ccbar asymmetry

n3fit/src/n3fit/layers/msr_normalization.py

@@ -2,9 +2,10 @@
 from n3fit.backends import operations as op
 
 GLUON_IDX = [[2]]
-V_IDX = [[3], [6], [7], [8]]
+V_IDX = [[3], [7], [8]]
 V3_IDX = [[4]]
 V8_IDX = [[5]]
+V15_IDX = [[6]]
 
 
 class MSR_Normalization(MetaLayer):
@@ -30,7 +31,7 @@ def __init__(self, output_dim=14, mode="ALL", **kwargs):
         if self._msr_enabled:
             idx += GLUON_IDX
         if self._vsr_enabled:
-            idx += V_IDX + V3_IDX + V8_IDX
+            idx += V_IDX + V3_IDX + V8_IDX + V15_IDX
 
         self._out_scatter = op.as_layer(
             op.scatter_to_one, op_kwargs={"indices": idx, "output_dim": output_dim}
@@ -41,9 +42,10 @@ def __init__(self, output_dim=14, mode="ALL", **kwargs):
     def call(self, pdf_integrated):
         """Imposes the valence and momentum sum rules:
         A_g = (1-sigma)/g
-        A_v  = A_v15 = A_v24 = A_v35 = 3/V
+        A_v = A_v24 = A_v35 = 3/V
         A_v3 = 1/V_3
         A_v8 = 3/V_8
+        A_v15 = 3/V_15
 
         Note that both the input and the output are in the 14-flavours fk-basis
         """
@@ -58,6 +60,7 @@ def call(self, pdf_integrated):
             n_av = [3.0 / y[V_IDX[0][0]]] * len(V_IDX)
             n_av3 = [1.0 / y[V3_IDX[0][0]]] * len(V3_IDX)
             n_av8 = [3.0 / y[V8_IDX[0][0]]] * len(V8_IDX)
-            norm_constants += n_av + n_av3 + n_av8
+            n_av15 = [3.0 / y[V15_IDX[0][0]]] * len(V15_IDX)
+            norm_constants += n_av + n_av3 + n_av8 + n_av15
 
         return self._out_scatter(norm_constants)

n3fit/src/n3fit/layers/rotations.py

@@ -78,7 +78,7 @@ def call(self, pdf_raw):
             x[2],  # v
             x[3],  # v3
             x[4],  # v8
-            x[2],  # v15
+            x[8],  # v15
             x[2],  # v24
             x[2],  # v35
             x[5],  # t3

n3fit/src/n3fit/layers/x_operations.py

@@ -33,7 +33,7 @@ class xDivide(MetaLayer):
 
     def __init__(self, output_dim=BASIS_SIZE, div_list=None, **kwargs):
         if div_list is None:
-            div_list = [3, 4, 5]
+            div_list = [3, 4, 5, 6]
         self.output_dim = output_dim
         self.div_list = div_list
         super().__init__(**kwargs)

n3fit/src/n3fit/msr.py

@@ -36,7 +36,7 @@ def gen_integration_input(nx):
     return xgrid, weights_array
 
 
-def msr_impose(nx=int(2e3), basis_size=8, mode='All', scaler=None):
+def msr_impose(nx=int(2e3), mode='All', scaler=None):
     """
         This function receives:
         Generates a function that applies a normalization layer to the fit.
@@ -51,8 +51,6 @@ def msr_impose(nx=int(2e3), basis_size=8, mode='All', scaler=None):
         ----------
             nx: int
                 number of points for the integration grid, default: 2000
-            basis_size: int
-                number of flavours output of the NN, default: 8
             mode: str
                 what sum rules to compute (MSR, VSR or All), default: All
             scaler: scaler
@@ -69,16 +67,14 @@ def msr_impose(nx=int(2e3), basis_size=8, mode='All', scaler=None):
     # 2. Prepare the pdf for integration
     #    for that we need to multiply several flavours with 1/x
     division_by_x = xDivide()
-
     # 3. Now create the integration layer (the layer that will simply integrate, given some weight
     integrator = xIntegrator(weights_array, input_shape=(nx,))
 
     # 4. Now create the normalization by selecting the right integrations
-    normalizer = MSR_Normalization(input_shape=(basis_size,), mode=mode)
+    normalizer = MSR_Normalization(mode=mode)
 
