eko.evolution_operator package

Contains the central operator classes.

See Operator overview.

eko.evolution_operator.select_singlet_element(ker, mode0, mode1)

Select element of the singlet matrix.

Parameters:

• ker (numpy.ndarray) – singlet integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

singlet integration kernel element

Return type:

complex

eko.evolution_operator.select_QEDsinglet_element(ker, mode0, mode1)

Select element of the QEDsinglet matrix.

Parameters:

• ker (numpy.ndarray) – QEDsinglet integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

ker – QEDsinglet integration kernel element

Return type:

complex

eko.evolution_operator.select_QEDvalence_element(ker, mode0, mode1)

Select element of the QEDvalence matrix.

Parameters:

• ker (numpy.ndarray) – QEDvalence integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

ker – QEDvalence integration kernel element

Return type:

complex

class eko.evolution_operator.QuadKerBase(*args, **kwargs)

Bases: QuadKerBase

Manage the common part of Mellin inversion integral.

Parameters:

• u (float) – quad argument

• is_log (boolean) – is a logarithmic interpolation

• logx (float) – Mellin inversion point

• mode0 (str) – first sector element

class_type = jitclass.QuadKerBase#73a56d9d8550<is_singlet:bool,is_QEDsinglet:bool,is_QEDvalence:bool,is_log:bool,logx:float64,u:float64>

eko.evolution_operator.quad_ker(u, order, mode0, mode1, method, is_log, logx, areas, as_list, mu2_from, mu2_to, a_half, alphaem_running, nf, L, ev_op_iterations, ev_op_max_order, sv_mode, is_threshold, n3lo_ad_variation, is_polarized, is_time_like, use_fhmruvv)

Raw evolution kernel inside quad.

Parameters:

• u (float) – quad argument

• order (int) – perturbation order

• mode0 (int) – pid for first sector element

• mode1 (int) – pid for second sector element

• method (str) – method

• is_log (boolean) – is a logarithmic interpolation

• logx (float) – Mellin inversion point

• areas (tuple) – basis function configuration

• as1 (float) – target coupling value

• as0 (float) – initial coupling value

• mu2_from (float) – initial value of mu2

• mu2_from – final value of mu2

• aem_list (list) – list of electromagnetic coupling values

• alphaem_running (bool) – whether alphaem is running or not

• nf (int) – number of active flavors

• L (float) – logarithm of the squared ratio of factorization and renormalization scale

• ev_op_iterations (int) – number of evolution steps

• ev_op_max_order (int) – perturbative expansion order of U

• sv_mode (int, enum.IntEnum) – scale variation mode, see eko.scale_variations.Modes

• is_threshold (boolean) – is this an intermediate threshold operator?

• n3lo_ad_variation (tuple) – N3LO anomalous dimension variation (gg, gq, qg, qq, nsp, nsm, nsv)

• is_polarized (boolean) – is polarized evolution ?

• is_time_like (boolean) – is time-like evolution ?

• use_fhmruvv (bool) – if True use the FHMRUVV N3LO anomalous dimension

Returns:

evaluated integration kernel

Return type:

float

eko.evolution_operator.quad_ker_qcd(ker_base, order, mode0, mode1, method, as1, as0, nf, L, ev_op_iterations, ev_op_max_order, sv_mode, is_threshold, is_polarized, is_time_like, n3lo_ad_variation, use_fhmruvv)

Raw evolution kernel inside quad.

Parameters:

• quad_ker (float) – quad argument

• order (int) – perturbation order

• mode0 (int) – pid for first sector element

• mode1 (int) – pid for second sector element

• method (str) – method

• as1 (float) – target coupling value

• as0 (float) – initial coupling value

• nf (int) – number of active flavors

• L (float) – logarithm of the squared ratio of factorization and renormalization scale

• ev_op_iterations (int) – number of evolution steps

• ev_op_max_order (int) – perturbative expansion order of U

• sv_mode (int, enum.IntEnum) – scale variation mode, see eko.scale_variations.Modes

• is_threshold (boolean) – is this an itermediate threshold operator?

