diff --git a/cmsdb/campaigns/run3_2022_postEE_nano_v12/ewk.py b/cmsdb/campaigns/run3_2022_postEE_nano_v12/ewk.py
index 1e89f945..72a6e97e 100644
--- a/cmsdb/campaigns/run3_2022_postEE_nano_v12/ewk.py
+++ b/cmsdb/campaigns/run3_2022_postEE_nano_v12/ewk.py
@@ -634,6 +634,121 @@
 )
 
 
+#
+# DY + photon (Zγ)
+#
+
+cpn.add_dataset(
+    name="dyg_m50toinf_amcatnlo",
+    id=15618548,
+    processes=[procs.dyg_m50toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=291,
+    n_events=60_907_978,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg10to100_amcatnlo",
+    id=14887232,
+    processes=[procs.dyg_m50toinf_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=872,
+    n_events=171_496_738,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg100to200_amcatnlo",
+    id=14793597,
+    processes=[procs.dyg_m50toinf_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=27,
+    n_events=696_610,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg200to400_amcatnlo",
+    id=14886082,
+    processes=[procs.dyg_m50toinf_ptg200to400],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-200to400_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=29,
+    n_events=1_785_572,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg400to600_amcatnlo",
+    id=14887668,
+    processes=[procs.dyg_m50toinf_ptg400to600],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-400to600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=33,
+    n_events=1_776_157,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg600toinf_amcatnlo",
+    id=14886958,
+    processes=[procs.dyg_m50toinf_ptg600toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=62,
+    n_events=1_797_374,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_amcatnlo",
+    id=15671988,
+    processes=[procs.dyg_m4to50],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=394,
+    n_events=61_688_959,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg10to100_amcatnlo",
+    id=14809616,
+    processes=[procs.dyg_m4to50_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=576,
+    n_events=85_739_885,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg100to200_amcatnlo",
+    id=14809461,
+    processes=[procs.dyg_m4to50_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=75,
+    n_events=1_448_629,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg200toinf_amcatnlo",
+    id=14811651,
+    processes=[procs.dyg_m4to50_ptg200toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22EENanoAODv12-130X_mcRun3_2022_realistic_postEE_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=30,
+    n_events=746_202,
+)
+
+
 #
 # Triboson
 #
diff --git a/cmsdb/campaigns/run3_2022_preEE_nano_v12/ewk.py b/cmsdb/campaigns/run3_2022_preEE_nano_v12/ewk.py
index 89fd4974..8ffcc483 100644
--- a/cmsdb/campaigns/run3_2022_preEE_nano_v12/ewk.py
+++ b/cmsdb/campaigns/run3_2022_preEE_nano_v12/ewk.py
@@ -395,6 +395,120 @@
     n_events=1181750,
 )
 
+#
+# DY + photon (Zγ)
+#
+
+cpn.add_dataset(
+    name="dyg_m50toinf_amcatnlo",
+    id=15618184,
+    processes=[procs.dyg_m50toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=167,
+    n_events=24_686_639,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg10to100_amcatnlo",
+    id=14887589,
+    processes=[procs.dyg_m50toinf_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=341,
+    n_events=49_496_896,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg100to200_amcatnlo",
+    id=14794999,
+    processes=[procs.dyg_m50toinf_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=17,
+    n_events=201_017,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg200to400_amcatnlo",
+    id=14887957,
+    processes=[procs.dyg_m50toinf_ptg200to400],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-200to400_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=23,
+    n_events=509_420,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg400to600_amcatnlo",
+    id=14887209,
+    processes=[procs.dyg_m50toinf_ptg400to600],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-400to600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=28,
+    n_events=490_675,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg600toinf_amcatnlo",
+    id=14886090,
+    processes=[procs.dyg_m50toinf_ptg600toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=21,
+    n_events=488_259,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_amcatnlo",
+    id=15671122,
+    processes=[procs.dyg_m4to50],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=211,
+    n_events=24_921_673,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg10to100_amcatnlo",
+    id=14811443,
+    processes=[procs.dyg_m4to50_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=135,
+    n_events=24_279_030,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg100to200_amcatnlo",
+    id=14811593,
+    processes=[procs.dyg_m4to50_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=21,
+    n_events=391_451,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg200toinf_amcatnlo",
+    id=14811610,
+    processes=[procs.dyg_m4to50_ptg200toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer22NanoAODv12-130X_mcRun3_2022_realistic_v5-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=18,
+    n_events=185_067,
+)
+
 #
 # Triboson
 #
diff --git a/cmsdb/campaigns/run3_2023_postBPix_nano_v12/ewk.py b/cmsdb/campaigns/run3_2023_postBPix_nano_v12/ewk.py
index b728a666..70294588 100644
--- a/cmsdb/campaigns/run3_2023_postBPix_nano_v12/ewk.py
+++ b/cmsdb/campaigns/run3_2023_postBPix_nano_v12/ewk.py
@@ -560,6 +560,120 @@
     ),
 )
 
