def modDsN2(x):
N = 3
dds = 0
# ds = 0 # UNUSED
qx = cudahelpers.getqx()
ek = A * (math.sqrt((x[0])**2 + (x[1])**2))**2 + A * (eE0 / hOmg)**2
ekq = A * (math.sqrt((x[0] + qx)**2 +
(x[1] + 0)**2))**2 + A * (eE0 / hOmg)**2
xk = 2 * A * eE0 * math.sqrt((x[0])**2 + (x[1])**2) / hOmg**2
xkq = 2 * A * eE0 * math.sqrt((x[0] + qx)**2 + (x[1] + 0)**2) / hOmg**2
singrmatrix = numba.cuda.shared.array((6, N), dtype=numba.types.f8)
singzmatrix = numba.cuda.shared.array((4, N), dtype=numba.types.complex128)
n = 0
i = -(N - 1) / 2
for n in range(0, N):
nu = hOmg * i
chi = hOmg / 2
omicron = ek - chi + nu
phi = ekq - chi + nu
iota = ek + chi + nu
kappa = ekq + chi + nu
omisq = omicron**2
phisq = phi**2
iotasq = iota**2
kappasq = kappa**2
singrmatrix[0, n] = 2 * math.atan2(Gamm, omicron)
singrmatrix[1, n] = 2 * math.atan2(Gamm, phi)
singrmatrix[2, n] = 2 * math.atan2(Gamm, iota)
singrmatrix[3, n] = 2 * math.atan2(Gamm, kappa)
singzmatrix[0, n] = complex(0, 1) * math.log(Gammsq + omisq)
singzmatrix[1, n] = complex(0, 1) * math.log(Gammsq + phisq)
singzmatrix[2, n] = complex(0, 1) * math.log(Gammsq + iotasq)
singzmatrix[3, n] = complex(0, 1) * math.log(Gammsq + kappasq)
chinu = chi - nu
singrmatrix[4, n] = cudahelpers.my_heaviside(mu - chinu)
singrmatrix[5, n] = cudahelpers.my_heaviside(mu + chinu)
i = i + 1
size_dbl = 5 # 2N-1
dblrmatrix = numba.cuda.shared.array((5, size_dbl), dtype=numba.types.f8)
dblzmatrix = numba.cuda.shared.array((4, size_dbl),
dtype=numba.types.complex128)
i = -(N - 1)
for n in range(0, size_dbl):
xi = hOmg * i
zeta = ek - mu + xi
eta = ekq - mu + xi
zetasq = zeta**2
etasq = eta**2
dblrmatrix[0, n] = 2 * math.atan2(Gamm, zeta)
dblrmatrix[1, n] = 2 * math.atan2(Gamm, eta)
logged1 = math.log(Gammsq + zetasq)
logged2 = math.log(Gammsq + etasq)
dblzmatrix[0, n] = complex(0, logged1)
dblzmatrix[1, n] = complex(0, logged2)
dblrmatrix[2, n] = cudahelpers.besselj(i, xk)
dblrmatrix[3, n] = cudahelpers.besselj(i, xkq)
fac1i = ek - ekq + xi
fac2i = complex(fac1i, 2 * Gamm)
dblrmatrix[4, n] = fac1i
dblzmatrix[2, n] = fac2i
dblzmatrix[3, n] = fac2i - ek + ekq
i = i + 1
# This is implementing what Mahmoud and I discussed to construct these outside.
sdr00 = numba.cuda.shared.array((N, N), dtype=numba.types.f8)
sdr20 = numba.cuda.shared.array((N, N), dtype=numba.types.f8)
sdr11 = numba.cuda.shared.array((N, N), dtype=numba.types.f8)
sdr31 = numba.cuda.shared.array((N, N), dtype=numba.types.f8)
sdz00 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
sdz20 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
sdz11 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
sdz31 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
dd11 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
dd00 = numba.cuda.shared.array((N, N), dtype=numba.types.c16)
