def mp1_mp2_cpuntag(i, j, k, l): # untag_CP(B>X(s+d) + gamma)
print(i, j, k, l)
m1_axis = np.array([i for i in np.arange(10, 570, 20)])
m2_axis = np.array([i for i in np.arange(10, 1070, 20)])
m2 = m2_axis[0]
m1 = m1_axis[0]
emptytag = []
for m2 in m2_axis:
for m1 in m1_axis:
tag= bsg.untag_cp(mb,mw,m1,m2,\
[exe.Y2(i,j,k,l)],[ - exe.X2(i,j,k,l) * np.conjugate(exe.Y2(i,j,k,l) )],\
[exe.Y3(i,j,k,l)],[ - exe.X3(i,j,k,l) * np.conjugate(exe.Y3(i,j,k,l) )])
# print(acppd)
emptytag.append(tag)
# print(emptytag)
resulttag = plt.contourf(m1_axis, m2_axis, \
np.resize(np.array(emptytag),len(np.array(emptytag))).\
reshape(len(m2_axis),len(m1_axis)), \
# colors = ['black','royalblue','purple','darkgreen','brown','red','gray','orange'],\
levels = np.array([0.4,0.6,0.8,1.2,1.4,1.6])
)
plt.colorbar(resulttag)
plt.xlabel('$M_{H^{\pm}_{1}}$')
plt.ylabel('$M_{H^{\pm}_{2}}$')
plt.title('$A_{CP} (B \\to X_{s + d} \gamma )$ for 3HDM')
# plt.grid(axis='y', linestyle='-', color='0.75') # show y-axis grid line
# plt.grid(axis='x', linestyle='-', color='0.75') # show x-axis grid line
# plt.axis([50,200, 50.0, 1000.0])
plt.axis([0, 500, 0.0, 500.0])
plt.show()
plt.close()
return
def mp1_mp2_cpsdiffer(i, j, k, l): # Delta_CP(B>Xs + gamma)
print(i, j, k, l)
m1_axis = np.array([i for i in np.arange(10, 550, 50)])
m2_axis = np.array([i for i in np.arange(10, 1050, 50)])
m2 = m2_axis[0]
m1 = m1_axis[0]
emptycpsd = []
for m2 in m2_axis:
for m1 in m1_axis:
acppd= bsg.newdifferacps(mb,mw,m1,m2,\
[exe.Y2(i,j,k,l)],[ - exe.X2(i,j,k,l) * np.conjugate(exe.Y2(i,j,k,l) )],\
[exe.Y3(i,j,k,l)],[ - exe.X3(i,j,k,l) * np.conjugate(exe.Y3(i,j,k,l) )])
# print(acppd)
emptycpsd.append(acppd)
resultcpsd = plt.contourf(m1_axis, m2_axis, \
np.resize(np.array(emptycpsd),len(np.array(emptycpsd))).\
reshape(len(m2_axis),len(m1_axis)), \
# colors = ['black','royalblue','purple','darkgreen','brown','red','gray','orange'],\
# levels = np.array([0.0,0.5,1,1.5,2])
)
plt.colorbar(resultcpsd)
plt.xlabel('$M_{H^{\pm}_{1}}$')
plt.ylabel('$M_{H^{\pm}_{2}}$')
plt.title('$\\Delta_{X_s\gamma}$ for 3HDM')
# plt.grid(axis='y', linestyle='-', color='0.75') # show y-axis grid line
# plt.grid(axis='x', linestyle='-', color='0.75') # show x-axis grid line
# plt.axis([50,200, 50.0, 1000.0])
plt.axis([0, 500, 0.0, 500.0])
plt.show()
plt.close()
return
def mp1_A_cpsdiffer(i, j, k, l):
m1_axis = np.array([i for i in np.arange(1, 551, 25)])
# m2_axis = np.array([ i for i in np.arange(10,1050,50)] )
cps_li = []
for j in exe.tbe:
print('j', j)
for m1 in m1_axis:
acpp= bsg.newa_cp(mb,mw,m1,300,\
[exe.Y2(i,j,k,l)],[- exe.X2(i,j,k,l) * np.conjugate(exe.Y2(i,j,k,l) )],\
[exe.Y3(i,j,k,l)],[- exe.X3(i,j,k,l) * np.conjugate(exe.Y3(i,j,k,l) )])
cps_li.append(acpp)
resultcps = plt.contourf(m1_axis, exe.tbe, \
np.resize(np.array(cps_li),len(np.array(cps_li))).\
reshape(len(exe.tbe),len(m1_axis)), \
# colors = ['black','royalblue','purple','darkgreen','brown','red','gray','orange'],\
# levels = np.array([0,0.5,1,1.5,2])
)