+#
+# DY + photon (Zγ)
+#
+
+cpn.add_dataset(
+    name="dyg_m50toinf_amcatnlo",
+    id=15617668,
+    processes=[procs.dyg_m50toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=180,
+    n_events=26_668_199,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg10to100_amcatnlo",
+    id=14930640,
+    processes=[procs.dyg_m50toinf_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=119,
+    n_events=48_023_180,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg100to200_amcatnlo",
+    id=14958503,
+    processes=[procs.dyg_m50toinf_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v3/NANOAODSIM",  # noqa
+    ],
+    n_files=14,
+    n_events=929_434,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg200to400_amcatnlo",
+    id=14930629,
+    processes=[procs.dyg_m50toinf_ptg200to400],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-200to400_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=11,
+    n_events=502_620,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg400to600_amcatnlo",
+    id=14930551,
+    processes=[procs.dyg_m50toinf_ptg400to600],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-400to600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=9,
+    n_events=501_187,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg600toinf_amcatnlo",
+    id=14930882,
+    processes=[procs.dyg_m50toinf_ptg600toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=28,
+    n_events=461_697,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_amcatnlo",
+    id=15671905,
+    processes=[procs.dyg_m4to50],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=199,
+    n_events=25_602_889,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg10to100_amcatnlo",
+    id=15279848,
+    processes=[procs.dyg_m4to50_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=288,
+    n_events=97_324_198,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg100to200_amcatnlo",
+    id=15247647,
+    processes=[procs.dyg_m4to50_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=97,
+    n_events=11_439_928,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg200toinf_amcatnlo",
+    id=15251130,
+    processes=[procs.dyg_m4to50_ptg200toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23BPixNanoAODv12-130X_mcRun3_2023_realistic_postBPix_v6-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=50,
+    n_events=4_052_517,
+)
+
 #
 # Triboson
 #
diff --git a/cmsdb/campaigns/run3_2023_preBPix_nano_v12/ewk.py b/cmsdb/campaigns/run3_2023_preBPix_nano_v12/ewk.py
index 296ebe8e..4632b903 100644
--- a/cmsdb/campaigns/run3_2023_preBPix_nano_v12/ewk.py
+++ b/cmsdb/campaigns/run3_2023_preBPix_nano_v12/ewk.py
@@ -874,6 +874,122 @@
     ),
 )
 