# Now to fill the arrays, we use a dummy variable that will be referenced below by the actual indices.
for i in range(0, N): # i will be indexed by s below
for j in range(
0, N
): # j will be indexed by alpha, beta, or gamma in the nested loops
ij = i + j
sdr00[i, j] = singrmatrix[0, j] - dblrmatrix[0, ij]
sdr20[i, j] = singrmatrix[2, j] - dblrmatrix[0, ij]
sdr11[i, j] = -singrmatrix[1, j] + dblrmatrix[1, ij]
sdr31[i, j] = -singrmatrix[3, j] + dblrmatrix[1, ij]
sdz00[i, j] = singzmatrix[0, j] + dblzmatrix[0, ij]
sdz20[i, j] = singzmatrix[2, j] + dblzmatrix[0, ij]
sdz11[i, j] = singzmatrix[1, j] + dblzmatrix[1, ij]
sdz31[i, j] = singzmatrix[3, j] + dblzmatrix[1, ij]
dd11[i, j] = dblrmatrix[1, ij] - dblzmatrix[1, ij]
dd00[i, j] = dblrmatrix[0, ij] + dblzmatrix[0, ij]
for n in range(0, N):
nmod = n + N - 1
for alpha in range(0, N):
for beta in range(0, N):
abdiff = alpha - beta + N - 1
for gamma in range(0, N):
bgdiff = beta - gamma + N - 1
agdiff = alpha - gamma + N - 1
d1 = -2 * complex(0, 1) * dblrmatrix[
4, bgdiff] * dblzmatrix[2, agdiff] * dblzmatrix[3,
abdiff]
d2 = -2 * complex(0, 1) * dblrmatrix[
4, abdiff] * dblzmatrix[2, agdiff] * dblzmatrix[3,
bgdiff]
for s in range(0, N):
smod = s + N - 1
p1p = dblrmatrix[4, bgdiff] * (sdr00[s, alpha] -
sdz00[s, alpha])
p2p = dblzmatrix[2, agdiff] * (singrmatrix[0, beta] -
dd00[s, beta] +
singzmatrix[0, beta])
p3p = dblzmatrix[3, abdiff] * (sdr11[s, gamma] -
sdz11[s, gamma])
p1m = dblrmatrix[4, bgdiff] * (sdr20[s, alpha] -
sdz20[s, alpha])
p2m = dblzmatrix[2, agdiff] * (singrmatrix[2, beta] -
dd00[s, beta] +
singzmatrix[2, beta])
p3m = dblzmatrix[3, abdiff] * (sdr31[s, gamma] -
sdz31[s, gamma])
omint1p = singrmatrix[4, s] * ((p1p + p2p + p3p) / d1)
omint1m = singrmatrix[5, s] * ((p1m + p2m + p3m) / d1)
pp1p = dblrmatrix[4, abdiff] * (sdr11[s, gamma] -
sdz11[s, gamma])
pp2p = dblzmatrix[2, agdiff] * (-singrmatrix[1, beta] +
dd11[s, beta] +
singzmatrix[1, beta])
pp3p = dblzmatrix[3, bgdiff] * (sdr00[s, alpha] -
sdz00[s, alpha])
pp1m = dblrmatrix[4, abdiff] * (sdr31[s, gamma] -
sdz31[s, gamma])
pp2m = dblzmatrix[2, agdiff] * (-singrmatrix[3, beta] +
dd11[s, beta] +
singzmatrix[3, beta])
pp3m = dblzmatrix[3, bgdiff] * (sdr20[s, alpha] -
sdz20[s, alpha])
omint2p = singrmatrix[4, s] * (
(pp1p + pp2p + pp3p) / d2)
omint2m = singrmatrix[5, s] * (
(pp1m + pp2m + pp3m) / d2)
for l in range(0, N):
lmod = l + N - 1
bess1 = dblrmatrix[3, gamma - nmod] * dblrmatrix[
3, gamma - lmod] * dblrmatrix[
2, beta - lmod] * dblrmatrix[
2, beta - smod] * dblrmatrix[
2, alpha -
smod] * dblrmatrix[2, alpha - nmod]
grgl = bess1 * (omint1p - omint1m)
bess2 = dblrmatrix[3, gamma - nmod] * dblrmatrix[
3, gamma - smod] * dblrmatrix[
3, beta - smod] * dblrmatrix[
3, beta - lmod] * dblrmatrix[
2, alpha -
lmod] * dblrmatrix[2, alpha - nmod]
glga = bess2 * (omint2p - omint2m)
dds = dds + Gamm * (grgl + glga)
return -4 * dds.real / math.pi**2
def modDsN2(x):
N = 3
dds = 0
# ds = 0 # UNUSED
qx = cudahelpers.getqx()
ek = A * (math.sqrt((x[0])**2 + (x[1])**2))**2 + A * (eE0 / hOmg)**2
ekq = A * (math.sqrt((x[0] + qx)**2 +
(x[1] + 0)**2))**2 + A * (eE0 / hOmg)**2