plt.colorbar(resultcps)
plt.xlabel('$M_{H^{\pm}_{1}}$')
plt.ylabel(exe.readlist[int(exe.read1)])
plt.title('$\\Delta_{X_s\gamma}$ for 3HDM')
plt.show()
plt.close()
return
def plot_under_deltascan(i, j, k, l):
m1_axis = np.array([i for i in np.arange(50, 550, 50)])
m2_axis = np.array([i for i in np.arange(50, 1050, 50)])
m2 = m2_axis[0]
m1 = m1_axis[0]
# print('i,j,k,l',i,j,k,l)
# xx, yy = np.meshgrid(m1_axis, m2_axis)
print('i,j,k,l', i, j, k, l)
empty = []
for m2 in m2_axis:
for m1 in m1_axis:
threehdm = bsg.BR_B_Xs_gamma(mb,mw,m1,m2,\
[exe.Y2(i,j,k,l)],[- exe.X2(i,j,k,l) * np.conjugate(exe.Y2(i,j,k,l) )],\
[exe.Y3(i,j,k,l)],[- exe.X3(i,j,k,l) * np.conjugate(exe.Y3(i,j,k,l) )])
empty.append(threehdm)
result = plt.contourf(m1_axis, m2_axis, \
np.resize(np.array(empty) / (1e-4),len(np.array(empty) / (1e-4))).\
reshape(len(m2_axis),len(m1_axis)), \
colors = ['black','royalblue','purple','darkgreen','brown','red','gray','orange'],\
levels = np.array([2.99,3.55])
)
plt.colorbar(result)
plt.xlabel('$M_{H^{\pm}_{1}}$')
plt.ylabel('$M_{H^{\pm}_{2}}$')
plt.title('BR($\\bar{B} \\to X_{s} \gamma$) $\\times 10^{4}$')
plt.grid(axis='y', linestyle='-', color='0.75') # show y-axis grid line
plt.grid(axis='x', linestyle='-', color='0.75') # show x-axis grid line
# plt.axis([50,200, 50.0, 1000.0])
plt.axis([0, 500, 0.0, 1000.0])
plt.show()
plt.close()
def mp1_mp2_cps(i, j, k, l):
m1_axis = np.array([i for i in np.arange(10, 550, 50)])
m2_axis = np.array([i for i in np.arange(10, 1050, 50)])
m2 = m2_axis[0]
m1 = m1_axis[0]
empty = []
for m2 in m2_axis:
for m1 in m1_axis:
acpp= bsg.newa_cp(mb,mw,m1,m2,\
[exe.Y2(i,j,k,l)],[- exe.X2(i,j,k,l) * np.conjugate(exe.Y2(i,j,k,l) )],\
[exe.Y3(i,j,k,l)],[- exe.X3(i,j,k,l) * np.conjugate(exe.Y3(i,j,k,l) )])
empty.append(acpp)
resultcps = plt.contourf(m1_axis, m2_axis, \
np.resize(np.array(empty),len(np.array(empty))).\
reshape(len(m2_axis),len(m1_axis)), \
# colors = ['black','royalblue','purple','darkgreen','brown','red','gray','orange'],\
# levels = np.array([-0.08,0.2])
)
plt.colorbar(resultcps)
plt.xlabel('$M_{H^{\pm}_{1}}$')
plt.ylabel('$M_{H^{\pm}_{2}}$')
plt.title('$A_{CP} (b \\to s \gamma)$ for 3HDM')
# plt.grid(axis='y', linestyle='-', color='0.75') # show y-axis grid line
# plt.grid(axis='x', linestyle='-', color='0.75') # show x-axis grid line
# plt.axis([50,200, 50.0, 1000.0])
plt.axis([0, 500, 0.0, 1000.0])
plt.show()
plt.close()
return
def plt_A_B_cpsdiffer(i, j): #Delta-CPS-asymmetry in {A,B} plane
result_deltas = []
mass_axis1, mass_axis2 = i, j
for n in np.arange(0, len(ABarray4())):
cpsdif = bsg.newdifferacps(mb,mw,mass_axis1,mass_axis2,\
exe.Y2(*ABarray4()[n] ), exe.complexyfunction(*ABarray4()[n] ),\
# [0.0],[0.0])
exe.Y3(*ABarray4()[n] ), exe.complexyfunction3(*ABarray4()[n] ))
result_deltas.append(cpsdif)
result = plt.contourf(exe.A, exe.B, \
np.resize(np.array(result_deltas).flatten() ,\
