address review comments

doc/source/shared/abbreviations.rst

@@ -77,6 +77,7 @@
 
 .. |BFKL| replace::
    :abbr:`BFKL (Balitsky-Fadin-Kuraev-Lipatov)`
+
 .. external
 
 .. |yadism| replace::
@@ -91,7 +92,6 @@
 .. |pineko| replace::
    :pineko:`\ `
 
-
 .. |APFEL| raw:: html
 
    <a href="https://apfel.mi.infn.it/"><abbr title="A PDF Evolution Library">APFEL</abbr></a>
@@ -108,6 +108,9 @@
 
    <a href="https://www.nikhef.nl/~h24/qcdnum/"><abbr title="Quantum ChromoDynamics NUM">QCDNUM</abbr></a>
 
+.. |FHMRUVV| replace::
+   :abbr:`FHMRUVV (Falcioni, Herzog, Moch, Ruijl, Ueda, Vermaseren and Vogt)`
+
 .. |T| raw:: html
 
    <span class="green">✓</span>

extras/lh_bench_23/run-n3lo.py

@@ -35,7 +35,7 @@
     parser.add_argument("sv", help="scale variation: up, central, or down")
     parser.add_argument(
         "ad_variation",
-        help="n3lo anomalous dimension variation: (gg_var, gq_var, qg_var, qq_var, nsp_var, nsm_var, nsv_var)",
+        help="n3lo anomalous dimension variation: (gg, gq, qg, qq, nsp, nsm, nsv)",
         nargs="*",
         type=int,
     )

src/eko/evolution_operator/__init__.py

@@ -262,7 +262,7 @@ def quad_ker(
     is_time_like : boolean
         is time-like evolution ?
     use_fhmruvv : bool
-        if True use the Falcioni, Herzog, Moch, Ruijl, Ueda, Vermaseren, Vogt N3LO anomalous dimension
+        if True use the |FHMRUVV| |N3LO| anomalous dimension
 
     Returns
     -------
@@ -371,7 +371,7 @@ def quad_ker_qcd(
     n3lo_ad_variation : tuple
         |N3LO| anomalous dimension variation ``(gg, gq, qg, qq, nsp, nsm, nsv)``
     use_fhmruvv : bool
-        if True use the Falcioni, Herzog, Moch, Ruijl, Ueda, Vermaseren, Vogt N3LO anomalous dimensions
+        if True use the |FHMRUVV| |N3LO| anomalous dimensions
 
     Returns
     -------
@@ -501,7 +501,7 @@ def quad_ker_qed(
     is_threshold : boolean
         is this an itermediate threshold operator?
     n3lo_ad_variation : tuple
-        |N3LO| anomalous dimension variation ``(gg_var, gq_var, qg_var, qq_var)``
+        |N3LO| anomalous dimension variation ``(gg, gq, qg, qq)``
 
     Returns
     -------

src/eko/io/runcards.py

@@ -48,7 +48,7 @@ class TheoryCard(DictLike):
     n3lo_ad_variation: N3LOAdVariation
     """|N3LO| anomalous dimension variation: ``(gg, gq, qg, qq, nsp, nsm, nsv)``."""
     use_fhmruvv: Optional[bool] = False
-    """If True use the Falcioni, Herzog, Moch, Ruijl, Ueda, Vermaseren, Vogt N3LO anomalous dimensions"""
+    """If True use the |FHMRUVV| |N3LO| anomalous dimensions"""
     matching_order: Optional[Order] = None
     """Matching conditions perturbative order tuple, ``(QCD, QED)``."""
 

src/ekore/anomalous_dimensions/unpolarized/space_like/__init__.py

@@ -41,7 +41,7 @@ def gamma_ns(order, mode, n, nf, n3lo_ad_variation, use_fhmruvv=False):
     n3lo_ad_variation : tuple
         |N3LO| anomalous dimension variation ``(gg, gq, qg, qq, nsp, nsm, nsv)``
     use_fhmruvv: bool
-        if True use the Falcioni Herzog Moch Vogt N3LO anomalous dimensions
+        if True use the |FHMRUVV| N3LO anomalous dimensions
 