xk = 2 * A * eE0 * math.sqrt((x[0])**2 + (x[1])**2) / hOmg**2
xkq = 2 * A * eE0 * math.sqrt((x[0] + qx)**2 + (x[1] + 0)**2) / hOmg**2
singmatrix = numba.cuda.shared.array((10, N), dtype=numba.types.complex128)
n = 0
i = -(N - 1) / 2
while (i < ((N - 1) / 2 + 1)):
nu = hOmg * i
chi = hOmg / 2
omicron = ek - chi + nu
phi = ekq - chi + nu
iota = ek + chi + nu
kappa = ekq + chi + nu
omisq = omicron**2
phisq = phi**2
iotasq = iota**2
kappasq = kappa**2
singmatrix[0, n] = 2 * math.atan2(Gamm, omicron)
singmatrix[1, n] = 2 * math.atan2(Gamm, phi)
singmatrix[2, n] = 2 * math.atan2(Gamm, iota)
singmatrix[3, n] = 2 * math.atan2(Gamm, kappa)
singmatrix[4, n] = complex(0, 1) * math.log(Gammsq + omisq)
singmatrix[5, n] = complex(0, 1) * math.log(Gammsq + phisq)
singmatrix[6, n] = complex(0, 1) * math.log(Gammsq + iotasq)
singmatrix[7, n] = complex(0, 1) * math.log(Gammsq + kappasq)
chinu = chi - nu
singmatrix[8, n] = cudahelpers.my_heaviside(mu - chinu)
singmatrix[9, n] = cudahelpers.my_heaviside(mu + chinu)
i = i + 1
n = n + 1
#numba.cuda.syncthreads()
size_dbl = 5
dblmatrix = numba.cuda.shared.array((9, size_dbl),
dtype=numba.types.complex128)
n = 0
for i in range(-(N - 1), N, 1):
xi = hOmg * i
zeta = ek - mu + xi
eta = ekq - mu + xi
zetasq = zeta**2
etasq = eta**2
dblmatrix[0, n] = 2 * math.atan2(Gamm, zeta)
dblmatrix[1, n] = 2 * math.atan2(Gamm, eta)
logged1 = math.log(Gammsq + zetasq)
logged2 = math.log(Gammsq + etasq)
dblmatrix[2, n] = complex(0, logged1)
dblmatrix[3, n] = complex(0, logged2)
dblmatrix[4, n] = cudahelpers.besselj(i, xk)
dblmatrix[5, n] = cudahelpers.besselj(i, xkq)
fac1i = ek - ekq + xi
fac2i = complex(fac1i, 2 * Gamm)
dblmatrix[6, n] = fac1i
dblmatrix[7, n] = fac2i
dblmatrix[8, n] = fac2i - ek + ekq
n = n + 1
#numba.cuda.syncthreads()
for n in range(0, N):
for alpha in range(0, N):
for beta in range(0, N):
for gamma in range(0, N):
for s in range(0, N):
for l in range(0, N):
p1p = dblmatrix[6, beta - gamma + N - 1] * (
singmatrix[0, alpha] -
dblmatrix[0, s + alpha] -
singmatrix[4, alpha] + dblmatrix[2, s + alpha])
p2p = dblmatrix[7, alpha - gamma + N - 1] * (
singmatrix[0, beta] - dblmatrix[0, s + beta] +
singmatrix[4, beta] - dblmatrix[2, s + beta])
p3p = dblmatrix[8, alpha - beta + N - 1] * (
-singmatrix[1, gamma] +
dblmatrix[1, s + gamma] -
singmatrix[5, gamma] + dblmatrix[3, s + gamma])
p1m = dblmatrix[6, beta - gamma + N - 1] * (
singmatrix[2, alpha] -
dblmatrix[0, s + alpha] -
singmatrix[6, alpha] + dblmatrix[2, s + alpha])
p2m = dblmatrix[7, alpha - gamma + N - 1] * (
singmatrix[2, beta] - dblmatrix[0, s + beta] +
singmatrix[6, beta] - dblmatrix[2, s + beta])
p3m = dblmatrix[8, alpha - beta + N - 1] * (
-singmatrix[3, gamma] +
dblmatrix[1, s + gamma] -
singmatrix[7, gamma] + dblmatrix[3, s + gamma])
d1 = -2 * complex(0, 1) * dblmatrix[
6, beta - gamma + N -
1] * dblmatrix[7, alpha - gamma + N -
1] * dblmatrix[8, alpha - beta +
N - 1]
omint1p = singmatrix[8, s] * (
(p1p + p2p + p3p) / d1)
omint1m = singmatrix[9, s] * (
(p1m + p2m + p3m) / d1)
bess1 = dblmatrix[
5, gamma - n + N - 1] * dblmatrix[
5, gamma - l + N - 1] * dblmatrix[
4, beta - l + N - 1] * dblmatrix[
4, beta - s + N - 1] * dblmatrix[