len(np.array(result_deltas).flatten() ) ).\
reshape(len(exe.B),len(exe.A)), \
cmap = plt.cm.get_cmap('RdBu_r'))#levels = np.arange(-20,-8,2) )
plt.colorbar(result)
plt.title('$\\Delta_{X_s\gamma}$ with charged Higgs: '\
+ str("%02d" % mass_axis1) +', ' + str("%02d"% mass_axis2)+' GeV.' )
plt.xlabel(exe.readlist[int(exe.read1)])
plt.ylabel(exe.readlist[int(exe.read2)])
plt.axis([0, 6.5, -1.6, 0])
plt.savefig('cpsdiffer' + str("%02d" % mass_axis1) +
str("%02d" % mass_axis2) + '.png')
plt.show()
plt.close()
def plt_A_B_untag(i, j): #Untag-asymmetry in {A,B} plane
result_untag = []
mass_axis1, mass_axis2 = i, j
for n in np.arange(0, len(ABarray4())):
untagg = bsg.untag_cp(mb,mw,mass_axis1,mass_axis2,\
exe.Y2(*ABarray4()[n] ), exe.complexyfunction(*ABarray4()[n] ),\
# [0.0],[0.0])
exe.Y3(*ABarray4()[n] ), exe.complexyfunction3(*ABarray4()[n] ))
result_untag.append(untagg)
result = plt.contourf(exe.A, exe.B, \
np.resize(np.array(result_untag).flatten() ,\
len(np.array(result_untag).flatten() ) ).\
reshape(len(exe.B),len(exe.A)), \
cmap = plt.cm.get_cmap('RdBu_r'))#levels = np.arange(-20,-8,2) )
plt.colorbar(result)
plt.title('$A_{CP} (B \\to X_{s + d} \gamma )$ with charged Higgs: '\
+ str("%02d" % mass_axis1) +', ' + str("%02d"% mass_axis2)+' GeV.' )
plt.xlabel(exe.readlist[int(exe.read1)])
plt.ylabel(exe.readlist[int(exe.read2)])
plt.axis([0, 6.5, -1.6, 0])
plt.savefig('untag' + str("%02d" % mass_axis1) + str("%02d" % mass_axis2) +
'.png')
plt.show()
plt.close()
def plt_A_B_cps(i, j): #CP-asymmetry in {A,B} plane
result_cp = []
mass_axis1, mass_axis2 = i, j
for n in np.arange(0, len(ABarray4())):
cpasymetry = bsg.newa_cp(mb,mw,mass_axis1,mass_axis2,\
exe.Y2(*ABarray4()[n] ), exe.complexyfunction(*ABarray4()[n] ),\
# [0.0],[0.0])
exe.Y3(*ABarray4()[n] ), exe.complexyfunction3(*ABarray4()[n] ))
result_cp.append(cpasymetry)
cpresult = plt.contourf(exe.A, exe.B, \
np.resize(np.array(result_cp).flatten() ,\
len(np.array(result_cp).flatten() ) ).\
reshape(len(exe.B),len(exe.A)), \
cmap = plt.cm.get_cmap('RdBu_r') )# levels = np.array([-12,-10,-8,-6,-4,-2,0,2,4]) )
plt.colorbar(cpresult)
plt.title('$A_{CP}(B \\to X_{s}\gamma)$ with charged Higgs: '\
+ str("%02d" % mass_axis1) +', ' + str("%02d"% mass_axis2)+' GeV.' )
plt.xlabel(exe.readlist[int(exe.read1)])
plt.ylabel(exe.readlist[int(exe.read2)])
plt.axis([0, 6.5, -1.6, 0])
plt.savefig('cp' + str("%02d" % mass_axis1) + str("%02d" % mass_axis2) +
'.png')
plt.show()
plt.close()
def plt_A_B_bsg(i, j): # Bsgamma-result in {A,B} plane
mass_axis1, mass_axis2 = i, j
print(ABarray4()[0], mass_axis1, len(ABarray4()))
print(ABarray4()[1], mass_axis2, len(ABarray4()))
resultb = []
#B>Xs+gamma SECTION
for n in np.arange(0, len(ABarray4())):
y3hdm= bsg.BR_B_Xs_gamma(mb,mw,mass_axis1,mass_axis2,\
exe.Y2(*ABarray4()[n] ), exe.complexyfunction(*ABarray4()[n] ),\
exe.Y3(*ABarray4()[n] ), exe.complexyfunction3(*ABarray4()[n] ))
resultb.append(y3hdm / (1e-4))