+####################################################################################################
+#
+# DY + photon (Zγ)
+#
+####################################################################################################
+
+cpn.add_dataset(
+    name="dyg_m50toinf_amcatnlo",
+    id=15618387,
+    processes=[procs.dyg_m50toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=287,
+    n_events=49_351_934,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg10to100_amcatnlo",
+    id=15047524,
+    processes=[procs.dyg_m50toinf_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v4/NANOAODSIM",  # noqa
+    ],
+    n_files=237,
+    n_events=97_352_254,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg100to200_amcatnlo",
+    id=14931202,
+    processes=[procs.dyg_m50toinf_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v3/NANOAODSIM",  # noqa
+    ],
+    n_files=33,
+    n_events=1_889_390,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg200to400_amcatnlo",
+    id=14930013,
+    processes=[procs.dyg_m50toinf_ptg200to400],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-200to400_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v4/NANOAODSIM",  # noqa
+    ],
+    n_files=5,
+    n_events=981_022,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg400to600_amcatnlo",
+    id=14930683,
+    processes=[procs.dyg_m50toinf_ptg400to600],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-400to600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v4/NANOAODSIM",  # noqa
+    ],
+    n_files=21,
+    n_events=969_648,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg600toinf_amcatnlo",
+    id=14931380,
+    processes=[procs.dyg_m50toinf_ptg600toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-50_PTG-600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v4/NANOAODSIM",  # noqa
+    ],
+    n_files=26,
+    n_events=940_148,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_amcatnlo",
+    id=15671863,
+    processes=[procs.dyg_m4to50],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=353,
+    n_events=50_249_469,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg10to100_amcatnlo",
+    id=15281760,
+    processes=[procs.dyg_m4to50_ptg10to100],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-10to100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=159,
+    n_events=50_266_088,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg100to200_amcatnlo",
+    id=15246913,
+    processes=[procs.dyg_m4to50_ptg100to200],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-100to200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=44,
+    n_events=5_683_089,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_ptg200toinf_amcatnlo",
+    id=15251596,
+    processes=[procs.dyg_m4to50_ptg200toinf],
+    keys=[
+        "/DYGto2LG-1Jets_MLL-4to50_PTG-200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/Run3Summer23NanoAODv12-130X_mcRun3_2023_realistic_v15-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=31,
+    n_events=2_045_586,
+)
+
 ####################################################################################################
 #
 # Triboson
diff --git a/cmsdb/campaigns/run3_2024_nano_v15/ewk.py b/cmsdb/campaigns/run3_2024_nano_v15/ewk.py
index a62ed36f..16664d29 100644
--- a/cmsdb/campaigns/run3_2024_nano_v15/ewk.py
+++ b/cmsdb/campaigns/run3_2024_nano_v15/ewk.py
@@ -805,7 +805,7 @@
     n_events=4_800_000,
 )
 
-# further ww decay modes
+# qqWW decay modes (Powheg NLO)
 cpn.add_dataset(
     name="ww_dl_powheg",
     id=15304453,
@@ -839,7 +839,7 @@
     n_events=151_214_029,
 )
 
-# further ww decay modes with specific leptons
+# ggWW dilepton decay modes (MCFM LO)
 cpn.add_dataset(
     name="ww_wenu_wenu_pythia",
     id=15349213,
@@ -909,6 +909,18 @@
     n_events=1_999_273,
 )
 
+# same-sign WW
+cpn.add_dataset(
+    name="ww_ss_2j_madgraph",
+    id=15515111,
+    processes=[procs.ww_ss_2j],
+    keys=[
+        "/WpWpJJ-EWK-QCD_TuneCP5_13p6TeV_madgraph-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=17,
+    n_events=243_119,
+)
+
 # further wz decay modes
 cpn.add_dataset(
     name="wz_wlnu_zll_powheg",
@@ -1092,6 +1104,91 @@
     n_events=2_800_000,
 )
 
