How to use the smelli.ckm.CKMScheme function in smelli

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github smelli / smelli / smelli / ckm.py View on Github external
def ckm_np(self, w=None, iterate=10):
        """Return the central values for the four CKM parameters
        `Vus`, `Vcb`, `Vub`, `delta`,
        in the presence of new physics (parametrized by a `wilson.Wilson`
        instance `w`) """
        Vus, Vcb, Vub, delta = [self.ckm_initial[p] for p in ['Vus', 'Vcb', 'Vub', 'delta']]
        for _ in range(iterate):
            if w is None:
                Vus, Vcb, Vub, delta = self._ckm_np(w=None, Vus=Vus, Vcb=Vcb, Vub=Vub, delta=delta)
            else:
                w.set_option('parameters', {'Vus': Vus, 'Vcb': Vcb, 'Vub': Vub, 'gamma': delta})
                Vus, Vcb, Vub, delta = self._ckm_np(w, Vus=Vus, Vcb=Vcb, Vub=Vub, delta=delta)
        return Vus, Vcb, Vub, delta


class CKMSchemeRmuBtaunuBxlnuDeltaM(CKMScheme):
    """CKM scheme where the four input observables are given by:
    - 'RKpi(P+->munu)' (mostly fixing `Vus`)
    - 'BR(B->Xcenu)' (fixing `Vcb`)
    - 'BR(B+->taunu)' (fixing `Vub`)
    - 'DeltaM_d/DeltaM_s' (mostly fixing `delta`)
    """

    observables=[
        'RKpi(P+->munu)',
        'BR(B->Xcenu)',
        'BR(B+->taunu)',
        'DeltaM_d/DeltaM_s'
    ]

    @staticmethod
    def ckm_fac(Vus, Vcb, Vub, delta):
github smelli / smelli / smelli / ckm.py View on Github external
def get_ckm_schemes():
    return {
        k: v() for k,v in globals().items()
        if inspect.isclass(v)
        and issubclass(v, CKMScheme)
        and len(v.observables) == 4
    }

smelli

A Python package providing a global likelihood function in the space of dimension-6 Wilson coefficients of the Standard Model Effective Field Theory (SMEFT)

MIT
Latest version published 2 months ago

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