def get_subleading(q2, wc_obj, par_dict, B, P, lep, cp_conjugate):
if q2 <= 9:
sub_name = B+'->'+P + 'll subleading effects at low q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
elif q2 > 14:
sub_name = B+'->'+P + 'll subleading effects at high q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
else:
return {}
def get_subleading(q2, wc_obj, par_dict, B, V, cp_conjugate):
if q2 <= 9:
sub_name = B + '->' + V + 'll subleading effects at low q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(
par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
elif q2 > 14:
sub_name = B + '->' + V + 'll subleading effects at high q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(
par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
else:
return {}
def get_subleading_high(q2, wc_obj, par_dict, B, V, cp_conjugate):
if q2 < 14:
return {
('0', 'V'): 0,
('pl', 'V'): 0,
('mi', 'V'): 0,
}
sub_name = B + '->' + V + 'll subleading effects at high q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(
par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
def amps_subleading(wc_obj, par, B, V, cp_conjugate):
scale = config['renormalization scale']['bvgamma']
sub_name = B+'->'+V+ 'll subleading effects at low q2'
q2=0.001 # away from zero to avoid pole
amps = AuxiliaryQuantity.get_instance(sub_name).prediction(par_dict=par, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
N = prefactor_helicityamps(q2, par, B, V)
a = {}
a['L'] = -N * amps[('mi' ,'V')]
a['R'] = +N * amps[('pl' ,'V')]
return a
def get_ss(q2, wc_obj, par_dict, B, V, cp_conjugate):
# this only needs to be done for low q2 - which doesn't exist for taus!
if q2 >= 8.9:
return {
('0', 'V'): 0,
('pl', 'V'): 0,
('mi', 'V'): 0,
}
ss_name = B + '->' + V + 'll spectator scattering'
return AuxiliaryQuantity.get_instance(ss_name).prediction(
par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
def amps_subleading(wc_obj, par, B, V, cp_conjugate):
scale = config['renormalization scale']['bvgamma']
sub_name = B + '->' + V + 'll subleading effects at low q2'
q2 = 0.001 # away from zero to avoid pole
amps = AuxiliaryQuantity.get_instance(sub_name).prediction(
par_dict=par, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
N = prefactor_helicityamps(q2, par, B, V)
a = {}
a['L'] = -N * amps[('mi', 'V')]
a['R'] = +N * amps[('pl', 'V')]
return a
def amps_subleading(wc_obj, par, B, V, cp_conjugate):
scale = config["renormalization scale"]["bvgamma"]
sub_name = B + "->" + V + "ll subleading effects at low q2"
q2 = 0.001 # away from zero to avoid pole
amps = AuxiliaryQuantity.get_instance(sub_name).prediction(
par_dict=par, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate
)
N = prefactor_helicityamps(q2, par, B, V)
a = {}
a["L"] = -N * amps[("mi", "V")]
a["R"] = +N * amps[("pl", "V")]
return a
def amps_ff(wc_obj, par_dict, B, V, cp_conjugate):
par = par_dict.copy()
if cp_conjugate:
par = conjugate_par(par)
N = prefactor(par, B, V)
bq = meson_quark[(B, V)]
ff_name = meson_ff[(B, V)] + " form factor"
ff = AuxiliaryQuantity.get_instance(ff_name).prediction(par_dict=par, wc_obj=None, q2=0.0)
scale = config["renormalization scale"]["bvgamma"]
# these are the b->qee Wilson coefficients - they contain the b->qgamma ones as a subset
wc = wctot_dict(wc_obj, bq + "ee", scale, par)
if cp_conjugate:
wc = conjugate_wc(wc)
delta_C7 = flavio.physics.bdecays.matrixelements.delta_C7(par=par, wc=wc, q2=0, scale=scale, qiqj=bq)
a = {}
a["L"] = N * (wc["C7eff_" + bq] + delta_C7) * ff["T1"]
a["R"] = N * wc["C7effp_" + bq] * ff["T1"]
return a
def amps_ff(wc_obj, par_dict, B, V, cp_conjugate):
par = par_dict.copy()
if cp_conjugate:
par = conjugate_par(par)
N = prefactor(par, B, V)
bq = meson_quark[(B,V)]
ff_name = meson_ff[(B,V)] + ' form factor'
ff = AuxiliaryQuantity.get_instance(ff_name).prediction(par_dict=par, wc_obj=None, q2=0.)