4, alpha - s + N -
1] * dblmatrix[4, alpha - n +
N - 1]
grgl = bess1 * (omint1p - omint1m)
pp1p = dblmatrix[6, alpha - beta + N - 1] * (
-singmatrix[1, gamma] +
dblmatrix[1, s + gamma] -
singmatrix[5, gamma] + dblmatrix[3, s + gamma])
pp2p = dblmatrix[7, alpha - gamma + N - 1] * (
-singmatrix[1, beta] + dblmatrix[1, s + beta] +
singmatrix[5, beta] - dblmatrix[3, s + beta])
pp3p = dblmatrix[8, beta - gamma + N - 1] * (
singmatrix[0, alpha] -
dblmatrix[0, s + alpha] -
singmatrix[4, alpha] + dblmatrix[2, s + alpha])
pp1m = dblmatrix[6, alpha - beta + N - 1] * (
-singmatrix[3, gamma] +
dblmatrix[1, s + gamma] -
singmatrix[7, gamma] + dblmatrix[3, s + gamma])
pp2m = dblmatrix[7, alpha - gamma + N - 1] * (
-singmatrix[3, beta] + dblmatrix[1, s + beta] +
singmatrix[7, beta] - dblmatrix[3, s + beta])
pp3m = dblmatrix[8, beta - gamma + N - 1] * (
singmatrix[2, alpha] -
dblmatrix[0, s + alpha] -
singmatrix[6, alpha] + dblmatrix[2, s + alpha])
d2 = -2 * complex(0, 1) * dblmatrix[
6, alpha - beta + N -
1] * dblmatrix[7, alpha - gamma + N -
1] * dblmatrix[8, beta - gamma +
N - 1]
omint2p = singmatrix[8, s] * (
(pp1p + pp2p + pp3p) / d2)
omint2m = singmatrix[9, s] * (
(pp1m + pp2m + pp3m) / d2)
bess2 = dblmatrix[
5, gamma - n + N - 1] * dblmatrix[
5, gamma - s + N - 1] * dblmatrix[
5, beta - s + N - 1] * dblmatrix[
5, beta - l + N - 1] * dblmatrix[
4, alpha - l + N -
1] * dblmatrix[4, alpha - n +
N - 1]
glga = bess2 * (omint2p - omint2m)
dds = dds + Gamm * (grgl + glga)
return -4 * dds.real / math.pi**2
def modDs_real(x):
dds = 0
r = cudahelpers.getr()
ek = A * (math.sqrt((x[0])**2 + (x[1])**2))**2 + A * (eE0 / hOmg)**2
ekq = A * (math.sqrt((x[0] + x[2])**2 +
(x[1] + 0)**2))**2 + A * (eE0 / hOmg)**2
xk = 2 * A * eE0 * math.sqrt((x[0])**2 + (x[1])**2) / hOmg**2
xkq = 2 * A * eE0 * math.sqrt((x[0] + x[2])**2 + (x[1] + 0)**2) / hOmg**2
ts1 = ek - hOmg / 2
ts2 = ekq - hOmg / 2
ts3 = ek + hOmg / 2
ts4 = ekq + hOmg / 2
arc2ts1 = math.atan2(Gamm, ts1)
arc2ts2 = math.atan2(Gamm, ts2)
arc2ts3 = math.atan2(Gamm, ts3)
arc2ts4 = math.atan2(Gamm, ts4)
taninv1kp = 2 * arc2ts1
taninv1kqp = 2 * arc2ts2
taninv1km = 2 * arc2ts3
taninv1kqm = 2 * arc2ts4
squared1 = ek - hOmg / 2
squared2 = ekq - hOmg / 2
squared3 = ek + hOmg / 2
squared4 = ekq + hOmg / 2
logged1 = Gamm**2 + squared1**2
logged2 = Gamm**2 + squared2**2
logged3 = Gamm**2 + squared3**2
logged4 = Gamm**2 + squared4**2
logged1 = Gamm**2 + (ek - hOmg / 2)**2
logged2 = Gamm**2 + (ekq - hOmg / 2)**2
logged3 = Gamm**2 + (ek + hOmg / 2)**2
logged4 = Gamm**2 + (ekq + hOmg / 2)**2
ln1 = math.log(logged1)
ln2 = math.log(logged2)
ln3 = math.log(logged3)
ln4 = math.log(logged4)
lg1kp = complex(0, 1) * ln1
lg1kqp = complex(0, 1) * ln2
lg1km = complex(0, 1) * ln3
lg1kqm = complex(0, 1) * ln4
heavi1 = mu - hOmg / 2
heavi2 = mu + hOmg / 2
ferp = cudahelpers.my_heaviside(heavi1)
ferm = cudahelpers.my_heaviside(heavi2)
taninv2k = 2 * math.atan2(Gamm, ek - mu)
taninv2kq = 2 * math.atan2(Gamm, ekq - mu)
lg2k = complex(0, 1) * math.log(Gamm**2 + (ek - mu)**2)
lg2kq = complex(0, 1) * math.log(Gamm**2 + (ekq - mu)**2)
besk = cudahelpers.besselj(0, xk)
beskq = cudahelpers.besselj(0, xkq)