     # 5. Make the xgrid array into a backend input layer so it can be given to the normalization
     xgrid_input = op.numpy_to_input(xgrid, name="integration_grid")
-
     # Finally prepare a function which will take as input the output of the PDF model
     # and will return it appropiately normalized.
     def apply_normalization(layer_pdf):

n3fit/src/n3fit/tests/test_vpinterface.py

@@ -14,7 +14,7 @@ def generate_n3pdf(layers=1, members=1, name="n3fit"):
     """Generate a N3PDF model"""
     fake_fl = [
         {"fl": i, "largex": [0, 1], "smallx": [1, 2]}
-        for i in ["u", "ubar", "d", "dbar", "c", "cbar", "s", "sbar"]
+        for i in ["u", "ubar", "d", "dbar", "c", "g", "s", "sbar"]
     ]
     nodes = list(np.random.randint(1, 10, size=layers)) + [8]
     activations = ["tanh"] * layers + ["linear"]
@@ -24,6 +24,7 @@ def generate_n3pdf(layers=1, members=1, name="n3fit"):
         seed=np.random.randint(100),
         flav_info=fake_fl,
         parallel_models=members,
+        fitbasis="FLAVOUR"
     )
     return N3PDF(pdf_model, name=name)
 

validphys2/src/validphys/pdfbases.py

@@ -502,12 +502,14 @@ def f_(transform_func):
     'photon'   : {'photon':1},
     },
     aliases = {'gluon':'g', 'singlet': r'\Sigma', 'sng': r'\Sigma', 'sigma': r'\Sigma',
-               'v': 'V', 'v3': 'V3', 'v8': 'V8', 't3': 'T3', 't8': 'T8', 't15': 'T15'},
+               'v': 'V', 'v3': 'V3', 'v8': 'V8', 't3': 'T3', 't8': 'T8', 't15': 'T15', 'v15': 'V15',},
     default_elements=(r'\Sigma', 'V', 'T3', 'V3', 'T8', 'V8', 'T15', 'gluon', )
 )
 
 EVOL = evolution
 
+CCBAR_ASYMM = evolution
+
 PDF4LHC20 = LinearBasis.from_mapping({
         r'\Sigma': {
             'u': 1, 'ubar': 1, 'd': 1, 'dbar': 1, 's': 1, 'sbar': 1,
@@ -684,7 +686,15 @@ def fitbasis_to_NN31IC(flav_info, fitbasis):
 
     """
     if fitbasis == 'NN31IC':
-        return np.identity(8)
+        sng = {'sng': 1, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'cp': 0, 'g': 0 }
+        v = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'cp': 0, 'g': 0 }
+        v3 = {'sng': 0, 'v': 0, 'v3': 1, 'v8': 0, 't3': 0, 't8': 0, 'cp': 0, 'g': 0 }
+        v8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 1, 't3': 0, 't8': 0, 'cp': 0, 'g': 0 }
+        t3 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 1, 't8': 0, 'cp': 0, 'g': 0 }
+        t8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 1, 'cp': 0, 'g': 0 }
+        cp = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'cp': 1, 'g': 0 }
+        g = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'cp': 0, 'g': 1 }
+        v15 = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'cp': 0, 'g': 0 }
 
     elif fitbasis == 'NN31PC':
         sng = {'sng': 1, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'g': 0 }
@@ -695,6 +705,7 @@ def fitbasis_to_NN31IC(flav_info, fitbasis):
         t8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 1, 'g': 0 }
         cp = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'g': 0 }
         g = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 'g': 1 }
+        v15 = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0}
 
     elif fitbasis == 'FLAVOUR':
         sng = {'u': 1, 'ubar': 1, 'd': 1, 'dbar': 1, 's': 1, 'sbar': 1, 'c': 2, 'g': 0 }
@@ -705,6 +716,7 @@ def fitbasis_to_NN31IC(flav_info, fitbasis):
         t8 = {'u': 1, 'ubar': 1, 'd': 1, 'dbar': 1, 's': -2, 'sbar': -2, 'c': 0, 'g': 0 }
         cp = {'u': 0, 'ubar': 0, 'd': 0, 'dbar': 0, 's': 0, 'sbar': 0, 'c': 2, 'g': 0 }
         g = {'u': 0, 'ubar': 0, 'd': 0, 'dbar': 0, 's': 0, 'sbar': 0, 'c': 0, 'g': 1 }
+        v15 = {'u': 1, 'ubar': -1, 'd': 1, 'dbar': -1, 's': 1, 'sbar': -1, 'c': 0, 'g': 0 }
 