     Returns
     -------
@@ -76,15 +76,15 @@ def gamma_ns(order, mode, n, nf, n3lo_ad_variation, use_fhmruvv=False):
     if order[0] >= 4:
         if use_fhmruvv:
             if mode == 10101:
-                gamma_ns_3 = as4.fhmruvv_approximations.gamma_nsp(
+                gamma_ns_3 = as4.fhmruvv.gamma_nsp(
                     n, nf, cache, variation=n3lo_ad_variation[4]
                 )
             elif mode == 10201:
-                gamma_ns_3 = as4.fhmruvv_approximations.gamma_nsm(
+                gamma_ns_3 = as4.fhmruvv.gamma_nsm(
                     n, nf, cache, variation=n3lo_ad_variation[5]
                 )
             elif mode == 10200:
-                gamma_ns_3 = as4.fhmruvv_approximations.gamma_nsv(
+                gamma_ns_3 = as4.fhmruvv.gamma_nsv(
                     n, nf, cache, variation=n3lo_ad_variation[6]
                 )
         else:
@@ -113,7 +113,7 @@ def gamma_singlet(order, n, nf, n3lo_ad_variation, use_fhmruvv=False):
     n3lo_ad_variation : tuple
         |N3LO| anomalous dimension variation ``(gg, gq, qg, qq, nsp, nsm, nsv)``
     use_fhmruvv: bool
-        if True use the Falcioni Herzog Moch Vogt N3LO anomalous dimensions
+        if True use the |FHMRUVV| N3LO anomalous dimensions
 
     Returns
     -------
@@ -130,9 +130,7 @@ def gamma_singlet(order, n, nf, n3lo_ad_variation, use_fhmruvv=False):
         gamma_s[2] = as3.gamma_singlet(n, nf, cache)
     if order[0] >= 4:
         if use_fhmruvv:
-            gamma_s[3] = as4.fhmruvv_approximations.gamma_singlet(
-                n, nf, cache, n3lo_ad_variation
-            )
+            gamma_s[3] = as4.fhmruvv.gamma_singlet(n, nf, cache, n3lo_ad_variation)
         else:
             gamma_s[3] = as4.gamma_singlet(n, nf, cache, n3lo_ad_variation)
     return gamma_s
@@ -293,7 +291,7 @@ def gamma_singlet_qed(order, n, nf, n3lo_ad_variation):
     nf : int
         Number of active flavors
     n3lo_ad_variation : tuple
-        |N3LO| anomalous dimension variation ``(gg_var, gq_var, qg_var, qq_var)``
+        |N3LO| anomalous dimension variation ``(gg, gq, qg, qq)``
 
     Returns
     -------

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/__init__.py

@@ -6,7 +6,7 @@
 import numba as nb
 import numpy as np
 
-from . import fhmruvv_approximations
+from . import fhmruvv
 from .ggg import gamma_gg
 from .ggq import gamma_gq
 from .gnsm import gamma_nsm
@@ -35,7 +35,7 @@ def gamma_singlet(N, nf, cache, variation):
     cache: numpy.ndarray
         Harmonic sum cache
     variation : tuple
-        |N3LO| anomalous dimension variation ``(gg_var, gq_var, qg_var, qq_var)``
+        |N3LO| anomalous dimension variation ``(gg, gq, qg, qq)``
 
     Returns
     -------

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/__init__.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/__init__.py

@@ -1,4 +1,4 @@
-"""The |N3LO| Altarelli-Parisi splitting kernels, from Falcioni, Herzog, Moch, Ruijl, Ueda, Vermaseren, Vogt approximations."""
+"""The |FHMRUVV| |N3LO| Altarelli-Parisi splitting kernels approximations."""
 import numba as nb
 import numpy as np
 
@@ -30,7 +30,7 @@ def gamma_singlet(N, nf, cache, variation):
     cache: numpy.ndarray
         Harmonic sum cache
     variation : tuple
-        |N3LO| anomalous dimension variation ``(gg_var, gq_var, qg_var, qq_var)``
+        |N3LO| anomalous dimension variation ``(gg, gq, qg, qq)``
 
     Returns
     -------

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/ggg.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/ggg.py

@@ -1,4 +1,4 @@
-r"""The unpolarized, space-like anomalous dimension :math:`\gamma_{qg}^{(3)}`."""
+r"""The unpolarized, space-like anomalous dimension :math:`\gamma_{gg}^{(3)}`."""
 import numba as nb
 
 from ......harmonics import cache as c
@@ -116,7 +116,7 @@ def gamma_gg(n, nf, cache, variation):
             + 34362.0 * lm13m1(n, S1, S2, S3)
         )
     else:
-        raise NotImplementedError("nf^6 is not available at N3LO")
+        raise NotImplementedError("nf=6 is not available at N3LO")
 
     # We return (for now) one of the two error-band representatives
     # or the present best estimate, their average

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/ggq.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/ggq.py