fac1 = ek - ekq
fac2 = fac1 + 2 * complex(0, 1) * Gamm
fac3 = fac2 - ek + ekq
# NOTE: N = 1 implies all loops below will be evaluated once.
p1p = fac1 * (taninv1kp - taninv2k - lg1kp + lg2k)
p2p = fac2 * (taninv1kp - taninv2k + lg1kp - lg2k)
p3p = fac3 * (-taninv1kqp + taninv2kq - lg1kqp + lg2kq)
p1m = fac1 * (taninv1km - taninv2k - lg1km + lg2k)
p2m = fac2 * (taninv1km - taninv2k + lg1km - lg2k)
p3m = fac3 * (-taninv1kqm + taninv2kq - lg1kqm + lg2kq)
d1 = -2 * complex(0, 1) * fac1 * fac2 * fac3
omint1p = ferp * ((p1p + p2p + p3p) / d1)
omint1m = ferm * ((p1m + p2m + p3m) / d1)
bess1 = beskq * beskq * besk * besk * besk * besk
grgl = bess1 * (omint1p - omint1m)
pp1p = fac1 * (-taninv1kqp + taninv2kq - lg1kqp + lg2kq)
pp2p = fac2 * (-taninv1kqp + taninv2kq + lg1kqp - lg2kq)
pp3p = fac3 * (taninv1kp - taninv2k - lg1kp + lg2k)
pp1m = fac1 * (-taninv1kqm + taninv2kq - lg1kqm + lg2kq)
pp2m = fac2 * (-taninv1kqm + taninv2kq + lg1kqm - lg2kq)
pp3m = fac3 * (taninv1km - taninv2k - lg1km + lg2k)
d2 = -2 * complex(0, 1) * fac1 * fac2 * fac3
omint2p = ferp * ((pp1p + pp2p + pp3p) / d2)
omint2m = ferm * ((pp1m + pp2m + pp3m) / d2)
bess2 = beskq * beskq * beskq * beskq * besk * besk
glga = bess2 * (omint2p - omint2m)
bess0 = cudahelpers.besselj(0, x[2] * r)
dds = dds + Gamm * (grgl + glga) * x[2] * bess0
return -2 * dds.real / math.pi**3
def modDsN2(x):
N = 1
dds = 0
# ds = 0 # UNUSED
qx = helpers.getqx()
ek = A * (math.sqrt((x[0])**2 + (x[1])**2))**2 + A * (eE0 / hOmg)**2
ekq = A * (math.sqrt((x[0] + qx)**2 +
(x[1] + 0)**2))**2 + A * (eE0 / hOmg)**2
xk = 2 * A * eE0 * math.sqrt((x[0])**2 + (x[1])**2) / hOmg**2
xkq = 2 * A * eE0 * math.sqrt((x[0] + qx)**2 + (x[1] + 0)**2) / hOmg**2
singmatrix = numba.cuda.shared.array((10, N), dtype=numba.types.complex128)
n = 0
i = -(N - 1) / 2
while (i < ((N - 1) / 2 + 1)):
nu = hOmg * i
chi = hOmg / 2
omicron = ek - chi + nu
phi = ekq - chi + nu
iota = ek + chi + nu
kappa = ekq + chi + nu
omisq = omicron**2
phisq = phi**2
iotasq = iota**2
kappasq = kappa**2
singmatrix[0, n] = 2 * math.atan2(Gamm, omicron)
singmatrix[1, n] = 2 * math.atan2(Gamm, phi)
singmatrix[2, n] = 2 * math.atan2(Gamm, iota)
singmatrix[3, n] = 2 * math.atan2(Gamm, kappa)
singmatrix[4, n] = complex(0, 1) * math.log(Gammsq + omisq)
singmatrix[5, n] = complex(0, 1) * math.log(Gammsq + phisq)
singmatrix[6, n] = complex(0, 1) * math.log(Gammsq + iotasq)
singmatrix[7, n] = complex(0, 1) * math.log(Gammsq + kappasq)
chinu = chi - nu
singmatrix[8, n] = helpers.my_heaviside(mu - chinu)
singmatrix[9, n] = helpers.my_heaviside(mu + chinu)
i = i + 1
n = n + 1
size_dbl = 5
dblmatrix = numba.cuda.shared.array((9, size_dbl),
dtype=numba.types.complex128)
n = 0
for i in range(-(N - 1), N, 1):
xi = hOmg * i