• n3lo_ad_variation (tuple) – N3LO anomalous dimension variation (gg, gq, qg, qq, nsp, nsm, nsv)

• use_fhmruvv (bool) – if True use the FHMRUVV N3LO anomalous dimensions

Returns:

evaluated integration kernel

Return type:

float

eko.evolution_operator.quad_ker_qed(ker_base, order, mode0, mode1, method, as_list, mu2_from, mu2_to, a_half, alphaem_running, nf, L, ev_op_iterations, ev_op_max_order, sv_mode, is_threshold, n3lo_ad_variation, use_fhmruvv)

Raw evolution kernel inside quad.

Parameters:

• ker_base (QuadKerBase) – quad argument

• order (int) – perturbation order

• mode0 (int) – pid for first sector element

• mode1 (int) – pid for second sector element

• method (str) – method

• as1 (float) – target coupling value

• as0 (float) – initial coupling value

• mu2_from (float) – initial value of mu2

• mu2_from – final value of mu2

• aem_list (list) – list of electromagnetic coupling values

• alphaem_running (bool) – whether alphaem is running or not

• nf (int) – number of active flavors

• L (float) – logarithm of the squared ratio of factorization and renormalization scale

• ev_op_iterations (int) – number of evolution steps

• ev_op_max_order (int) – perturbative expansion order of U

• sv_mode (int, enum.IntEnum) – scale variation mode, see eko.scale_variations.Modes

• is_threshold (boolean) – is this an itermediate threshold operator?

• n3lo_ad_variation (tuple) – N3LO anomalous dimension variation (gg, gq, qg, qq, nsp, nsm, nsv)

• use_fhmruvv (bool) – if True use the FHMRUVV N3LO anomalous dimensions

Returns:

evaluated integration kernel

Return type:

float

eko.evolution_operator.OpMembers

Map of all operators.

alias of Dict[Tuple[int, int], OpMember]

class eko.evolution_operator.Managers(atlas: Atlas, couplings: Couplings, interpolator: InterpolatorDispatcher)

Bases: object

Set of steering objects.

atlas: Atlas

couplings: Couplings

interpolator: InterpolatorDispatcher

class eko.evolution_operator.Operator(config, managers: Managers, segment: Segment, mellin_cut=0.05, is_threshold=False)

Bases: ScaleVariationModeMixin

Internal representation of a single EKO.

The actual matrices are computed upon calling compute().

Parameters:

• config (dict) – configuration

• managers (dict) – managers

• nf (int) – number of active flavors

• q2_from (float) – evolution source

• q2_to (float) – evolution target

• mellin_cut (float) – cut to the upper limit in the mellin inversion

• is_threshold (bool) – is this an itermediate threshold operator?

log_label = 'Evolution'

full_labels: Tuple[Tuple[int, int], ...] = ((100, 100), (100, 21), (21, 100), (21, 21), (10201, 0), (10101, 0), (10200, 0))

full_labels_qed: Tuple[Tuple[int, int], ...] = ((21, 21), (21, 22), (21, 100), (21, 101), (22, 21), (22, 22), (22, 100), (22, 101), (100, 21), (100, 22), (100, 100), (100, 101), (101, 21), (101, 22), (101, 100), (101, 101), (10200, 10200), (10200, 10204), (10204, 10200), (10204, 10204), (10103, 0), (10203, 0), (10102, 0), (10202, 0))

property n_pools

Return number of parallel cores.

property xif2

Return scale variation factor \((\mu_F/\mu_R)^2\).

property int_disp: InterpolatorDispatcher

Return the interpolation dispatcher.

property grid_size

Return the grid size.

property mu2

Return the arguments to the \(a_s\) function.

compute_a()

Return the computed values for \(a_s\) and \(a_{em}\).

property a_s

Return the computed values for \(a_s\).

property a_em

Return the computed values for \(a_{em}\).

compute_aem_list()

Return the list of the couplings for the different values of \(a_s\).