+#
+# V + gamma
+#
+
+cpn.add_dataset(
+    name="wg_wlnu_amcatnlo",
+    id=15467536,
+    processes=[procs.wg_wlnu],
+    keys=[
+        "/WGtoLNuG-1Jets_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=2_424,
+    n_events=445_891_677,
+)
+
+#
+# DY + photon (Zγ) — 2024 uses Bin- convention with open PTG thresholds
+#
+
+cpn.add_dataset(
+    name="dyg_m50toinf_amcatnlo",
+    id=15462713,
+    processes=[procs.dyg_m50toinf],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=1_527,
+    n_events=263_214_524,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg100toinf_amcatnlo",
+    id=15463184,
+    processes=[procs.dyg_m50toinf_ptg100toinf],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-50-PTG-100_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=301,
+    n_events=27_365_714,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg200toinf_amcatnlo",
+    id=15463372,
+    processes=[procs.dyg_m50toinf_ptg200toinf],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-50-PTG-200_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=207,
+    n_events=21_252_950,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg400toinf_amcatnlo",
+    id=15463178,
+    processes=[procs.dyg_m50toinf_ptg400toinf],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-50-PTG-400_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=236,
+    n_events=17_944_020,
+)
+
+cpn.add_dataset(
+    name="dyg_m50toinf_ptg600toinf_amcatnlo",
+    id=15463007,
+    processes=[procs.dyg_m50toinf_ptg600toinf],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-50-PTG-600_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=253,
+    n_events=20_717_390,
+)
+
+cpn.add_dataset(
+    name="dyg_m4to50_amcatnlo",
+    id=15463162,
+    processes=[procs.dyg_m4to50],
+    keys=[
+        "/DYGto2LG-1Jets_Bin-MLL-4to50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=1_437,
+    n_events=250_363_098,
+)
+
 #
 # Triple-boson
 #
diff --git a/cmsdb/campaigns/run3_2024_nano_v15/higgs.py b/cmsdb/campaigns/run3_2024_nano_v15/higgs.py
index c91b6ab7..2b13697b 100644
--- a/cmsdb/campaigns/run3_2024_nano_v15/higgs.py
+++ b/cmsdb/campaigns/run3_2024_nano_v15/higgs.py
@@ -260,7 +260,27 @@
 # tH
 #
 
-# tba
+cpn.add_dataset(
+    name="thq_4f_madgraph",
+    id=15537100,
+    processes=[procs.thq],
+    keys=[
+        "/THQ-4FS-ctcvcp_Par-M-125_TuneCP5_13p6TeV_madgraph-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=352,
+    n_events=19_985_991,
+)
+
+cpn.add_dataset(
+    name="thw_madgraph",
+    id=15539363,
+    processes=[procs.thw],
+    keys=[
+        "/THW-5FS-ctcvcp_Par-M-125_TuneCP5_13p6TeV_madgraph-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=267,
+    n_events=14_995_985,
+)
 
 #
 # ttVH
diff --git a/cmsdb/campaigns/run3_2024_nano_v15/top.py b/cmsdb/campaigns/run3_2024_nano_v15/top.py
index 8792a8a6..609ebe54 100644
--- a/cmsdb/campaigns/run3_2024_nano_v15/top.py
+++ b/cmsdb/campaigns/run3_2024_nano_v15/top.py
@@ -620,8 +620,50 @@
 # 4 top
 #
 
