bsgamma.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 28 12:27:55 2019

@author: muyuansong0419
"""

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 17 14:58:53 2019
@author: muyuansong0419
"""

import numpy as np
import matplotlib.pyplot as plt
import gammaeffective as gaeff
from scipy.integrate import quad
from scipy import special as sp
from invariant import *
from matplotlib.ticker import MultipleLocator
#from eehh import mhch
#from exercise import xyfun,xyfun3,yfun,yfun3,U,X2,X3,Y2,Y3,Z2,Z3,complexyfunction,complexyfunction3
#import exercise as ex
#print('xyfun',np.array(xyfun))
#print('U',U(- PI/2.1,2,20,0.0)[0][2] / U(- PI/2.1,2,20,0.0)[0][0])
#print('X3',X3(- PI/2.1,2,20,0.0),Y3(- PI/2.1,2,20,0.0))
mass_differ  = 80   # charged Higgs mass diference
# I make two arrays to pretend solution of XY* and Y
#ll1 = np.array(xyfun) #j = XY^*
#ll2 = np.array(yfun)#i = Y
#############
############
#QCD running coupling constant (alp) at energy scale MH. Relevant                                                                                                                                                                        
#for QCD corrections to Higgs decay widths.
################ LO for strong coupling constant
def LOalpha_s(i): #alpha_s(mu) at LO
#    print(i,zz,alpmz,mz)
    beta_0 = 23/3
    beta_1 = 0
    v = 1 - beta_0 * (alpmz / (2.0 * PI)) * np.log(mz / i)
    ratio1 = np.log(v) / v
    return alpmz / v * (1 - (beta_1 / beta_0) * (alpmz / (4 * PI)) * ratio1)

################ NLO for strong coupling constant
def NLOalpha_s(i): #alpha_s(mu) at NLO
    beta_0 = 23 / 3
    beta_1 = 116 / 3
    v = 1 - beta_0 * (alpmz / (2.0 * PI)) * np.log(mz / i)
    ratio1 = np.log(v) / v
    return alpmz / v * (1 - (beta_1 / beta_0) * (alpmz / (4 * PI)) * ratio1)
def eta0(s1,s2):
    return LOalpha_s(s1) / LOalpha_s(s2)
def eta1(s1,s2):
    return NLOalpha_s(s1) / NLOalpha_s(s2)
print('mu_w scale at LO and NLO:',mw,LOalpha_s(mw),NLOalpha_s(mw))
print('4.8 scale at LO and NLO:',4.8,LOalpha_s(4.8),NLOalpha_s(4.8))
print('mu_z scale at LO and NLO:',mz,LOalpha_s(mz),NLOalpha_s(mz))
print('mu_b scale at LO and NLO:',mb,LOalpha_s(mb),NLOalpha_s(mb))
print('mu_t scale at LO and NLO:',mt,LOalpha_s(mt),NLOalpha_s(mt))
#################running quark mass at scale mu_w under minimal subtract scheme
def run_quark_bar(s,q):# 
    c1 = np.log(q**2 / s**2)
    c2 = NLOalpha_s(s) / PI
    return q * (1 + c2 * c1 - 4 / 3 * c2 )
print(run_quark_bar(4.8,4.8))
print(LOalpha_s(run_quark_bar(4.8,4.8)),NLOalpha_s(run_quark_bar(4.8,4.8)))
#############
charHm_100 = np.array([100,300,500,1000]) #for MH+2 = 100GeV
charHm_large = np.array([300,500,1000,1200]) #for MH+3 > 100GeV
delta_cp = 0.3 #delta_cp fraction of Energy cut in CP-asymmetry 
zz = (mc / mb )**2  # mc^2 / mb^2
#zz = (mc / mb)**2
xx = mt**2 / mw**2 # mt^2 /mw^2
NLOxx = mt**2 / mw**2
PI = np.pi
# mt^2 / mh^2
def yy(mass):
    return mt**2 / mass**2
def NLOyy(mass):
    return mt**2 / mass**2
print('zz',zz,1/zz)
a_i = [14 /23, 16 /23, 6 /23, - 12/23,0.4086,-0.4230,-0.8994,0.1456]#{a_i}
h_i = [626126/272277 , - 56281/51730, - 3/7, - 1/14, - 0.6494, - 0.0380,\
                - 0.0186, - 0.0057]#{h_i}
a2_i = [14/23, 0.4086, - 0.4230, - 0.8994, 0.1456]#{a'_i}
h2_i = [313063/363036, - 0.9135, 0.0873, - 0.0571, 0.0209]#{h'_i}
e_i = [4661194/816831, - 8516/2217, 0.0,0.0,- 1.9043, - 0.1008,\
                0.1216,0.0183]#{e_i}
f_i = [- 17.3023, 8.5027, 4.5508, 0.7519, 2.0040, 0.7476, - 0.5385, 0.0914]#{f_i}
k_i = [9.9372, - 7.4878, 1.2688, - 0.2925, -2.2923, - 0.1461, 0.1239, 0.0812]#{k_i}
l_i = [0.5784, - 0.3921, -0.1429, 0.0476, - 0.1275, 0.0317, 0.0078, - 0.0031]#{l_i}
y_i = [0.0,0.0,- 1/3.0,- 4/9.0,- 20/3.0, - 80/9.0]# {y_i} 
z_i = [0,0,1.0,- 1/6.0, 20, - 10/3.0]#{z_i}
##########################################################
# PHYSICAL REVIEW D, VOLUME 58,074004-7 EQUATION (36,39)
# PHASE- SPACE FUNCTION g(z)
g_z = 1 - 8 * zz + 8 * zz**3 - zz**4 - 12 * zz**2 * np.log(zz)
# QCD-RADIATION FUNCTION f(z)
f_z = (PI**2 - 31 / 4) * (1 - np.sqrt(zz))**2 + 3 / 2
lam1 = -0.5
lam2 = -0.12
#NON-Perturbative kronc-delta (GeV^2)
delta_NP_ga = lam1 / 2 - 9 * lam2 / 2
delta_NP_c = - lam2 / 9
delta_NP_SL = lam1 /2 + 3 * lam2 / 2 * (1 - 4 * (1 - zz)**4 / g_z) 
#########################################################
#print(gaeff.gamma0eff())#gamma_0_eff_ji matrix values
#print(gaeff.gamma1eff())#gamma_1_eff_ji matrix values
print('run-bquark-at-mw-scale',run_quark_bar(mw,mb))