This functions is needed in order to compute the values of \(a_s\) and \(a_em\) in the middle point of the \(mu^2\) interval, and the values of \(a_s\) at the borders of every intervals. This is needed in the running_alphaem solution.

property labels

Compute necessary sector labels to compute.

Returns:

sector labels

Return type:

list(str)

property ev_method

Return the evolution method.

quad_ker(label, logx, areas)

Return partially initialized integrand function.

Parameters:

• label (tuple) – operator element pids

• logx (float) – Mellin inversion point

• areas (tuple) – basis function configuration

Returns:

partially initialized integration kernel

Return type:

functools.partial

initialize_op_members()

Init all operators with the identity or zeros.

run_op_integration(log_grid)

Run the integration for each grid point.

Parameters:

log_grid (tuple(k, logx)) – log grid point with relative index

Returns:

computed operators at the give grid point

Return type:

list

compute()

Compute the actual operators (i.e. run the integrations).

integrate()

Run the integration.

copy_ns_ops()

Copy non-singlet kernels, if necessary.

Submodules

eko.evolution_operator.flavors module

The write-up of the matching conditions is given in Matching Conditions.

eko.evolution_operator.flavors.pids_from_intrinsic_evol(label, nf, normalize)

Obtain the list of pids with their corresponding weight, that are contributing to evol.

The normalization of the weights is only needed for the output rotation:

• if we want to build e.g. the singlet in the initial state we simply have to sum to obtain \(\Sigma = u + \bar u + d + \bar d + \ldots\)

• if we want to rotate back in the output we have to normalize the weights: e.g. in nf=3 \(u = \frac 1 6 \Sigma + \frac 1 6 V + \ldots\)

The normalization can only happen here since we’re actively cutting out some flavor (according to nf).

Parameters:

• label (str) – evolution label

• nf (int) – maximum number of light flavors

• normalize (bool) – normalize output

Returns:

list of weights

Return type:

list(float)

eko.evolution_operator.flavors.get_range(evol_labels, qed)

Determine the number of light and heavy flavors participating in the input and output.

Here, we assume that the T distributions (e.g. T15) appears always before the corresponding V distribution (e.g. V15).

Parameters:

qed (bool) – activate qed

Returns:

• nf_in (int) – number of light flavors in the input

• nf_out (int) – number of light flavors in the output

eko.evolution_operator.flavors.rotate_pm_to_flavor(label)

Rotate from +- basis to flavor basis.

Parameters:

label (str) – label

Returns:

list of weights

Return type:

list(float)

eko.evolution_operator.flavors.rotate_matching(nf, qed, inverse=False)

Rotation between matching basis (with e.g. S,g,…V8 and c+,c-) and new true evolution basis (with S,g,…V8,T15,V15).

Parameters:

• nf (int) – number of active flavors in the higher patch: to activate T15, nf=4

• qed (bool) – use QED?

• inverse (bool) – use inverse conditions?

Returns:

mapping in dot notation between the bases

Return type:

dict

eko.evolution_operator.flavors.rotate_matching_inverse(nf, qed)

Inverse rotation between matching basis (with e.g. S,g,…V8 and c+,c-) and new true evolution basis (with S,g,…V8,T15,V15).

Parameters:

• nf (int) – number of active flavors in the higher patch: to activate T15, nf=4

• qed (bool) – use QED?

Returns:

mapping in dot notation between the bases

Return type:

dict

eko.evolution_operator.flavors.qed_rotation_parameters(nf)

Parameters of the QED basis rotation.

From \((\Sigma, \Sigma_{\Delta}, h_+)\) into \((\Sigma, \Sigma_{\Delta}, T_i^j)\), or equivalentely for \(V, V_{\Delta}, V_i^j, h_-\).

