validphys.photon package

Submodules

validphys.photon.alpha module

Module that implements the alpha running

class validphys.photon.alpha.Alpha(theory, q2max)[source]

Bases: object

Class that solves the RGE for alpha_qed

alpha_em(q)[source]

Compute the value of the running alphaem.

Parameters: q (float) – value in which alphaem is computed
Returns: alpha_em – electromagnetic coupling
Return type: numpy.ndarray

alphaem_fixed_flavor_exa(q, alphaem_ref, qref, nf, nl)[source]

Compute numerically the running alphaem for nf fixed.

Parameters

q (float) – target scale
alph_aem_ref (float) – reference value of alpha_em
qref (float) – reference scale
nf (int) – number of flavors
nl (int) – number of leptons

Returns

alpha_em – target value of a

Return type

float

alphaem_fixed_flavor_trn(q, alphaem_ref, qref, nf, nl)[source]

Compute the running alphaem for nf fixed at, at least, NLO, using truncated method. In this case the RGE for alpha_em is solved decoupling it from the RGE for alpha_s (so the mixed terms are removed). alpha_s will just be unused.

Parameters

q (float) – target scale
alph_aem_ref (float) – reference value of alpha_em
qref (float) – reference scale
nf (int) – number of flavors
nl (int) – number of leptons

Returns

alpha_em at NLO – target value of a

Return type

float

compute_alphaem_at_thresholds()[source]: Compute and store alphaem at thresholds to speed up the calling to alpha_em inside fiatlux: when q is in a certain range (e.g. thresh_c < q < thresh_b) and qref in a different one (e.g. thresh_b < q < thresh_t) we need to evolve from qref to thresh_b with nf=5 and then from thresh_b to q with nf=4. Given that the value of alpha at thresh_b is always the same we can avoid computing the first step storing the values of alpha in the threshold points. It is done for qref in a generic range (not necessarly qref=91.2).

compute_betas(regions)[source]: Set values of betaQCD and betaQED.

find_region(q)[source]

interpolate_alphaem(q)[source]

Interpolate precomputed values of alpha_em.

Parameters: q (float) – value in which alpha_em is computed
Returns: alpha_em – electromagnetic coupling
Return type: float

validphys.photon.compute module

Module that calls fiatlux to add the photon PDF.

class validphys.photon.compute.Photon(theoryid, lux_params, replicas)[source]

Bases: object

Photon class computing the photon array with the LuxQED approach.

compute_photon_array(replica)[source]

Compute the photon PDF for every point in the grid xgrid.

Parameters: replica (int) – replica id
Returns: compute_photon_array – photon PDF at the fitting scale Q0
Return type: numpy.array

property error_matrix: Generate error matrix to be used in generate_errors.

generate_errors(replica)[source]: Generate LUX additional errors according to the procedure described in sec. 2.5 of https://arxiv.org/pdf/1712.07053.pdf