print('LOalpha_s(run_m_b)',LOalpha_s(run_quark_bar(mw,mb)),\
      'LO a_s(mw) / LO a_s(run_mb)', LOalpha_s(mw) / LOalpha_s(run_quark_bar(mw,mb)))
#########################################################################
# Function G(t) in E2 of PHYSICAL REVIEW D, Vol58, 074004-19
def G_(t):# t < 4 and t > 4
    if t < 4:
       return - 2 * np.arctan(np.sqrt(t /(4 - t) ) )**2
    else:
       log_value = np.log((np.sqrt(t) + np.sqrt(t - 4))/2)
       repart = - PI**2 / 2 + 2 * log_value**2
       impart =  - 2 * PI * log_value
       return complex(repart , impart)
def grand1(t): # f_22 integrand
    return (1 - zz * t)**2 * abs(G_(t) / t + 1 / 2)**2
def grand2(t): # f_27 integrand
    return (1 - zz * t) * (np.real(G_(t)) + t / 2)
def grand3(t): # f_27 integrand imaginary
    return (1 - zz * t) * (np.imag(G_(t)))
print('quad3',G_(1.0 / zz), zz,quad(grand3, 0, 1.0 / zz ), type(quad(grand3, 0, 1.0/ zz )))        
##########################################################################
#4*pi*SQRT(2); factor appears in partial width of 2 fermions
fac = 4.0 * np.sqrt(2.0) * PI 
############################
#############################
####Virtual Correction Functions r_i

##########################################################################
### Wilson coefficient at matching scale(mu_w)
####################### LO
def c0_7sm():
    x = xx
    chunk = - 8 * x**3 + 3 * x**2 + 12 * x - 7
    chunk1 = (18 * x**2 - 12 * x) * np.log(x)
    return x / 24 * ( (chunk + chunk1) / (x - 1)**4 )
def c0_8sm():
    x = xx
    chunk = - x**3 + 6 * x**2 - 3 * x - 2 - 6 * x * np.log(x)
    return x / 8 * ( chunk / (x - 1)**4 )
def c0_7yy(mass):
    y = yy(mass)
    chunk = - 8 * y**3 + 3 * y**2 + 12 * y - 7
    chunk1 = (18 * y**2 - 12 * y) * np.log(y)
    return y / 24 * ( (chunk + chunk1) / (y - 1)**4 ) * 1 / 3.0
def c0_8yy(mass):
    y = yy(mass)
    chunk = - y**3 + 6 * y**2 - 3 * y - 2 - 6 * y * np.log(y)
    return y / 8 * ( chunk / (y - 1)**4 ) * 1 / 3.0
def c0_7xy(mass):
    y = yy(mass)
    chunk = - 5 * y**2 + 8 * y  - 3
    chunk1 = (6 * y - 4) * np.log(y)
    return y / 12 * ( (chunk + chunk1) / (y - 1)**3)
def c0_8xy(mass):
    y = yy(mass)
    chunk = - y**2 + 4 * y - 3 - 2 * np.log(y)
    return y / 4 * ( chunk / (y - 1)**3 )
print('c0_7sm',c0_7sm(),c0_8sm())
##########################
########################## NLO
def E_0():#NLO
    x = NLOxx
    chunk_1 = x * (x**2 + 11 * x - 18) / (12 * (x - 1)**3)
    chunk_2 = x**2 * (4 * x**2 - 16 * x + 15) * np.log(x) / (6 * (x - 1)**4)
    chunk_3 = - 2 / 3 * np.log(x) - 2 / 3
    return chunk_1 + chunk_2 + chunk_3
def w7_sm():#NLO
    x = NLOxx
    chunk_1 = (- 16 * x**4 - 122 * x**3 + 80 * x**2 - 8 * x) / (9 * (x - 1)**4)
    chunk_2 = sp.spence( 1.0/x)
    chunk_3 = (6 * x**4 + 46 * x**3 - 28 * x**2) * (np.log(x))**2 / (3 * (x - 1)**5) 
    chunk_4 = (- 102 * x**5 - 588 * x**4 - 2262 * x**3 + 3244 * x**2 - 1364 * x + 208 ) * \
    np.log(x) / (81 * (x - 1)**5)
    chunk_5 = (1646 * x**4 + 12205 * x**3 - 10740 * x**2 + 2509 * x - 436) / (486 * (x - 1)**4)
    return chunk_1 * chunk_2 + chunk_3 + chunk_4 + chunk_5
def w8_sm():#NLO
    x = NLOxx
    chunk_1 = (- 4 * x**4 + 40 * x**3 + 41 * x**2 + x)/(6 * (x - 1)**4)
    chunk_2 = sp.spence( 1.0/x)
    chunk_3 = (- 17 * x**3 - 31 * x**2) * (np.log(x))**2 / (2 * (x - 1)**5)
    chunk_4 = (- 210 * x**5 + 1086 * x**4 + 4893 * x**3 + 2857 * x**2 - 1994 * x + 280) * \
    np.log(x) / (216 * (x - 1)**5)
    chunk_5 = (737 * x**4 - 14102 * x**3 - 28209 * x**2 + 610 * x - 508) \
    / (1296 * (x - 1)**4)
    return chunk_1 * chunk_2 + chunk_3 + chunk_4 + chunk_5
def m7_sm():#NLO
    x = NLOxx
    chunk_1 = 82 * x**5 + 301 * x**4 + 703 * x**3 - 2197 * x**2 + 1319 * x - 208
    chunk_2 = - (162 * x**4 + 1242 * x**3 - 756 * x**2) * np.log(x)
    return (chunk_1 + chunk_2) / (81 * (x - 1)**5)
def m8_sm():#NLO
    x = NLOxx
    chunk_1 = 77 * x**5 - 475 * x**4 - 1111 * x**3 + 607 * x**2 + 1042 * x - 140
    chunk_2 = ( 918 * x**3 + 1674 * x**2) * np.log(x)
    return (chunk_1 + chunk_2) / (108 * (x - 1)**5)
def t7_sm():#NLO
    x = NLOxx
    chunk_1 = 47 * x**3 - 63 * x**2 + 9 * x + 7 
    chunk_2 = - (18 * x**3 + 30 * x**2 - 24 * x) * np.log(x)
    return x / 3 * ( (chunk_1 + chunk_2) / ((x - 1)**5) )
def t8_sm():#NLO
    x = NLOxx
    chunk_1 = - x**3 - 9 * x**2 + 9 * x + 1 + (6 * x**2 + 6 * x) * np.log(x)
    chunk_2 = (x - 1)**5
    return 2.0 * x * (chunk_1 / chunk_2)
#coupling Y^2