@@ -84,12 +84,6 @@ def gamma_gq(n, nf, cache, variation):
         )
         P3gqApp2 = (
             P3GQ01
-            # + 5.0*bfkl1* (-(1 / (-1 + n) ** 2))
-            # - 469533.* 1/((-1 + n) * n)
-            # - 26199.2 * 1/n
-            # - 294828.* (-(1/n**2))
-            # + 9089.9* lm12(n, S1, S2)
-            # + 2440.9* lm13(n, S1, S2, S3)
             + 5.4 * bfkl1 * (-(1 / (-1 + n) ** 2))
             - 547215.0 * 1 / ((-1 + n) * n)
             - 41523.0 * 1 / n
@@ -117,7 +111,7 @@ def gamma_gq(n, nf, cache, variation):
             + 2727.3 * lm13(n, S1, S2, S3)
         )
     else:
-        raise NotImplementedError("nf^6 is not available at N3LO")
+        raise NotImplementedError("nf=6 is not available at N3LO")
 
     # We return (for now) one of the two error-band representatives
     # or the present best estimate, their average

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/gnsm.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/gnsm.py

@@ -13,11 +13,11 @@ def gamma_nsm(n, nf, cache, variation):
 
     The routine is taken from :cite:`Moch:2017uml`.
 
-    The nf^{0,1} leading large-nc contributions and the nf^2 part are
+    The :math:`nf^{0,1}` leading large-nc contributions and the :math:`nf^2` part are
     high-accuracy (0.1% or better) parametrizations of the exact
-    results. The nf^3 expression is exact up to numerical truncations.
+    results. The :math:`nf^3` expression is exact up to numerical truncations.
 
-    The remaining nf^{0,1} terms are approximations based on the first
+    The remaining :math:`nf^{0,1}` terms are approximations based on the first
     eight odd moments together with small-x and large-x constraints.
     The two sets spanning the error estimate are called via  IMOD = 1
     and  IMOD = 2.  Any other value of IMOD invokes their average.

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/gnsp.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/gnsp.py

@@ -13,11 +13,11 @@ def gamma_nsp(n, nf, cache, variation):
 
     The routine is taken from :cite:`Moch:2017uml`.
 
-    The nf^{0,1} leading large-nc contributions and the nf^2 part
+    The :math:`nf^{0,1}` leading large-nc contributions and the :math:`nf^2` part
     are high-accuracy (0.1% or better) parametrizations of the exact
-    results. The nf^3 expression is exact up to numerical truncations.
+    results. The :math:`nf^3` expression is exact up to numerical truncations.
 
-    The remaining nf^{0,1} terms are approximations based on the first
+    The remaining :math:`nf^{0,1}` terms are approximations based on the first
     eight even moments together with small-x and large-x constraints.
     The two sets spanning the error estimate are called via  IMOD = 1
     and  IMOD = 2.  Any other value of IMOD invokes their average.

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/gnsv.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/gnsv.py

@@ -12,10 +12,10 @@ def gamma_nss(n, nf, cache, variation):
 
     The routine is taken from :cite:`Moch:2017uml`.
 
-    The nf^2 part is a high-accuracy (0.1% or better) parametrization
+    The :math:`nf^2` part is a high-accuracy (0.1% or better) parametrization
     of the exact expression obtained in arXiv:1610.07477, see xpns3m.f
 
-    The nf^1 part is an approximation based on the first 9 odd moments.
+    The :math:`nf^1` part is an approximation based on the first 9 odd moments.
     The two sets spanning the error estimate are called via  IMOD = 1
     and  IMOD = 2.  Any other value of IMOD invokes their average.
 

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/gps.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/gps.py

@@ -152,7 +152,7 @@ def gamma_ps(n, nf, cache, variation):
             - 10295.0 * lm12m2(n, S1, S2)
         )
     else:
-        raise NotImplementedError("nf^6 is not available at N3LO")
+        raise NotImplementedError("nf=6 is not available at N3LO")
 
     # We return (for now) one of the two error-band boundaries
     # or the present best estimate, their average

src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv_approximations/gqg.py → src/ekore/anomalous_dimensions/unpolarized/space_like/as4/fhmruvv/gqg.py

@@ -151,7 +151,7 @@ def gamma_qg(n, nf, cache, variation):
             + 385995.0 * (S1 - n * (np.pi**2 / 6 - S2)) / n**2
         )
     else:
-        raise NotImplementedError("nf^6 is not available at N3LO")
+        raise NotImplementedError("nf=6 is not available at N3LO")
 
     # We return one of the two error-band representatives
     # or the present best estimate, their average

tests/ekore/anomalous_dimensions/unpolarized/space_like/test_as4_fhmv.py

@@ -3,7 +3,7 @@
 import pytest
 
 from ekore import harmonics as h
-from ekore.anomalous_dimensions.unpolarized.space_like.as4.fhmruvv_approximations import (
+from ekore.anomalous_dimensions.unpolarized.space_like.as4.fhmruvv import (
     gamma_singlet,
     ggg,
     ggq,