) or op.shape==(16,16))
if op.shape != (4, 4):
raise ValueError('wrong op shape for two body gate.')
s = int(ssqrt(op.shape[0]))
op = op.reshape((s, s, s, s))
else:
# assert(op.rank==4 and (op.shape==(2,2,2,2) or op.shape==(4,4,4,4)))
if op.shape != (2, 2, 2, 2):
raise ValueError('wrong op shape for two body gate.')
if ((l1[0] == l2[0] and l1[1] == l2[1] + 1)
or (l1[0] == l2[0] + 1 and l1[1] == l2[1])):
op = op.transpose((1, 0, 3, 2))
key = (l2, l1)
op = split_bondmpo(op)
return key, op
def dscM(l, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density.
"""
global lCache, aMSW
# if l did not change, the update is unnecessary
if l == lCache:
return
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= self.earthModel.rICore:
aMSW = aMSWWoRhoICore * self.earthModel.profInt(r)
elif r <= self.earthModel.rOCore:
aMSW = aMSWWoRhoOCore * self.earthModel.profInt(r)
else:
aMSW = aMSWWoRho * self.earthModel.profInt(r)
lCache = l
def dscM(l, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density.
"""
global lCache, aMSW
# if l did not change, the update is unnecessary
if l == lCache:
return
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= self.earthModel.rICore:
aMSW = aMSWWoRhoICore * self.earthModel.profInt(r)
elif r <= self.earthModel.rOCore:
aMSW = aMSWWoRhoOCore * self.earthModel.profInt(r)
else:
aMSW = aMSWWoRho * self.earthModel.profInt(r)
lCache = l
def calcProb(inTuple):
"""
Calculate the oscillation probabilities of an individual nu.
The constant -2.533866j that appears throughout this function is -j*1.266933,
where j is the imaginary unit and the other factor is GeV*fm/(4*hbar*c), which
is the factor required to transition from natural units to SI units.
It is hard-coded as it is not a free parameter and will never change.
"""
# python 3 does not support tuple parameter unpacking anymore
mcType, mcEn, mcZen = inTuple
def dscM(l, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density.
"""
global lCache, aMSW
# if l did not change, the update is unnecessary
if l == lCache:
return
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= self.earthModel.rICore:
aMSW = aMSWWoRhoICore * self.earthModel.profInt(r)
elif r <= self.earthModel.rOCore:
aMSW = aMSWWoRhoOCore * self.earthModel.profInt(r)
else:
aMSW = aMSWWoRho * self.earthModel.profInt(r)
lCache = l
def f(l, psi, en, zen):
dscM(l, zen)
# see calcProb docstring for magic-number explanation
if isAnti:
return -2.533866j/en * dot((VACa + aMSW), psi)
else:
return -2.533866j/en * dot((VACn + aMSW), psi)
def jac(l, psi, en, zen):
dscM(l, zen)
if isAnti:
return -2.533866j/en * (VACa + aMSW)
else:
return -2.533866j/en * (VACn + aMSW)
try:
mcType = self.mcTypeDict[mcType]
except KeyError:
raise KeyError("The mcType %d is not known to nuCraft!" % mcType)
isAnti = mcType[0] == -1
# inefficient performance-wise, but nicer code, and vacuum is fast enough anyway
if vacuum:
aMSWWoRho = diag(zeros_like(self.earthModel.A))
aMSWWoRhoOCore = aMSWWoRho
aMSWWoRhoICore = aMSWWoRho
else:
aMSWWoRho = diag(mcType[0] * self.earthModel.A * mcEn)
aMSWWoRhoOCore = diag(mcType[0] * self.earthModel.AOCore * mcEn)
aMSWWoRhoICore = diag(mcType[0] * self.earthModel.AICore * mcEn)
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=5, with_jacobian=True,
nsteps=12000000, atol=numPrec*2e-2, rtol=numPrec*2e-2)
solver.set_initial_value(mcType[1], L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
if not solver.successful():
raise ArithmeticError("ODE solver was not successful, check for warnings about 'excess work done'!")
prob = square(absolute(solver.y))
if abs(1-sum(prob)) > numPrec:
warnings.warn("The computed unitarity does not meet the specified precision: %.2e > %.2e" % (abs(1-sum(prob)), numPrec))
return prob
def calcProb(inTuple):
"""
Calculate the oscillation probabilities of an individual nu.