def E_H(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = 7 * y**3 - 36 * y**2 + 45 * y - 16
    chunk_2 = (18 * y - 12) * np.log(y)
    return  y / 36 * ( (chunk_1 + chunk_2) / ((y - 1)**4) )
print('E_H(mass)',E_H(charHm_100))
def w7_yy(mass):#NLO
    y = NLOyy(mass)
    
    chunk_1 = (8 * y**3 - 37 * y**2 + 18 * y) / ((y - 1)**4)
    chunk_2 = sp.spence( 1.0 / y)
    chunk_3 = (3 * y**3 + 23 * y**2 - 14 * y) * (np.log(y))**2 / ((y - 1)**5)
    chunk_4 = (21 * y**4 - 192 * y**3 - 174 * y**2 + 251 * y - 50) \
    * np.log(y) / (9 * (y - 1)**5)
    chunk_5 = (- 1202 * y**3 + 7569 * y**2 - 5436 * y + 797) / (108 * (y - 1)**4)
    return 2 * y / 9 * (chunk_1 * chunk_2 + chunk_3 + chunk_4 + chunk_5) - \
4 / 9 * E_H(mass)
def w8_yy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = (13 * y**3 - 17 * y**2 + 30 * y) / ((y - 1)**4)
    chunk_2 = sp.spence( 1.0 / y)
    chunk_3 = - (17 * y**2 + 31 * y) / ((y - 1)**5) * (np.log(y))**2
    chunk_4 = (42 * y**4 + 318 * y**3 + 1353 * y**2 + 817 * y - 226) * \
np.log(y) / (36 * (y - 1)**5)
    chunk_5 = (- 4451 * y**3 + 7650 * y**2 - 18153 * y + 1130) / (216 * (y - 1)**4)
    return 1 / 6 * y * (chunk_1 * chunk_2 + chunk_3 + chunk_4 + chunk_5) - \
1 / 6 * E_H(mass)
def m7_yy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = - 14 * y**4 + 149 * y**3 - 153 * y**2 - 13 * y + 31
    chunk_2 = - (18 * y**3 + 138 * y**2 - 84 * y) * np.log(y)
    chunk_3 = (y - 1)**5
    return 1 / 27 * y * ( (chunk_1 + chunk_2) / chunk_3 )
def m8_yy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = - 7 * y**4 + 25 * y**3 - 279 * y**2 + 223 * y + 38 
    chunk_2 = (102 * y**2 + 186 * y) * np.log(y)
    chunk_3 = (y - 1)**5
    return 1 / 36 * y * ( (chunk_1 + chunk_2) / chunk_3)
def t7_yy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = 47 * y**3 - 63 * y**2 + 9 * y + 7 
    chunk_2 = - (18 * y**3 + 30 * y**2 - 24 * y) * np.log(y)
    return 1 / 3 * (y / 3 * ( (chunk_1 + chunk_2) / (y - 1)**5 ) )
def t8_yy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = - y**3 - 9 * y**2 + 9 * y + 1 + (6 * y**2 + 6 * y) * np.log(y)
    chunk_2 = (y - 1)**5
    return 1 / 3 * ( 2 * y * (chunk_1 / chunk_2) )

#Coupling (XY*)
def w7_xy(mass):#NLO
    y = NLOyy(mass)
    chunk_1 = (8 * y**2 - 28 * y + 12) / (3 * (y - 1)**3)
    chunk_2 = sp.spence( 1.0 / y)
    chunk_3 = (3 * y**2 + 14 * y - 8) * (np.log(y))**2 / (3 * (y - 1)**4)
    chunk_4 = (4 * y**3 - 24 * y**2 + 2 * y + 6 ) * np.log(y) / (3 * (y - 1)**4)
    chunk_5 = (- 2 * y**2 + 13 * y  - 7) / ((y - 1)**3)
    return 4 / 3 * y * (chunk_1 * chunk_2 + chunk_3 + chunk_4 + chunk_5)
def w8_xy(mass):#NLO
    y = NLOyy(mass)
    c1 = (17 * y**2 - 25 * y + 36) / (2 * (y - 1)**3)
    c2 = sp.spence( 1.0/ y)
    c3 = - (17 * y + 19) * (np.log(y))**2 / ((y - 1)**4)
    c4 = (14 * y**3 - 12 * y**2 + 187 * y + 3) * np.log(y) / (4 * (y - 1)**4)
    c5 = - (3 * (29 * y**2 - 44 * y + 143)) / (8 * (y - 1)**3)
    return 1 / 3 * y * (c1 * c2 + c3 + c4 + c5)
def m7_xy(mass):#NLO
    y = NLOyy(mass)
    c1 = - 8 * y**3 + 55 * y**2 - 68 * y + 21 
    c2 = - (6 * y**2 + 28 * y - 16) * np.log(y)
    c3 = (y - 1)**4
    return  2 / 9 * y * ( (c1 + c2) / c3 )
def m8_xy(mass):#NLO
    y = NLOyy(mass)
    c1 = - 7 * y**3 + 23 * y**2 - 97 * y  + 81
    c2 = (34 * y + 38) * np.log(y)
    c3 = (y - 1)**4
    return 1 / 6 * y * ( (c1 + c2) / c3 )
def t7_xy(mass):#NLO
    y = NLOyy(mass)
    c1 = 13 * y**2 - 20 * y + 7 - (6 * y**2 + 4 * y - 4) * np.log(y)
    c2 = (y - 1)**4
    return 2 / 3 * y * (c1 / c2)
def t8_xy(mass):#NLO
    y = NLOyy(mass)
    c1 = - y**2 - 4 * y + 5 + (4 * y + 2) * np.log(y)
    c2 = (y - 1)**4
    return 2 * y * (c1 / c2)
#####################################################
##################################################################
###################################################
#EQUATION 18
def c1_mu_effective(s,mass1,mass2,i1,j1,i2,j2):
    ratio1 = np.log(mt**2 / s**2)
    ratio = np.log(s**2 / mw**2)
    ratio2 = np.log(s**2/mass1**2)
    if np.any(mass2) == 0.0:
        ratio22 = 0.0
    else:
        ratio22 = np.log(s**2/(mass2)**2)
    ratio_muoverpi = NLOalpha_s(mw) / (4 * PI) 
#    print('yy()',yy())
#    print('w7_sm',w7_sm(),t7_sm() * (ratio1  - 4 / 3))
#    print('===',w8_yy(),w8_xy(),t8_xy(),t8_yy(),m8_xy())
    listsm7 =  w7_sm() + m7_sm() * ratio + \
        t7_sm() * (ratio1  - 4 / 3) #7
    listsm8 =  w8_sm() + m8_sm() * ratio + \
        t8_sm() * (ratio1  - 4 / 3) #8
    listyy7 =  w7_yy(mass1) + m7_yy(mass1) * ratio2 + \
        t7_yy(mass1) * (ratio1  - 4 / 3) #7