Parameters:

nf (int) – number of active flavors in the higher patch: e.g. to activate \(T_3^u\) or \(V_3^u\) choose nf=4

Returns:

a,b,c,d,e,f – Parameters of the rotation: \(\Sigma_{\Delta} = a*\Sigma + b*\Sigma_{\Delta} + c*h_+, T_i = d*\Sigma + e*\Sigma_{\Delta} + f*h_+\)

Return type:

float

eko.evolution_operator.flavors.pids_from_intrinsic_unified_evol(label, nf, normalize)

Obtain the list of pids with their corresponding weight, that are contributing to intrinsic unified evolution.

Parameters:

• evol (str) – evolution label

• nf (int) – maximum number of light flavors

• normalize (bool) – normalize output

Returns:

list of weights

Return type:

list(float)

eko.evolution_operator.matching_condition module

Defines the matching conditions for the VFNS evolution.

class eko.evolution_operator.matching_condition.MatchingCondition(op_members, q2_final)

Bases: OperatorBase

Matching conditions for PDF at threshold.

The continuation of the (formally) heavy non-singlet distributions with either the full singlet \(S\) or the full valence \(V\) is considered “trivial”. Instead at NNLO additional terms (“non-trivial”) enter.

classmethod split_ad_to_evol_map(op_members, nf, q2_thr, qed=False)

Create the instance from the OME.

Parameters:

• op_members (eko.operator_matrix_element.OperatorMatrixElement.op_members) – Attribute of OperatorMatrixElement containing the OME

• nf (int) – number of active flavors below the threshold

• q2_thr (float) – threshold value

• qed (bool) – activate qed

eko.evolution_operator.operator_matrix_element module

The OME for the non-trivial matching conditions in the VFNS evolution.

class eko.evolution_operator.operator_matrix_element.MatchingMethods(value)

Bases: IntEnum

Enumerate matching methods.

FORWARD = 1

BACKWARD_EXACT = 2

BACKWARD_EXPANDED = 3

eko.evolution_operator.operator_matrix_element.matching_method(s: InversionMethod | None) → MatchingMethods

Return the matching method.

Parameters:

s – string representation

Returns:

int representation

Return type:

i

eko.evolution_operator.operator_matrix_element.build_ome(A, matching_order, a_s, backward_method)

Construct the matching expansion in \(a_s\) with the appropriate method.

Parameters:

• A (numpy.ndarray) – list of OME

• matching_order (tuple(int,int)) – perturbation matching order

• a_s (float) – strong coupling, needed only for the exact inverse

• backward_method (MatchingMethods) – empty or method for inverting the matching condition (exact or expanded)

Returns:

ome – matching operator matrix

Return type:

numpy.ndarray

eko.evolution_operator.operator_matrix_element.quad_ker(u, order, mode0, mode1, is_log, logx, areas, a_s, nf, L, sv_mode, Lsv, backward_method, is_msbar, is_polarized, is_time_like)

Raw kernel inside quad.

Parameters:

• u (float) – quad argument

• order (tuple(int,int)) – perturbation matching order

• mode0 (int) – pid for first element in the singlet sector

• mode1 (int) – pid for second element in the singlet sector

• is_log (boolean) – logarithmic interpolation

• logx (float) – Mellin inversion point

• areas (tuple) – basis function configuration

• a_s (float) – strong coupling, needed only for the exact inverse

• nf (int) – number of active flavor below threshold

• L (float) – :math:\ln(\mu_F^2 / m_h^2)

• backward_method (InversionMethod or None) – empty or method for inverting the matching condition (exact or expanded)

• is_msbar (bool) – add the \(\overline{MS}\) contribution

• is_polarized (boolean) – is polarized evolution ?

• is_time_like (boolean) – is time-like evolution ?

Returns:

ker – evaluated integration kernel

Return type:

float

class eko.evolution_operator.operator_matrix_element.OperatorMatrixElement(config, managers: Managers, nf: int, q2: float, is_backward: bool, L: float, is_msbar: bool)

Bases: Operator

Internal representation of a single OME.