#########
bsgamm = plt.contourf(exe.A, exe.B, \
np.resize(np.array(resultb).flatten() ,len(np.array(resultb).flatten() ) ).\
reshape(len(exe.B),len(exe.A)) ,\
levels = np.array([2.99,3.55]),colors = ['green'] )
plt.colorbar(bsgamm)
plt.title('BR($\\bar{B} \\to X_{s} \gamma$) in '\
+ str("%02d" % mass_axis1) +', ' + str("%02d"% mass_axis2) )
plt.xlabel(exe.readlist[int(exe.read1)])
plt.ylabel(exe.readlist[int(exe.read2)])
plt.axis([0, 6.5, -1.6, 0])
# plt.axis([1,60,-1.6,0])
# plt.axis([0,60,0,60])
plt.savefig(
str("%02d" % mass_axis1) + str("%02d" % mass_axis2) + 'bsg.png')
plt.show()
plt.close()
def numerical():
mass_axis = (80.0, 250.0)
result = []
for n in np.arange(0, len(ABarray4())):
y3hdm= bsg.BR_B_Xs_gamma(mb,mw,mass_axis[0],mass_axis[1],\
exe.Y2(*ABarray4()[n] ),- exe.complexyfunction(*ABarray4()[n] ),\
exe.Y3(*ABarray4()[n] ),- exe.complexyfunction3(*ABarray4()[n] ))
# print(y3hdm / (1e-4),n)
result.append(y3hdm / (1e-4))
return np.concatenate(result).ravel()
def plt_A_B_bsgnedm(i, j): # Bsgamma-result and N-EDM in {A,B} plane
mass_axis1, mass_axis2 = i, j
print(ABarray4()[0], mass_axis1, len(ABarray4()))
print(ABarray4()[1], mass_axis2, len(ABarray4()))
resultb = []
resultn = []
resulte = []
#B>Xs+gamma SECTION
for n in np.arange(0, len(ABarray4())):
y3hdm= bsg.BR_B_Xs_gamma(mb,mw,mass_axis1,mass_axis2,\
exe.Y2(*ABarray4()[n] ), exe.complexyfunction(*ABarray4()[n] ),\
exe.Y3(*ABarray4()[n] ), exe.complexyfunction3(*ABarray4()[n] ))
resultb.append(y3hdm / (1e-4))
#Nedm SECTION
nedm3hdm = abs(dn(mass_axis1,mass_axis2, exe.complexyfunction(*ABarray4()[n]),\
exe.complexyfunction3(*ABarray4()[n]) ) / (5.06e13) )\
/ 1e-26
resultn.append(nedm3hdm)
#eedm SECTION
eedm3hdm = abs(de(mass_axis1,mass_axis2,exe.yconjz2(*ABarray4()[n]),\
exe.yconjz3(*ABarray4()[n]) ) /1e-29 )
resulte.append(eedm3hdm)
#########
ned = plt.contourf(exe.A, exe.B, \
np.resize(np.array(resultn).flatten() ,len(np.array(resultn).flatten() ) ).\
reshape(len(exe.B),len(exe.A)) ,\
levels = np.array([0.0,1.8]),colors = ['red'] )
#########
bsgamm = plt.contourf(exe.A, exe.B, \
np.resize(np.array(resultb).flatten() ,len(np.array(resultb).flatten() ) ).\
reshape(len(exe.B),len(exe.A)) ,\
levels = np.array([2.99,3.55]),colors = ['green'] )
#########
# eed = plt.contourf(exe.A, exe.B, \
# np.resize(np.array(resulte).flatten() ,len(np.array(resulte).flatten() ) ).\
# reshape(len(exe.B),len(exe.A)) ,\
# levels = np.array([0.0,1.1]),colors = ['blue'] )
plt.title('BR($\\bar{B} \\to X_{s} \gamma$) and NEDM in '\
+ str("%02d" % mass_axis1) +', ' + str("%02d"% mass_axis2) )
plt.xlabel(exe.readlist[int(exe.read1)])
plt.ylabel(exe.readlist[int(exe.read2)])
# plt.axis([0,60,-1.6,0]) #{tanbeta/tangamma,theta} plane
# plt.axis([0,2 * PI ,-1.6,0]) #{theta,delta} plane
plt.axis([0, 60, 0, 60]) # {tanbeta,tangamma} plane
plt.savefig(
str("%02d" % mass_axis1) + str("%02d" % mass_axis2) + 'bsg.png')
plt.show()
plt.close()