zeta = ek - mu + xi
eta = ekq - mu + xi
zetasq = zeta**2
etasq = eta**2
dblmatrix[0, n] = 2 * math.atan2(Gamm, zeta)
dblmatrix[1, n] = 2 * math.atan2(Gamm, eta)
logged1 = math.log(Gammsq + zetasq)
logged2 = math.log(Gammsq + etasq)
dblmatrix[2, n] = complex(0, logged1)
dblmatrix[3, n] = complex(0, logged2)
dblmatrix[4, n] = helpers.besselj(i, xk)
dblmatrix[5, n] = helpers.besselj(i, xkq)
fac1i = ek - ekq + xi
fac2i = complex(fac1i, 2 * Gamm)
dblmatrix[6, n] = fac1i
dblmatrix[7, n] = fac2i
dblmatrix[8, n] = fac2i - ek + ekq
n = n + 1
sdr00 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdr42 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdr11 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdr20 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdr53 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdsdr3173 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
sdr62 = numba.cuda.shared.array((N, N), dtype=numba.types.complex128)
for s in range(0, N):
for dummy in range(0, N):
both = s + dummy
sdr00[s, dummy] = singmatrix[0, dummy] - dblmatrix[0, both]
sdr42[s, dummy] = singmatrix[4, dummy] + dblmatrix[2, both]
sdr11[s, dummy] = -singmatrix[1, dummy] + dblmatrix[1, both]
sdr20[s, dummy] = singmatrix[2, dummy] - dblmatrix[0, both]
sdr53[s, dummy] = singmatrix[5, dummy] + dblmatrix[3, both]
sdsdr3173[s, dummy] = -singmatrix[3, dummy] + dblmatrix[
1, both] - singmatrix[7, dummy] + dblmatrix[3, both]
sdr62[s, dummy] = singmatrix[6, dummy] + dblmatrix[2, both]
for n in range(0, N):
nmod = n + N - 1
for alpha in range(0, N):
for beta in range(0, N):
abdiff = alpha - beta + N - 1
d1part = -2 * complex(0, 1) * dblmatrix[8, abdiff]
d2part = -2 * complex(0, 1) * dblmatrix[6, abdiff]
for gamma in range(0, N):
bgdiff = beta - gamma + N - 1
agdiff = alpha - gamma + N - 1
d1 = d1part * dblmatrix[6, bgdiff] * dblmatrix[7, agdiff]
d2 = d2part * dblmatrix[7, agdiff] * dblmatrix[8, bgdiff]
besspart1 = dblmatrix[5, gamma -
nmod] * dblmatrix[4, alpha - nmod]
for s in range(0, N):
smod = s + N - 1
tau = s + beta
p1p = dblmatrix[6, bgdiff] * (sdr00[s, alpha] -
sdr42[s, alpha])
p2p = dblmatrix[7, agdiff] * (sdr00[s, beta] +
sdr42[s, beta])
p3p = dblmatrix[8, abdiff] * (sdr11[s, gamma] -
sdr53[s, gamma])
p1m = dblmatrix[6, bgdiff] * (sdr20[s, alpha] -
sdr62[s, alpha])
p2m = dblmatrix[7, agdiff] * (sdr20[s, beta] +
singmatrix[6, beta] -
dblmatrix[2, tau])
p3m = dblmatrix[8, abdiff] * (sdsdr3173[s, gamma])
pp1p = dblmatrix[6, abdiff] * (sdr11[s, gamma] -
sdr53[s, gamma])
pp2p = dblmatrix[7, agdiff] * (sdr11[s, beta] +
singmatrix[5, beta] -
dblmatrix[3, tau])
pp3p = dblmatrix[8, bgdiff] * (sdr00[s, alpha] -
sdr42[s, alpha])
pp1m = dblmatrix[6, abdiff] * (sdsdr3173[s, gamma])
pp2m = dblmatrix[7, agdiff] * (