    listyy8 =  w8_yy(mass1) + m8_yy(mass1) * ratio2 + \
        t8_yy(mass1) * (ratio1  - 4 / 3) #8
    listxy7 =  w7_xy(mass1) + m7_xy(mass1) * ratio2 + \
        t7_xy(mass1) * (ratio1  - 4 / 3) #7
    listxy8 =  w8_xy(mass1) + m8_xy(mass1) * ratio2 + \
        t8_xy(mass1) * (ratio1  - 4 / 3) #8
    listyy72 =  w7_yy(mass2) + m7_yy(mass2) * ratio22 + \
        t7_yy(mass2) * (ratio1  - 4 / 3) #7
    listyy82 =  w8_yy(mass2) + m8_yy(mass2) * ratio22 + \
        t8_yy(mass2) * (ratio1  - 4 / 3) #8
    listxy72 =  w7_xy(mass2) + m7_xy(mass2) * ratio22 + \
        t7_xy(mass2) * (ratio1  - 4 / 3) #7
    listxy82 =  w8_xy(mass2) + m8_xy(mass2) * ratio22 + \
        t8_xy(mass2) * (ratio1  - 4 / 3) #8
#    print('LO_7sm()',c0_7sm())
#    print('LO_7xy()',c0_7xy())
#    print('LO_7yy()',c0_7yy())
#    print('NLO7_yy',mass1,s,listyy7,listyy8)
#    print('NLO7_xy',mass1, s,listxy7,listxy8)
#    print('w7_xy(mass1)',w7_xy(mass1),m7_xy(mass1),ratio2,t7_xy(mass1),ratio1,t7_xy(mass1) * (ratio1  - 4 / 3))
#    print('NLO7_xy',listxy7 * ratio_muoverpi + c0_7xy())
#    print('NLO7_yy',listyy7 * ratio_muoverpi + c0_7yy())
#    print('w8_xy()', w8_xy(),m8_xy(),t8_xy(),ratio2)
#    print('listxy8',listxy8,listsm8,c0_8yy())
    
    result_NLO7 = listsm7 + np.abs(i1)**2 * listyy7 + np.abs(i2)**2 * listyy72 + \
                  np.array(j1) * listxy7 + np.array(j2) * listxy72
    result_LO7 = c0_7sm() + np.abs(i1)**2 * c0_7yy(mass1) + np.array(j1) * c0_7xy(mass1) +\
                  np.abs(i2)**2 * c0_7yy(mass2) + np.array(j2) * c0_7xy(mass2)
###########                  
    result_LO2 = np.array([1.0]  )
    result_NLO2 = np.array([0.0]  )
###########
    result_NLO8 = listsm8 + np.abs(i1)**2 * listyy8 + np.abs(i2)**2 * listyy82 + \
                  np.array(j1) * listxy8 + np.array(j2) * listxy82
    result_LO8 = c0_8sm() + np.abs(i1)**2 * c0_8yy(mass1) + np.array(j1) * c0_8xy(mass1) +\
                  np.abs(i2)**2 * c0_8yy(mass2) + np.array(j2) * c0_8xy(mass2)
#    print('result_LO8',result_LO8,result_NLO8,listsm8,listyy8,listxy8)
    result2 = result_LO2 + ratio_muoverpi * result_NLO2 
    result7 = result_LO7 + ratio_muoverpi * result_NLO7
    result8 = result_LO8 + ratio_muoverpi * result_NLO8
    return [result_LO2,result_NLO2,result2,result_LO7,result_NLO7,result7,\
                     result_LO8,result_NLO8,result8]
print('_____________________________________________________________')
print('_____________________________________________________________')
#################################################################
# NLO Wislon coefficients at mu_b
#### Wilson coefficient at low scale(mu_b)
##############################LO
def C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2): #c0_7_eff(mu_b) LO
    eta = eta1(s1,s2) # alpha_s (mu_w) / alpha_s(mu_b)
    step1 = eta**(16 / 23) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[3]
    step2 = (eta**(14 / 23) - eta**(16 / 23) ) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[6]
    result1 = 0.0
    for n in np.arange(0,8):
#        print('ai*hi*1.0',a_i[n] * h_i[n] * c0_eff(s1,i,j)[1])
        result1 += (eta)**(a_i[n]) * h_i[n] * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[0]
    return step1 + 8 /3 * (step2) + result1
###############################NLO
def C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2): #c1_7_eff(mu_b) NLO
    eta = eta1(s1,s2)
    step1 = eta **(39 / 23) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[4]
#    print('c1_eff(s1,i,j)[6,m]',c1_eff(NLOalpha_s(mw),ll2,ll1)[6])
    step2 = 8 / 3 * (eta**(37 / 23) - eta**(39 / 23) ) *\
            c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[7]
    step3 = ((297664 / 14283) * eta**(16 / 23) - 7164416 / 357075 * eta**(14 / 23) +\
256868/14283 * (eta**(37 / 23)) - 6698884 / 357075 * eta**(39 / 23)) * \
             c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[6]
    step4 = 37208/4761 * (eta**(39 / 23) - eta**(16 / 23)) * \
            c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[3]
    result = 0.0
    c1_4effmw = E_0() + 2 / 3 * np.log(s1**2 / mw**2) + np.abs(i1)**2 * E_H(mass1) + \
                 np.abs(i2)**2 * E_H(mass2)

    for n in np.arange(0,8):
        step5 = e_i[n] * eta * c1_4effmw
        step6 = (f_i[n] + k_i[n] * eta) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[0]
        step7 = l_i[n] * eta * (15 + 6 * np.log(s1**2 / mw**2))
#        print('STEP',step5,step6,step7)
        result += (eta**(a_i[n])) * (step5 + step6 + step7)
