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()