-singmatrix[3, beta] + dblmatrix[1, tau] +
singmatrix[7, beta] - dblmatrix[3, tau])
pp3m = dblmatrix[8, bgdiff] * (sdr20[s, alpha] -
sdr62[s, alpha])
omint1p = singmatrix[8, s] * ((p1p + p2p + p3p) / d1)
omint1m = singmatrix[9, s] * ((p1m + p2m + p3m) / d1)
omint2p = singmatrix[8, s] * (
(pp1p + pp2p + pp3p) / d2)
omint2m = singmatrix[9, s] * (
(pp1m + pp2m + pp3m) / d2)
bess1part2 = dblmatrix[4, beta - smod] * dblmatrix[
4, alpha - smod] * besspart1
bess2part2 = dblmatrix[5, gamma - smod] * dblmatrix[
5, beta - smod] * besspart1
for l in range(0, N):
lmod = l + N - 1
bess1 = bess1part2 * dblmatrix[
5, gamma - lmod] * dblmatrix[4, beta - lmod]
grgl = bess1 * (omint1p - omint1m)
bess2 = bess2part2 * dblmatrix[
5, beta - lmod] * dblmatrix[4, alpha - lmod]
glga = bess2 * (omint2p - omint2m)
dds = dds + Gamm * (grgl + glga)
return -4 * dds.real / math.pi**2
def modDsN2(x):
N = 3
dds = 0
# ds = 0 # UNUSED
qx = cudahelpers.getqx()
ek = A * (math.sqrt((x[0])**2 + (x[1])**2))**2 + A * (eE0 / hOmg)**2
ekq = A * (math.sqrt((x[0] + qx)**2 +
(x[1] + 0)**2))**2 + A * (eE0 / hOmg)**2
xk = 2 * A * eE0 * math.sqrt((x[0])**2 + (x[1])**2) / hOmg**2
xkq = 2 * A * eE0 * math.sqrt((x[0] + qx)**2 + (x[1] + 0)**2) / hOmg**2
singrmatrix = numba.cuda.shared.array((6, N), dtype=numba.types.f8)
singzmatrix = numba.cuda.shared.array((4, N), dtype=numba.types.complex128)
n = 0
i = -(N - 1) / 2
for n in range(0, N):
nu = hOmg * i
chi = hOmg / 2
omicron = ek - chi + nu
phi = ekq - chi + nu
iota = ek + chi + nu
kappa = ekq + chi + nu
omisq = omicron**2
phisq = phi**2
iotasq = iota**2
kappasq = kappa**2
singrmatrix[0, n] = 2 * math.atan2(Gamm, omicron)
singrmatrix[1, n] = 2 * math.atan2(Gamm, phi)
singrmatrix[2, n] = 2 * math.atan2(Gamm, iota)
singrmatrix[3, n] = 2 * math.atan2(Gamm, kappa)
singzmatrix[0, n] = complex(0, 1) * math.log(Gammsq + omisq)
singzmatrix[1, n] = complex(0, 1) * math.log(Gammsq + phisq)
singzmatrix[2, n] = complex(0, 1) * math.log(Gammsq + iotasq)
singzmatrix[3, n] = complex(0, 1) * math.log(Gammsq + kappasq)
chinu = chi - nu
singrmatrix[4, n] = cudahelpers.my_heaviside(mu - chinu)
singrmatrix[5, n] = cudahelpers.my_heaviside(mu + chinu)
i = i + 1
size_dbl = 5 # 2N-1
dblrmatrix = numba.cuda.shared.array((5, size_dbl), dtype=numba.types.f8)
dblzmatrix = numba.cuda.shared.array((4, size_dbl),
dtype=numba.types.complex128)
i = -(N - 1)
for n in range(0, size_dbl):
xi = hOmg * i
zeta = ek - mu + xi
eta = ekq - mu + xi
zetasq = zeta**2
etasq = eta**2
dblrmatrix[0, n] = 2 * math.atan2(Gamm, zeta)
dblrmatrix[1, n] = 2 * math.atan2(Gamm, eta)
logged1 = math.log(Gammsq + zetasq)
logged2 = math.log(Gammsq + etasq)
dblzmatrix[0, n] = complex(0, logged1)
dblzmatrix[1, n] = complex(0, logged2)