#        print('result',result)
    return step1 + step2 + step3 + step4 + result
def C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2):
    eta = eta1(s1,s2) # alpha_s (mu_w) / alpha_s(mu_b)
    step1 =  eta**(6 / 23) - eta**(- 12 / 23) 
    return step1 * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[0]
def C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2):
    eta = eta1(s1,s2) # alpha_s (mu_w) / alpha_s(mu_b)
    step1 = 2 /3 * eta**(6 / 23) + 1 /3 * eta**(- 12 / 23) 
    return step1 * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[0]
def C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2):
    eta = eta1(s1,s2) # alpha_s (mu_w) / alpha_s(mu_b)
    step1 = eta**(14 / 23) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[6]
    result = 0.0
    for n in np.arange(0,5):
        result += h2_i[n] * eta**(a2_i[n]) * c1_mu_effective(s1,mass1,mass2,i1,j1,i2,j2)[0]        
    return step1 + result
#print('LO C1^1 muW = 4.8GeV',C0_1_eff(4.8,mw,100,300,[0],[0],[0],[0]))
#print('LO C2^1 muW = 4.8GeV',C0_2_eff(4.8,mw,100,300,[0],[0],[0],[0]))
#print('LO C7^1 muW = 4.8GeV',C0_7_eff(4.8,mw,100,300,[0],[0],[0],[0]))
#print('LO C8^1 muW = 4.8GeV',C0_8_eff(4.8,mw,100,300,[0],[0],[0],[0]))
#print('NLO C7^1 muW = 4.8GeV',C1_7_eff(4.8,mw,100,300,[0],[0],[0],[0]))
#####################################################################
####################################################################
####################################################################
def D_bar(s2,s1,mass1,mass2,i1,j1,i2,j2):#mu_b scale Reduced Amplitude LO
    # Riemann Zeta func- tion zeta_3
    zeta_3 = 1.2020569031595951
    L = np.log(zz)
    r2 = complex(2/243 * (-833 + 144 * PI**2 * zz**(3/2) + (1728 - 180 * PI**2 - 1296 * zeta_3 + \
       (1296 - 324 * PI**2) * L + 108 * L**2 + 36 * L**3 ) * zz + \
       (648 + 72 * PI**2 + (432 - 216 * PI**2) * L + 36 * L**3 ) * zz**2 + \
       (- 54 - 84 * PI**2 + 1092 * L - 756 * L**2) * zz**3) ,\
        16 * PI / 81 * (- 5 + (45 - 3 * PI**2 + 9 * L + 9 * L**2) * zz + \
        (- 3 * PI**2 + 9 * L**2) * zz**2 + (28 - 12 * L) * zz**3))
    r1 = - 1 / 6 * r2
    r7 = 32 / 9 - 8 / 9 * PI**2
    r8 = - 4 / 27 * complex(- 33 + 2 * PI**2, - 6 * PI )
    ans1 = C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r1 + 1 / 2.0 * gaeff.gamma0eff()[0][6] * np.log(mb**2 / s2**2 ))
    ans2 = C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r2 + 1 / 2.0 * gaeff.gamma0eff()[1][6] * np.log(mb**2 / s2**2 ))
    ans7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r7 + 1 / 2.0 * gaeff.gamma0eff()[6][6] * np.log(mb**2 / s2**2 ))
    ans8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r8 + 1 / 2.0 * gaeff.gamma0eff()[7][6] * np.log(mb**2 / s2**2 ))
#    print('gaeff.gamma0eff()17',gaeff.gamma0eff()[0][6])
#    print('gaeff.gamma0eff()27',gaeff.gamma0eff()[1][6])
#    print('gaeff.gamma0eff()77',gaeff.gamma0eff()[6][6])
#    print('gaeff.gamma0eff()87',gaeff.gamma0eff()[7][6])
    v_ub = ans1 + ans2 + ans7 + ans8 - 16 / 3.0 * \
    C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    return C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) + \
NLOalpha_s(s2) / (4 * PI) *  ((C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) +  v_ub) )
####################################################################

####################################################################
def NewDbarsquared(s2,s1,mass1,mass2,i1,j1,i2,j2):#mu_b scale Reduced Amplitude NLO
#    zeta_3 = 1.2021
    zeta_3 = 1.2020569031595951
    L = np.log(zz)
    r2 = complex(2/243 * (-833 + 144 * PI**2 * zz**(3/2) + (1728 - 180 * PI**2 - 1296 * zeta_3 + \
       (1296 - 324 * PI**2) * L + 108 * L**2 + 36 * L**3 ) * zz + \
       (648 + 72 * PI**2 + (432 - 216 * PI**2) * L + 36 * L**3 ) * zz**2 + \
       (- 54 - 84 * PI**2 + 1092 * L - 756 * L**2) * zz**3) ,\
        16 * PI / 81 * (- 5 + (45 - 3 * PI**2 + 9 * L + 9 * L**2) * zz + \
        (- 3 * PI**2 + 9 * L**2) * zz**2 + (28 - 12 * L) * zz**3))
    r1 = - 1 / 6 * r2
    r7 = 32 / 9 - 8 / 9 * PI**2
    r8 = - 4 / 27 * complex(- 33 + 2 * PI**2, - 6 * PI )
    ans1 = C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r1 + 1 / 2.0 * gaeff.gamma0eff()[0][6] * np.log(mb**2 / s2**2 ))
    ans2 = C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r2 + 1 / 2.0 * gaeff.gamma0eff()[1][6] * np.log(mb**2 / s2**2 ))
    ans7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r7 + 1 / 2.0 * gaeff.gamma0eff()[6][6] * np.log(mb**2 / s2**2 ))