The constant -2.533866j that appears throughout this function is -2*j*1.266933,
where j is the imaginary unit and the other factor is GeV*fm/(4*hbar*c), which
is the factor required to transition from natural units to SI units.
It is hard-coded as it is not a free parameter and will never change.
"""
# python 3 does not support tuple parameter unpacking anymore
mcType, mcEn, mcZen = inTuple
def dscM(l, en, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density,
and update the state-transition matrix modVAC to the current time/position.
"""
global lCache, aMSW, modVAC
# if l did not change, the update is unnecessary
if l == lCache:
return
# modVAC is the time-dependent state-transition matrix that brings a state
# vector to the interaction basis, i.e., to the basis where the vacuum
# oscillations are flat; see calcProb docstring for magic-number explanation
if isAnti:
modVAC = dot(svdVAC0a * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2a)
else:
modVAC = dot(svdVAC0n * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2n)
# <==> modVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*(L-l)))), svdVAC2)
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= rICore:
aMSW = aMSWWoRhoICore * profInt(r)
elif r <= rOCore:
aMSW = aMSWWoRhoOCore * profInt(r)
else:
aMSW = aMSWWoRho * profInt(r)
lCache = l
def f(l, psi, en, zen):
dscM(l, en, zen)
return -2.533866j/en * dot(modVAC, aMSW*dot(psi, conj(modVAC)))
# <==> return -2.533866j/en * dot(modVAC, dot(diag(aMSW), dot(conj(modVAC).T, psi)))
def jac(l, psi, en, zen):
dscM(l, en, zen)
return -2.533866j/en * dot(modVAC*aMSW, conj(modVAC).T)
# <==> return -2.533866j/en * dot(dot(modVAC, diag(aMSW)), conj(modVAC).T)
try:
mcType = self.mcTypeDict[mcType]
except KeyError:
raise KeyError("The mcType %d is not known to nuCraft!" % mcType)
isAnti = mcType[0] == -1
# inefficient performance-wise, but nicer code, and vacuum is fast enough anyway
if vacuum:
aMSWWoRho = zeros_like(self.earthModel.A)
aMSWWoRhoOCore = aMSWWoRho
aMSWWoRhoICore = aMSWWoRho
else:
aMSWWoRho = mcType[0] * self.earthModel.A * mcEn
aMSWWoRhoOCore = mcType[0] * self.earthModel.AOCore * mcEn
aMSWWoRhoICore = mcType[0] * self.earthModel.AICore * mcEn
# depending on the mode, get a list of interaction altitude tuples, see method doc string;
# the first number of the tuples is the weight, the second the distance of the interaction
# point to the center of the Earth; the weights have to add up to 1.
if atmMode == 3:
# first get the tuples and propagate only the lowest-altitude neutrino:
rAtmTuples = self.InteractionAlt(mcType, mcEn, mcZen, 2)
rAtm = rAtmTuples[0][1]
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcEn, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=5, with_jacobian=True,
nsteps=1200000, atol=numPrec*2e-3, rtol=numPrec*2e-3)
solver.set_initial_value(dot(modVAC, mcType[1]), L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
# <==> endVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*L))), svdVAC2)
results = [rAtmTuples[0][0] * square(absolute( dot(conj(endVAC).T, solver.y) ))]
# now for all the other neutrinos, add the missing lengths as vacuum oscillations
# at the end of the track; keep in mind that atmosphere is always handled as vacuum
for rAtmWeight, rAtm in rAtmTuples[1:]:
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
results.append( rAtmWeight * square(absolute( dot(conj(endVAC).T, solver.y) )) )
else:
# in this case, just stupidly propagate every neutrino in the list...
results = []
for rAtmWeight, rAtm in self.InteractionAlt(mcType, mcEn, mcZen, atmMode):
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcEn, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=5, with_jacobian=True,
nsteps=1200000, atol=numPrec*2e-3, rtol=numPrec*2e-3)
solver.set_initial_value(dot(modVAC, mcType[1]), L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
# <==> endVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*L))), svdVAC2)
results.append( rAtmWeight * square(absolute( dot(conj(endVAC).T, solver.y) )) )
if not solver.successful():
raise ArithmeticError("ODE solver was not successful, check for warnings about 'excess work done'!")