     elif fitbasis == 'EVOL' or fitbasis == 'evolution':
         sng = {'sng': 1, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0 }
@@ -715,6 +727,7 @@ def fitbasis_to_NN31IC(flav_info, fitbasis):
         t8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 1, 't15': 0, 'g': 0 }
         cp = {'sng': 0.25, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': -0.25, 'g': 0 }
         g = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 1 }
+        v15 = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0 }
 
     elif fitbasis == 'PDF4LHC20':
         sng = {'sng': 1, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0 }
@@ -725,17 +738,27 @@ def fitbasis_to_NN31IC(flav_info, fitbasis):
         t8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 1, 't15': 0, 'g': 0 }
         cp = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0 }
         g = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 1 }
+        v15 = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0 }
+
+    elif fitbasis == "CCBAR_ASYMM":
+        sng = {'sng': 1, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0, 'v15': 0 }
+        v = {'sng': 0, 'v': 1, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0, 'v15': 0 }
+        v3 = {'sng': 0, 'v': 0, 'v3': 1, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0, 'v15': 0 }
+        v8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 1, 't3': 0, 't8': 0, 't15': 0, 'g': 0, 'v15': 0 }
+        t3 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 1, 't8': 0, 't15': 0, 'g': 0, 'v15': 0 }
+        t8 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 1, 't15': 0, 'g': 0, 'v15': 0 }
+        cp = {'sng': 0.25, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': -0.25, 'g': 0, 'v15': 0 }
+        g = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 1, 'v15': 0 }
+        v15 = {'sng': 0, 'v': 0, 'v3': 0, 'v8': 0, 't3': 0, 't8': 0, 't15': 0, 'g': 0, 'v15': 1 }
+
+    flist = [sng, g, v, v3, v8, t3, t8, cp, v15]
 
-    flist = [sng, g, v, v3, v8, t3, t8, cp]
-
-    evol_basis = False
     mat = []
     for f in flist:
         for flav_dict in flav_info:
             flav_name = flav_dict["fl"]
             mat.append(f[flav_name])
 
     nflavs = len(flav_info)
-    mat = np.asarray(mat).reshape(8, nflavs)
     # Return the transpose of the matrix, to have the first index referring to flavour
-    return mat.transpose()
+    return np.asarray(mat).reshape(9, nflavs).T

validphys2/src/validphys/sumrules.py

@@ -96,6 +96,7 @@ def f(x, lpdf, Q):
     "uvalence": _make_pdf_integrand({"u": 1, "ubar": -1}),
     "dvalence": _make_pdf_integrand({"d": 1, "dbar": -1}),
     "svalence": _make_pdf_integrand({"s": 1, "sbar": -1}),
+    "cvalence": _make_pdf_integrand({"c": 1, "cbar": -1}),
 }
 
 UNKNOWN_SUM_RULES = {
@@ -106,6 +107,7 @@ def f(x, lpdf, Q):
     "s momentum fraction": _make_momentum_fraction_integrand({"s": 1}),
     "sbar momentum fraction": _make_momentum_fraction_integrand({"sbar": 1}),
     "cp momentum fraction": _make_momentum_fraction_integrand({"c": 1, "cbar": 1}),
+    "cm momentum fraction": _make_momentum_fraction_integrand({"c": 1, "cbar": -1}),
     "g momentum fraction": _make_momentum_fraction_integrand({"g": 1}),
     "T3": _make_pdf_integrand({"u": 1, "ubar": 1, "d": -1, "dbar": -1}),
     "T8": _make_pdf_integrand(
@@ -118,6 +120,7 @@ def f(x, lpdf, Q):
     'uvalence': 2,
     'dvalence': 1,
     'svalence': 0,
+    'cvalence': 0,
 }
 
 
@@ -141,7 +144,7 @@ def _sum_rules(rules_dict, lpdf, Q):
 
 @check_positive('Q')
 def sum_rules(pdf:PDF, Q:numbers.Real):
-    """Compute the momentum, uvalence, dvalence and svalence sum rules for
+    """Compute the momentum, uvalence, dvalence, svalence and cvalence sum rules for
     each member (as defined by libnnpdf), at the energy scale ``Q``. Return a
     SumRulesGrid object with the list of values for each sum rule.  The
     integration is performed with absolute and relative tolerance of 1e-4."""
@@ -166,6 +169,7 @@ def unknown_sum_rules(pdf: PDF, Q: numbers.Real):
        - s momentum fraction
        - sbar momentum fraction
        - cp momentum fraction
+       - cm momentum fraction
        - g momentum fraction
        - T3
        - T8