    ans8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * \
    (r8 + 1 / 2.0 * gaeff.gamma0eff()[7][6] * np.log(mb**2 / s2**2 ))
#    print('zeta_3',zeta_3)
#    print('r1',r1)
#    print('r2',r2)
#    print('r7',r7)
#    print('r8',r8)
    v_ub = ans1 + ans2 + ans7 + ans8 - 16 / 3.0 * \
    C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    chunk1 = C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) + v_ub 
    chunk2 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    delta_D = NLOalpha_s(s2)/ (4 * PI) * chunk1 /  chunk2
    return abs(chunk2)**2 * (1 + 2 * np.real( delta_D) )
####################################################################

####################################################################
###########Decay_width of b > s gamma 
def decay_bsp(s2,s1,mass1,mass2,i1,j1,i2,j2):    
    return gf**2 / (32 * PI**4) * (vts * vtb)**2 * \
    alpha_electroweak * mb**5 * np.abs(D_bar(s2,s1,mass1,mass2,i1,j1,i2,j2))**2
####################################################################
def Amp(s2,s1,mass1,mass2,i1,j1,i2,j2):# A for Decay_width of b > s gamma gluon
        c0_1 = C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
        c0_2 = C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
        c0_7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
        c0_8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
#        print(c0_1,c0_2)
        f_22 = 16 * zz / 27 * quad(grand1, 0, 1.0 / zz  )[0] 
#        print('f_22',f_22)
        f_27 = - 8 * zz**2 / 9 * complex(quad(grand2, 0, 1.0 / zz )[0], quad(grand3, 0, 1.0 / zz )[0] ) 
#        print('f_27',f_27)
        f_11 = 1 /36 * f_22
        f_12 = - 1 /3 * f_22
        f_17 = - 1 /6 * f_27
        f_28 = - 1 /3 * f_27
        f_18 = - 1 /6 * f_28
        f_78 = 8 /9 * (25 /12 - PI**2 / 6)
        f_88 = 1 /27 * (16 /3 - 4 * PI**2 / 3 + 4 * np.log(mb / s2 ))
#        print('zz,s2,mb,mc',zz,s2,mb,mc)
#        print('f11',f_11,)
#        print('f12',f_12)
#        print('f17',f_17)
#        print('f18',f_18)
#        print('f_22',f_22)
#        print('f_27',f_27)
#        print('f_27',f_28)
#        print('f_78,f_88',f_78,f_88)
        summ11 = c0_1 * np.conjugate(c0_1) * f_11
        summ12 = c0_1 * np.conjugate(c0_2) * f_12
        summ17 = c0_1 * np.conjugate(c0_7) * f_17
        summ18 = c0_1 * np.conjugate(c0_8) * f_18
        summ22 = c0_2 * np.conjugate(c0_2) * f_22
        summ27 = c0_2 * np.conjugate(c0_7) * f_27
        summ28 = c0_2 * np.conjugate(c0_8) * f_28
        summ78 = c0_7 * np.conjugate(c0_8) * f_78
        summ88 = c0_8 * np.conjugate(c0_8) * f_88
        summ_all = np.real(summ11) + np.real(summ12) + np.real(summ17) + np.real(summ22)\
                    + np.real(summ27) + np.real(summ28)\
                    + np.real(summ78) + np.real(summ88) + np.real(summ18)
        return NLOalpha_s(s2) / PI * summ_all
print('D_bar_____________',D_bar(4.8,mw,100,300,[0],[0],[0],[0]))
print('D_bar**2_____________',NewDbarsquared(4.8,mw,100,300,[0],[0],[0],[0]))
print('Amp______________',Amp(4.8,mw,100,300,[0],[0],[0],[0]) )
###########Decay_width of b > s gamma gluon
def decay_bspg(s2,s1,mass1,mass2,i1,j1,i2,j2):
        a1 = gf**2 / (32 * PI**4) * (vts * vtb)**2 * \
        alpha_electroweak * mb**5 
        return a1 * Amp(s2,s1,mass1,mass2,i1,j1,i2,j2)  
###########Decay_width of semileptonic 
def decay_SL(s2):
    part1 = gf**2 /(192 * PI**3) * mb**5 * g_z
    part2 = 1 - 2 * NLOalpha_s(s2) * f_z / (3 * PI) \
    + delta_NP_SL / mb**2
    return part1 * part2
#print('Partial width of semileptonic decay', decay_SL() )
#################################################################
#################################################################
################################################################
#################### Partial width of B_bar > X_s + gamma
def decay_B_bar_Xsg(s2,s1,mass1,mass2,i1,j1,i2,j2):
    a1 = gf**2 / (32 * PI**4) * 1**2 * alpha_electroweak * mb**5 
#    chunk1 = abs(D_bar(s2,s1,mass1,mass2,i1,j1,i2,j2))**2 + \
    chunk1 =  NewDbarsquared(s2,s1,mass1,mass2,i1,j1,i2,j2) +\
             Amp(s2,s1,mass1,mass2,i1,j1,i2,j2) + (delta_NP_ga / mb**2) * \
             abs(C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2))**2 + \
             (delta_NP_c / mc**2) * \
      np.real(np.conj(C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)) *\
             (C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) - \