dblrmatrix[2, n] = cudahelpers.besselj(i, xk)
dblrmatrix[3, n] = cudahelpers.besselj(i, xkq)
fac1i = ek - ekq + xi
fac2i = complex(fac1i, 2 * Gamm)
dblrmatrix[4, n] = fac1i
dblzmatrix[2, n] = fac2i
dblzmatrix[3, n] = fac2i - ek + ekq
i = i + 1
for n in range(0, N):
nmod = n + N - 1
for alpha in range(0, N):
for beta in range(0, N):
abdiff = alpha - beta + N - 1
for gamma in range(0, N):
bgdiff = beta - gamma + N - 1
agdiff = alpha - gamma + N - 1
d1 = -2 * complex(0, 1) * dblrmatrix[
4, bgdiff] * dblzmatrix[2, agdiff] * dblzmatrix[3,
abdiff]
d2 = -2 * complex(0, 1) * dblrmatrix[
4, abdiff] * dblzmatrix[2, agdiff] * dblzmatrix[3,
bgdiff]
for s in range(0, N):
smod = s + N - 1
rho = s + alpha
tau = s + beta
upsilon = s + gamma
sdr00 = singrmatrix[0, alpha] - dblrmatrix[0, rho]
sdr20 = singrmatrix[2, alpha] - dblrmatrix[0, rho]
sdr11 = -singrmatrix[1, gamma] + dblrmatrix[1, upsilon]
sdr31 = -singrmatrix[3, gamma] + dblrmatrix[1, upsilon]
sdz00 = singzmatrix[0, alpha] + dblzmatrix[0, rho]
sdz20 = singzmatrix[2, alpha] + dblzmatrix[0, rho]
sdz11 = singzmatrix[1, gamma] + dblzmatrix[1, upsilon]
sdz31 = singzmatrix[3, gamma] + dblzmatrix[1, upsilon]
dd11 = dblrmatrix[1, tau] - dblzmatrix[1, tau]
dd00 = dblrmatrix[0, tau] + dblzmatrix[0, tau]
p1p = dblrmatrix[4, bgdiff] * (sdr00 - sdz00)
p2p = dblzmatrix[2, agdiff] * (
singrmatrix[0, beta] - dd00 + singzmatrix[0, beta])
p3p = dblzmatrix[3, abdiff] * (sdr11 - sdz11)
p1m = dblrmatrix[4, bgdiff] * (sdr20 - sdz20)
p2m = dblzmatrix[2, agdiff] * (
singrmatrix[2, beta] - dd00 + singzmatrix[2, beta])
p3m = dblzmatrix[3, abdiff] * (sdr31 - sdz31)
omint1p = singrmatrix[4, s] * ((p1p + p2p + p3p) / d1)
omint1m = singrmatrix[5, s] * ((p1m + p2m + p3m) / d1)
pp1p = dblrmatrix[4, abdiff] * (sdr11 - sdz11)
pp2p = dblzmatrix[2, agdiff] * (-singrmatrix[1, beta] +
dd11 +
singzmatrix[1, beta])
pp3p = dblzmatrix[3, bgdiff] * (sdr00 - sdz00)
pp1m = dblrmatrix[4, abdiff] * (sdr31 - sdz31)
pp2m = dblzmatrix[2, agdiff] * (-singrmatrix[3, beta] +
dd11 +
singzmatrix[3, beta])
pp3m = dblzmatrix[3, bgdiff] * (sdr20 - sdz20)
omint2p = singrmatrix[4, s] * (
(pp1p + pp2p + pp3p) / d2)
omint2m = singrmatrix[5, s] * (
(pp1m + pp2m + pp3m) / d2)
for l in range(0, N):
lmod = l + N - 1
bess1 = dblrmatrix[3, gamma - nmod] * dblrmatrix[
3, gamma - lmod] * dblrmatrix[
2, beta - lmod] * dblrmatrix[
2, beta - smod] * dblrmatrix[
2, alpha -
smod] * dblrmatrix[2, alpha - nmod]
grgl = bess1 * (omint1p - omint1m)
bess2 = dblrmatrix[3, gamma - nmod] * dblrmatrix[
3, gamma - smod] * dblrmatrix[
3, beta - smod] * dblrmatrix[
3, beta - lmod] * dblrmatrix[
2, alpha -
lmod] * dblrmatrix[2, alpha - nmod]
glga = bess2 * (omint2p - omint2m)
dds = dds + Gamm * (grgl + glga)
return -4 * dds.real / math.pi**2