validphys2/src/validphys/tests/regressions/test_sum_rules_MC.csv

@@ -1,15 +1,17 @@
 	mean	std	min	max	Central value
-momentum	1.0000359402582584	5.358395010408105e-07	1.0000346238340416	1.0000372086565177	1.0000359458599606
-uvalence	1.9997926747574069	0.0002809483175437137	1.998765120611357	2.0001202779127008	1.9997937994497308
-dvalence	0.9997164295681845	0.00028118151759189136	0.9986902415578234	1.000046111974624	0.9997173113369415
-svalence	0.00025025303862949585	0.0003303956500365186	-0.00042417491773433236	0.0014490597353980783	0.0002507254062854847
+momentum	1.0000359402582584	5.358395010688445e-07	1.0000346238340414	1.0000372086565177	1.000035945859961
+uvalence	1.9997926747574089	0.0002809483175438455	1.9987651206113481	2.000120277912697	1.9997937994497326
+dvalence	0.9997164295682045	0.00028118151761139914	0.9986902415578238	1.0000461119746196	0.9997173113369362
+svalence	0.0002502530386336261	0.0003303956500400418	-0.0004241749177333505	0.00144905973539311	0.00025072540628739287
+cvalence	-1.3250980807101706e-05	1.1497112653961402e-05	-5.583234972306736e-05	1.9950740107887218e-05	-1.3025352765570286e-05
 u momentum fraction	0.2555	0.0021	-1.0	-1.0	-1.0
 ubar momentum fraction	0.03387	0.00074	-1.0	-1.0	-1.0
 d momentum fraction	0.1278	0.0021	-1.0	-1.0	-1.0
 dbar momentum fraction	0.0422	0.0012	-1.0	-1.0	-1.0
 s momentum fraction	0.0316	0.002	-1.0	-1.0	-1.0
 sbar momentum fraction	0.0253	0.0012	-1.0	-1.0	-1.0
 cp momentum fraction	0.0286	0.0017	-1.0	-1.0	-1.0
+cm momentum fraction	-7.024e-05	8.7e-07	-1.0	-1.0	-1.0
 g momentum fraction	0.4466	0.0017	-1.0	-1.0	-1.0
 T3	0.79	0.23	-1.0	-1.0	-1.0
 T8	4.73	0.7	-1.0	-1.0	-1.0

validphys2/src/validphys/tests/regressions/test_sum_rules_hessian.csv

@@ -1,15 +1,17 @@
 	mean	std	min	max	Central value
-momentum	1.0000359346945835	3.249002390618474e-08	1.0000357949386856	1.000036007099919	1.000035943610909
-uvalence	1.9997947975241677	3.774745222364767e-05	1.9996255039155293	1.9998795897064394	1.9998052948252174
-dvalence	0.9997193904389039	3.913237872100671e-05	0.9995455646219639	0.9998033688013618	0.9997281952294002
-svalence	0.00021668009787772745	4.881864767300481e-05	2.8212616664191614e-05	0.00037062725233145966	0.00021200815810076823
+momentum	1.0000359346945835	3.249002389936152e-08	1.000035794938686	1.0000360070999192	1.000035943610909
+uvalence	1.999794797524114	3.7747452172582034e-05	1.9996255039155355	1.9998795897064396	1.9998052948252143
+dvalence	0.9997193904388911	3.913237869423472e-05	0.9995455646219693	0.9998033688013626	0.9997281952294024
+svalence	0.00021668009787584756	4.8818647675234034e-05	2.8212616642056543e-05	0.00037062725233308336	0.00021200815810049067
+cvalence	-1.4051604747740869e-05	1.6214339259070918e-06	-2.1935653748207965e-05	-1.107482404248553e-05	-1.3850510260915482e-05
 u momentum fraction	0.2554	0.00025	-1.0	-1.0	-1.0
 ubar momentum fraction	0.03386	0.0001	-1.0	-1.0	-1.0
 d momentum fraction	0.1277	0.00029	-1.0	-1.0	-1.0
 dbar momentum fraction	0.04224	0.00016	-1.0	-1.0	-1.0
 s momentum fraction	0.03172	0.00027	-1.0	-1.0	-1.0
 sbar momentum fraction	0.0253	0.00016	-1.0	-1.0	-1.0
 cp momentum fraction	0.02882	0.00023	-1.0	-1.0	-1.0
+cm momentum fraction	-7.022e-05	1.1e-07	-1.0	-1.0	-1.0
 g momentum fraction	0.44649	0.00025	-1.0	-1.0	-1.0
 T3	0.807	0.033	-1.0	-1.0	-1.0
 T8	4.65	0.1	-1.0	-1.0	-1.0