              C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * 1 / 6))
    return a1 * chunk1
def BR_B_Xs_gamma(s2,s1,mass1,mass2,i1,j1,i2,j2):
    return decay_B_bar_Xsg(s2,s1,mass1,mass2,i1,j1,i2,j2) \
          / decay_SL(s2) * B_SL 
#################################################################
#################################################################
#########################Partial width of B_bar > X_d + gamma
def decay_B_bar_Xdg(s2,s1,mass1,mass2,i1,j1,i2,j2):
    ###### Wolfenstein parametrization of the CKM matrix
    A,lamda1,rhho,etta = 0.819, 0.2196, 0.3, 0.34
    vcb = A * lamda1**2
    rho_bar = rhho * (1 - lamda1**2/2)
    eta_bar = etta * (1 - lamda1**2/2) 
    ###########################
    vstartdvtb = A * lamda1**3 * complex(1 - rho_bar , eta_bar)
    a1 = gf**2 / (32 * PI**4) * abs(vstartdvtb)**2 / abs(vcb)**2 \
            * alpha_electroweak * mb**5 
    chunk1 =  NewDbarsquared(s2,s1,mass1,mass2,i1,j1,i2,j2) +\
             Amp(s2,s1,mass1,mass2,i1,j1,i2,j2) + (delta_NP_ga / mb**2) * \
             abs(C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2))**2 + \
             (delta_NP_c / mc**2) * \
      np.real(np.conj(C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)) *\
             (C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) - \
              C0_1_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) * 1 / 6))
    return a1 * chunk1
def BR_B_Xd_gamma(s2,s1,mass1,mass2,i1,j1,i2,j2):
    return decay_B_bar_Xdg(s2,s1,mass1,mass2,i1,j1,i2,j2) \
          / decay_SL(s2) * B_SL 
print('SMBRBXSgamma______________',BR_B_Xs_gamma(4.8,mw,100,300,[0],[0],[0],[0]))
##################################################################
##################################################################
######### A_CP CP asymmetry  expression for B>Xs gamma and B>Xd gamma
######### https://arxiv.org/pdf/1012.3167v2.pdf
###################################################################
###################################################################
print('SMBRBXSgamma______________',BR_B_Xs_gamma(4.8,mw,100,300,[0],[0],[0],[0]))
def hadron_parameter():
    lamda_delat_c17 = 0.010 # 0.011 > new range -0.007 to 0.010
    lamda_delat_78 = 0.19  # 0.017 to 0.19 
    lamda_delat_u17 =  0.66#0.525 > new range -0.66 to 0.66
    return [lamda_delat_c17,lamda_delat_78,lamda_delat_u17]
###############################################################################
def newa_cp(s2,s1,mass1,mass2,i1,j1,i2,j2): # New B>X_s + gamma CP-asymmetry
    #PRL 106,141801 (2011) Formula 12 
    ###### Wolfenstein parametrization of the CKM matrix
    lamda1,rho_bar,eta_bar = 0.2254, 0.144, 0.342
    epsilon_s = lamda1**2 * complex(- rho_bar, eta_bar) / \
                (1 - lamda1**2 * 1 - rho_bar + 1j * eta_bar)
#    print('e_s',epsilon_s)
    lamda_delat_c17 = hadron_parameter()[0] #0.011
    lamda_delat_78 = hadron_parameter()[1]  #  0.017
    lamda_delat_u17 = hadron_parameter()[2] # 0.017
    lamda_c = 0.38 #Formula 4 
    espec = -1/3
#    c2,c7,c8 = 1j,1j,1j#1.204, - 0.381,- 0.175
    LOa = NLOalpha_s(s2)
    c2 = C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) + NLOalpha_s(s2) / \
         (4 * PI) * C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c2_c7 = c2/c7
    c8_c7 = c8/c7
    part1 = ((40 /81 - 40/9 * lamda_c/mb) * LOa / PI + \
             lamda_delat_c17/mb) * (c2_c7).imag
    part2 = ( 4 * LOa / (9 * PI )  -  4* PI * LOa *\
             espec * lamda_delat_78 / mb) * (c8_c7).imag
    part3 = ((lamda_delat_u17 - lamda_delat_c17)/mb + 40/9 * lamda_c/mb * \
             LOa / PI) * (epsilon_s * c2_c7).imag
    return (part1 - part2 - part3) * PI
####################################################################
def newa_cpd(s2,s1,mass1,mass2,i1,j1,i2,j2): # New B>X_d + gamma CP-asymmetry
    #PRL 106,141801 (2011) Formula 12 
    #and replace CKM matrix element from s to d
    ###### Wolfenstein parametrization of the CKM matrix
    rho_bar,eta_bar =  0.144, 0.342
    epsilon_d = (rho_bar - 1j * eta_bar) / (1 - rho_bar + 1j * eta_bar)
#    print('e_d',epsilon_d)
    ###########
    lamda_delat_c17 = hadron_parameter()[0] #0.011
    lamda_delat_78 = hadron_parameter()[1]  #  0.017
    lamda_delat_u17 = hadron_parameter()[2] # 0.017
    lamda_c = 0.38 #Formula 4 
#    c2,c7,c8 = 1j,1j,1j#1.204, - 0.381,- 0.175
    espec = -1/3
   
    LOa = NLOalpha_s(s2)
    c2 = C0_2_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2) + NLOalpha_s(s2) / \