scale = config['renormalization scale']['bvgamma']
# these are the b->qee Wilson coefficients - they contain the b->qgamma ones as a subset
wc = wctot_dict(wc_obj, bq+'ee', scale, par)
if cp_conjugate:
wc = conjugate_wc(wc)
delta_C7 = flavio.physics.bdecays.matrixelements.delta_C7(par=par, wc=wc, q2=0, scale=scale, qiqj=bq)
a = {}
a['L'] = N * (wc['C7eff_'+bq] + delta_C7) * ff['T1']
a['R'] = N * wc['C7effp_'+bq] * ff['T1']
return a
def amps_ff(wc_obj, par_dict, B, V, cp_conjugate):
par = par_dict.copy()
if cp_conjugate:
par = conjugate_par(par)
N = prefactor(par, B, V)
bq = meson_quark[(B, V)]
ff_name = meson_ff[(B, V)] + ' form factor'
ff = AuxiliaryQuantity.get_instance(ff_name).prediction(par_dict=par,
wc_obj=None,
q2=0.)
scale = config['renormalization scale']['bvgamma']
# these are the b->qee Wilson coefficients - they contain the b->qgamma ones as a subset
wc = wctot_dict(wc_obj, bq + 'ee', scale, par)
if cp_conjugate:
wc = conjugate_wc(wc)
delta_C7 = flavio.physics.bdecays.matrixelements.delta_C7(par=par,
wc=wc,
q2=0,
scale=scale,
qiqj=bq)
a = {}
a['L'] = N * (wc['C7eff_' + bq] + delta_C7) * ff['T1']
a['R'] = N * wc['C7effp_' + bq] * ff['T1']
return a
def get_ff(q2, par, B, V):
ff_name = meson_ff[(B, V)] + ' form factor'
return AuxiliaryQuantity.get_instance(ff_name).prediction(par_dict=par,
wc_obj=None,
q2=q2)
def get_ff(q2, par, B, P):
ff_name = meson_ff[(B,P)] + ' form factor'
return AuxiliaryQuantity.get_instance(ff_name).prediction(par_dict=par, wc_obj=None, q2=q2)
def get_ckm(par_dict):
return AuxiliaryQuantity.get_instance('CKM matrix').prediction(par_dict=par_dict, wc_obj=None)
def get_subleading_high(q2, wc_obj, par_dict, B, V, cp_conjugate):
if q2 < 14:
return {('0' ,'V'): 0, ('pl' ,'V'): 0, ('mi' ,'V'): 0, }
sub_name = B+'->'+V + 'll subleading effects at high q2'
return AuxiliaryQuantity.get_instance(sub_name).prediction(par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
def get_ss(q2, wc_obj, par_dict, B, V, cp_conjugate):
# this only needs to be done for low q2 - which doesn't exist for taus!
if q2 >= 8.9:
return {('0' ,'V'): 0, ('pl' ,'V'): 0, ('mi' ,'V'): 0, }
ss_name = B+'->'+V+'ll spectator scattering'
return AuxiliaryQuantity.get_instance(ss_name).prediction(par_dict=par_dict, wc_obj=wc_obj, q2=q2, cp_conjugate=cp_conjugate)
def get_ff(q2, par):
ff_aux = AuxiliaryQuantity.get_instance('Lambdab->Lambda form factor')
return ff_aux.prediction(par_dict=par, wc_obj=None, q2=q2)