prob = sum(results, 0)
if abs(1-sum(prob)) > numPrec:
warnings.warn("The computed unitarity does not meet the specified precision: %.2e > %.2e" % (abs(1-sum(prob)), numPrec))
return prob
def calcProb(inTuple):
"""
Calculate the oscillation probabilities of an individual nu.
"""
# python 3 does not support tuple parameter unpacking anymore
mcType, mcEn, mcZen = inTuple
def dscM(l, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density.
"""
global lCache, aMSW
# if l did not change, the update is unnecessary
if l == lCache:
return
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= self.earthModel.rICore:
aMSW = aMSWWoRhoICore * self.earthModel.profInt(r)
elif r <= self.earthModel.rOCore:
aMSW = aMSWWoRhoOCore * self.earthModel.profInt(r)
else:
aMSW = aMSWWoRho * self.earthModel.profInt(r)
lCache = l
def f(l, psi, en, zen):
dscM(l, zen)
if isAnti:
return -2.533866j/en * dot((VACa + aMSW), psi)
else:
return -2.533866j/en * dot((VACn + aMSW), psi)
def jac(l, psi, en, zen):
dscM(l, zen)
if isAnti:
return -2.533866j/en * (VACa + aMSW)
else:
return -2.533866j/en * (VACn + aMSW)
try:
mcType = self.mcTypeDict[mcType]
except KeyError:
raise KeyError("The mcType %d is not known to nuCraft!" % mcType)
isAnti = mcType[0] == -1
# inefficient performance-wise, but nicer code, and vacuum is fast enough anyway
if vacuum:
aMSWWoRho = diag(zeros_like(self.earthModel.A))
aMSWWoRhoOCore = aMSWWoRho
aMSWWoRhoICore = aMSWWoRho
else:
aMSWWoRho = diag(mcType[0] * self.earthModel.A * mcEn)
aMSWWoRhoOCore = diag(mcType[0] * self.earthModel.AOCore * mcEn)
aMSWWoRhoICore = diag(mcType[0] * self.earthModel.AICore * mcEn)
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=4, with_jacobian=True,
nsteps=1200000, min_step=0.0002, max_step=500.,
atol=.1e-6, rtol=.1e-6)
solver.set_initial_value(mcType[1], L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
return square(absolute(solver.y))
def calcProb(inTuple):
"""
Calculate the oscillation probabilities of an individual nu.
"""
# python 3 does not support tuple parameter unpacking anymore
mcType, mcEn, mcZen = inTuple
def dscM(l, en, zen):
"""
Update the MSW-induced mass-squared matrix aMSW with the current density,
and update the state-transition matrix modVAC to the current time/position.