The actual matrices are computed upon calling compute().

Parameters:

• config (dict) – configuration

• managers (dict) – managers

• nf (int) – number of active flavor below threshold

• q2 (float) – squared matching scale

• is_backward (bool) – True for backward matching

• L (float) – \(\ln(\mu_F^2 / m_h^2)\)

• is_msbar (bool) – add the \(\overline{MS}\) contribution

log_label = 'Matching'

full_labels: Tuple[OperatorLabel, ...] = ((100, 100), (100, 21), (21, 100), (21, 21), (90, 21), (90, 100), (21, 90), (100, 90), (90, 90), (200, 200), (200, 91), (91, 200), (91, 91))

full_labels_qed: Tuple[OperatorLabel, ...] = ((100, 100), (100, 21), (21, 100), (21, 21), (90, 21), (90, 100), (21, 90), (100, 90), (90, 90), (200, 200), (200, 91), (91, 200), (91, 91))

property labels

Necessary sector labels to compute.

Returns:

sector labels

Return type:

list(str)

quad_ker(label, logx, areas)

Return partially initialized integrand function.

Parameters:

• label (tuple) – operator element pids

• logx (float) – Mellin inversion point

• areas (tuple) – basis function configuration

Returns:

partially initialized integration kernel

Return type:

functools.partial

property a_s

Return the computed values for \(a_s\).

Note that here you need to use \(a_s^{n_f+1}\)

compute()

Compute the actual operators (i.e. run the integrations).

eko.evolution_operator.physical module

Contains the PhysicalOperator class.

class eko.evolution_operator.physical.PhysicalOperator(op_members, q2_final)

Bases: OperatorBase

Join several fixed flavor scheme operators together.

• provides the connection between the 7-dimensional anomalous dimension basis and the 15-dimensional evolution basis

• provides the connection between the 15-dimensional evolution basis and the 169-dimensional flavor basis

Parameters:

• op_members (dict) – list of all members

• q2_final (float) – final scale

classmethod ad_to_evol_map(op_members, nf, q2_final, qed=False)

Obtain map between the 3-dimensional anomalous dimension basis and the 4-dimensional evolution basis.

Todo

in VFNS sometimes IC is irrelevant if nf>=4

Parameters:

• op_members (dict) – operator members in anomalous dimension basis

• nf (int) – number of active light flavors

• qed (bool) – activate qed

Returns:

m – map

Return type:

dict

eko.evolution_operator.quad_ker module

Integration kernels.

eko.evolution_operator.quad_ker.select_singlet_element(ker, mode0, mode1)

Select element of the singlet matrix.

Parameters:

• ker (numpy.ndarray) – singlet integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

singlet integration kernel element

Return type:

complex

eko.evolution_operator.quad_ker.build_ome(A, matching_order, a_s, backward_method)

Construct the matching expansion in \(a_s\) with the appropriate method.

Parameters:

• A (numpy.ndarray) – list of OME

• matching_order (tuple(int,int)) – perturbation matching order

• a_s (float) – strong coupling, needed only for the exact inverse

• backward_method (InversionMethod or None) – empty or method for inverting the matching condition (exact or expanded)

Returns:

ome – matching operator matrix

Return type:

numpy.ndarray

eko.evolution_operator.quad_ker.select_QEDsinglet_element(ker, mode0, mode1)

Select element of the QEDsinglet matrix.

Parameters:

• ker (numpy.ndarray) – QEDsinglet integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

ker – QEDsinglet integration kernel element

Return type:

complex

eko.evolution_operator.quad_ker.select_QEDvalence_element(ker, mode0, mode1)

Select element of the QEDvalence matrix.

Parameters:

• ker (numpy.ndarray) – QEDvalence integration kernel

• mode0 (int) – id for first sector element

• mode1 (int) – id for second sector element

Returns:

ker – QEDvalence integration kernel element

Return type:

complex