         (4 * PI) * C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c2_c7 = c2/c7
    c8_c7 = c8/c7
    part1 = ((40 /81 - 40/9 * lamda_c/mb) * LOa / PI + lamda_delat_c17/mb) * \
    (c2_c7).imag
    part2 = ( 4 * LOa / (9 * PI)  -  4* PI * LOa * espec * lamda_delat_78 / mb) * \
    (c8_c7).imag
    part3 = ((lamda_delat_u17 - lamda_delat_c17)/mb + 40/9 * lamda_c/mb * LOa / PI) * \
    (epsilon_d * c2_c7).imag
#    print('1',((40 /81 - 40/9 * lamda_c/mb) * lamda_c/mb + lamda_delat_c17/mb) )
#    print('2',( 4 * lamda_c / (9 * mb)  -  4* PI * lamda_c/mb * PI * espec * lamda_delat_78 / mb))
#    print('3',((lamda_delat_u17 - lamda_delat_c17)/mb + 40/9 * lamda_c/mb * lamda_c/mb))
    return (part1 - part2 - part3) * PI
#######################################################################
def newdifferacps(s2,s1,mass1,mass2,i1,j1,i2,j2):#New CP difference of B>X_S + gamma
    #PRL 106,141801 (2011) formula 14
    LOa = LOalpha_s(s2)
    part1 = 4 * PI**2 * LOa * hadron_parameter()[1] / mb
    c7 = C0_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)# + NLOalpha_s(s2) / \
    #     (4 * PI) * C1_7_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c8 = C0_8_eff(s2,s1,mass1,mass2,i1,j1,i2,j2)
    c8_c7 = c8 / c7
    part2 = (c8_c7).imag
    return part1 * part2
######################################################################
def untag_cp(s2,s1,mass1,mass2,i1,j1,i2,j2): # Untagged CP-asymmetry(B>X_(s+d) + gamma)
    Rds = 1.73e-5/3.36e-5 # https://arxiv.org/pdf/hep-ex/0506079.pdf 
    s = newa_cp(s2,s1,mass1,mass2,i1,j1,i2,j2)
    d = newa_cpd(s2,s1,mass1,mass2,i1,j1,i2,j2)
    return (s + Rds * d) / (1 + Rds)
######################################################################
def sm_cps(u,c):
    u17 = u
    c17 = c
    return 1.15 * (u17 - c17)/0.3 + 0.71
def smm_directcps():#Formula 3
    #mu_scale = 2 #2 GeV
    alphas = 0.307 #from scale 2 GEV
    lamda1,rho_bar,eta_bar = 0.2254, 0.144, 0.342
    epsilon_s = lamda1**2 * complex(- rho_bar, eta_bar) / \
                (1 - lamda1**2 * complex(1 - rho_bar, eta_bar))
    lamda_c = 0.38 #Formula 4 
    c2,c7,c8 = 1.204, - 0.381,- 0.175
    part1 = 40 / 81 * np.imag(c2/c7)
    part2 = 4 / 9 * np.imag(c8/c7) 
    part3 = 40 * lamda_c / (9 * mb) * np.imag((1 + epsilon_s) * c2 /c7)   
    return alphas * (part1 - part2 - part3 )
######################################################################
def smm_cpsformula11():#Formula 11
    #mu_scale = 2 #2 GeV
    alphas = 0.307 #from scale 2 GEV
    lamda_delat_c17 = hadron_parameter()[0] #0.011
    lamda_delat_78 = hadron_parameter()[1]  #  0.017
    lamda_delat_u17 = hadron_parameter()[2] # 0.017
    lamda1,rho_bar,eta_bar = 0.2254, 0.144, 0.342
    epsilon_s = lamda1**2 * complex(- rho_bar, eta_bar) / \
                (1 - lamda1**2 * complex(1 - rho_bar, eta_bar))
    lamda_c = 0.38 #Formula 4 
    c2,c7,c8 = 1.204, - 0.381,- 0.175 #1,1,1
    part1 = np.abs(c2/c7)
    part2 = np.imag(epsilon_s)
    part3 = (lamda_delat_u17 - lamda_delat_c17)/mb + \
            40 * alphas * lamda_c / (9 * PI * mb)
    return PI * part1 * part2 * part3 
######################################################################
print('Newcps-asymmetry',newa_cp(mb,mw,80,170,[0.1],[0.1],[0.1],[complex(0.1,0.1)]))
print('Newcpd-asymmetry',newa_cpd(mb,mw,80,170,[0.1],[0.1],[0.1],[complex(0.1,0.1)]))
print('Newcps-asymmetrydifference',newdifferacps(mb,mw,80,170,[0.1],[0.1],[0.1],[complex(0.1,0.1)]))
print('NewUntagged (s + d) asymmetry',untag_cp(mb,mw,80,170,[0.1],[0.1],[0.1],[complex(0.1,0.1)]))
print('---------------------------------------------------------')
print(sm_cps(-0.33,-0.009),sm_cps(0.525,0.011),'newsmcps', sm_cps(-0.66,-0.007),sm_cps(0.66,0.01))
print('R_{ds}', 1.73e-5/3.36e-5,'Sigma_{R_ds}',np.sqrt((0.23/3.36)**2 + (0.22/1.73)**2) * (1.73e-5/3.36e-5))
print('Directasymmetry formula 3',smm_directcps())
print('SM CP-asymmetry X_s gamma formula 11',smm_cpsformula11())
print('---------------------------------------------------------')
print('SMBRBXSgamma______________',BR_B_Xs_gamma(mb,mw,100,300,[0],[0],[0],[0]))
print('SMcps-asymmetry',newa_cp(mb,mw,100,300,[0],[0],[0],[0]))
print('SMcpd-asymmetry',newa_cpd(mb,mw,100,300,[0],[0],[0],[0]))
print('SMcps-asymmetrydifference',newdifferacps(mb,mw,100,300,[0],[0],[0],[0]))
print('SMuntaggedcp(s+d)asymmetry',untag_cp(mb,mw,100,300,[0],[0],[0],[0]))

##############################################################################################