"""
global lCache, aMSW, modVAC
# if l did not change, the update is unnecessary
if l == lCache:
return
# modVAC is the time-dependent state-transition matrix that brings a
# state vector to the interaction basis, i.e., to the basis where
# the vacuum oscillations are flat
if isAnti:
modVAC = dot(svdVAC0a * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2a)
else:
modVAC = dot(svdVAC0n * exp(-2.533866j/en*svdVAC1*(L-l)), svdVAC2n)
# <==> modVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*(L-l)))), svdVAC2)
# distance from the center of Earth
r = ssqrt( l*l + rDet*rDet - 2*l*rDet*scos(pi - zen) )
if r <= rICore:
aMSW = aMSWWoRhoICore * profInt(r)
elif r <= rOCore:
aMSW = aMSWWoRhoOCore * profInt(r)
else:
aMSW = aMSWWoRho * profInt(r)
lCache = l
def f(l, psi, en, zen):
dscM(l, en, zen)
return -2.533866j/en * dot(modVAC, aMSW*dot(psi, conj(modVAC)))
# <==> return -2.533866j/en * dot(modVAC, dot(diag(aMSW), dot(conj(modVAC).T, psi)))
def jac(l, psi, en, zen):
dscM(l, en, zen)
return -2.533866j/en * dot(modVAC*aMSW, conj(modVAC).T)
# <==> return -2.533866j/en * dot(dot(modVAC, diag(aMSW)), conj(modVAC).T)
try:
mcType = self.mcTypeDict[mcType]
except KeyError:
raise KeyError("The mcType %d is not known to nuCraft!" % mcType)
isAnti = mcType[0] == -1
# inefficient performance-wise, but nicer code, and vacuum is fast enough anyway
if vacuum:
aMSWWoRho = zeros_like(self.earthModel.A)
aMSWWoRhoOCore = aMSWWoRho
aMSWWoRhoICore = aMSWWoRho
else:
aMSWWoRho = mcType[0] * self.earthModel.A * mcEn
aMSWWoRhoOCore = mcType[0] * self.earthModel.AOCore * mcEn
aMSWWoRhoICore = mcType[0] * self.earthModel.AICore * mcEn
# depending on the mode, get a list of interaction altitude tuples, see method doc string;
# the first number of the tuples is the weight, the second the distance of the interaction
# point to the center of the Earth; the weights have to add up to 1.
if atmMode == 3:
# first get the tuples and propagate only the lowest-altitude neutrino:
rAtmTuples = self.InteractionAlt(mcType, mcEn, mcZen, 2)
rAtm = rAtmTuples[0][1]
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcEn, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=4, with_jacobian=True,
nsteps=120000, min_step=0.0002, max_step=500.,
atol=numPrec*2e-3, rtol=numPrec*2e-3)
solver.set_initial_value(dot(modVAC, mcType[1]), L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
# <==> endVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*L))), svdVAC2)
results = [rAtmTuples[0][0] * square(absolute( dot(conj(endVAC).T, solver.y) ))]
# now for all the other neutrinos, add the missing lengths as vacuum oscillations
# at the end of the track; keep in mind that atmosphere is always handled as vacuum
for rAtmWeight, rAtm in rAtmTuples[1:]:
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
results.append( rAtmWeight * square(absolute( dot(conj(endVAC).T, solver.y) )) )
else:
# in this case, just stupidly propagate every neutrino in the list...
results = []
for rAtmWeight, rAtm in self.InteractionAlt(mcType, mcEn, mcZen, atmMode):
L = ssqrt( rAtm*rAtm + rDet*rDet - 2*rAtm*rDet*scos( mcZen - arcsin(sin(pi-mcZen)/rAtm*rDet) ) )
dscM(L, mcEn, mcZen)
solver = integrate.ode(f, jac).set_integrator('zvode', method='adams', order=4, with_jacobian=True,
nsteps=120000, min_step=0.0002, max_step=500.,
atol=numPrec*2e-3, rtol=numPrec*2e-3)
solver.set_initial_value(dot(modVAC, mcType[1]), L).set_f_params(mcEn, mcZen).set_jac_params(mcEn, mcZen)
solver.integrate(0.)
if isAnti:
endVAC = dot(svdVAC0a * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2a)
else:
endVAC = dot(svdVAC0n * exp(-2.533866j/mcEn*svdVAC1*L), svdVAC2n)
# <==> endVAC = dot(dot(svdVAC0, diag(exp(-2.533866j/mcEn*svdVAC1*L))), svdVAC2)
results.append( rAtmWeight * square(absolute( dot(conj(endVAC).T, solver.y) )) )
prob = sum(results, 0)
if abs(1-sum(prob)) > numPrec:
warnings.warn("The computed unitarity does not meet the specified precision: %.2e > %.2e" % (abs(1-sum(prob)), numPrec))
return prob