-# missing
-# cpn.add_dataset(
-#     name="tttt_amcatnlo",
-#     ...
-# )
+cpn.add_dataset(
+    name="tttt_amcatnlo",
+    id=15529183,
+    processes=[procs.tttt],
+    keys=[
+        "/TTTT_TuneCP5_13p6TeV_amcatnlo-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=101,
+    n_events=9_776_800,
+)
+
+#
+# top + photon
+#
+
+cpn.add_dataset(
+    name="ttg_amcatnlo",
+    id=15536929,
+    processes=[procs.ttg],
+    keys=[
+        "/TTG-1Jets_TuneCP5_13p6TeV_amcatnloFXFXold-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=143,
+    n_events=19_416_271,
+)
+
+cpn.add_dataset(
+    name="ttg_pt100to200_amcatnlo",
+    id=15536699,
+    processes=[procs.ttg_pt100to200],
+    keys=[
+        "/TTG-1Jets_Bin-PTG-100_TuneCP5_13p6TeV_amcatnloFXFXold-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v2/NANOAODSIM",  # noqa
+    ],
+    n_files=113,
+    n_events=10_495_130,
+)
+
+cpn.add_dataset(
+    name="ttg_pt200toinf_amcatnlo",
+    id=15536925,
+    processes=[procs.ttg_pt200toinf],
+    keys=[
+        "/TTG-1Jets_Bin-PTG-200_TuneCP5_13p6TeV_amcatnloFXFXold-pythia8/RunIII2024Summer24NanoAODv15-150X_mcRun3_2024_realistic_v2-v3/NANOAODSIM",  # noqa
+    ],
+    n_files=107,
+    n_events=9_630_092,
+)
diff --git a/cmsdb/processes/ewk.py b/cmsdb/processes/ewk.py
index 7b25450f..836cc6bc 100644
--- a/cmsdb/processes/ewk.py
+++ b/cmsdb/processes/ewk.py
@@ -88,14 +88,21 @@
     "ewk",
     "ewk_wp_lnu_m50toinf", "ewk_wm_lnu_m50toinf", "ewk_z_ll_m50toinf",
     "vv",
-    "zz",
+    "zz", "qqzz", "ggzz",
     "zz_zqq_zll", "zz_zll_znunu", "zz_zll_zll", "zz_zqq_zqq", "zz_znunu_zqq",
     "zz_zee_zee", "zz_zee_zmm", "zz_zee_ztt", "zz_zmm_zmm", "zz_zmm_ztt", "zz_ztt_ztt",
     "wz", "wz_wlnu_zll", "wz_wqq_zll", "wz_wqq_zqq", "wz_wlnu_zqq",
     "wzg", "wzg_wlnu",
-    "ww",
+    "wg_wlnu",
+    "dyg",
+    "dyg_m50toinf", "dyg_m50toinf_ptg10to100", "dyg_m50toinf_ptg100to200",
+    "dyg_m50toinf_ptg200to400", "dyg_m50toinf_ptg400to600", "dyg_m50toinf_ptg600toinf",
+    "dyg_m50toinf_ptg100toinf", "dyg_m50toinf_ptg200toinf", "dyg_m50toinf_ptg400toinf",
+    "dyg_m4to50", "dyg_m4to50_ptg10to100", "dyg_m4to50_ptg100to200", "dyg_m4to50_ptg200toinf",
+    "ww", "qqww", "ggww",
     "ww_dl", "ww_sl", "ww_fh",
     "ww_wenu_wenu", "ww_wenu_wmnu", "ww_wenu_wtnu", "ww_wmnu_wmnu", "ww_wmnu_wtnu", "ww_wtnu_wtnu",
+    "ww_ss_2j",
     "vvv",
     "zzz", "wzz", "wwz", "www",
 ]
@@ -106,7 +113,6 @@
 
 import cmsdb.constants as const
 from cmsdb.processes.stitching import get_stitched_dy_m50toinf_br, get_stitched_w_lnu_br
-from cmsdb.util import multiply_xsecs
 
 
 #
@@ -2214,87 +2220,217 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     label="Di-Boson",
 )
 
-# ZZ 13 TeV xsec values at nNNLO from
+# ZZ
+# Theory inclusive XS (qqZZ + ggZZ):
+#   13 TeV:   NNLO+NNLL = 16.518 ± 1.84% pb from https://journals.aps.org/prd/abstract/10.1103/2rr7-5xv3, table 1
+#   13.6 TeV: NNLO+NNLL = 17.627 ± 1.93% pb from the same paper, table 1
+# For the inclusive Pythia sample (ZZ_TuneCP5_13p6TeV_pythia8), XSDB lists 12.75 pb.
+# A second XSDB entry explicitly marks the order as LO (typical for Pythia-only samples).
+# Applying k=1.51 (LO→NNLO) gives 12.75 × 1.51 = 19.2525 pb.
+#
+# NOTE on k-factor: k=1.15 is used for NLO→NNLO (powheg/amcatnlo samples);
+# k=1.51 is used for LO→NNLO (Pythia-only/inclusive samples).
+# See Torben's slides: https://indico.cern.ch/event/1677270/contributions/7200886/attachments/3317393/5938464/ZZXS.pdf
+#
+# NOTE on per-decay-mode normalization: each dataset is normalized by its own
+# XSDB cross section (per decay mode) × k-factor. The per-decay-mode NLO values
+# from XSDB do NOT sum to the inclusive (they exceed it due to overlap / different
+# phase space cuts / EWK contributions at NLO enhancing leptonic modes).
+# If combining multiple ZZ decay-mode samples, stitching would be required.
+
+# k-factors for ZZ
+# See Torben's slides: https://indico.cern.ch/event/1677270/contributions/7200886/attachments/3317393/5938464/ZZXS.pdf
+zz_k_nlo_to_nnlo = 1.15   # NLO→NNLO (powheg/amcatnlo samples)
+zz_k_lo_to_nnlo = 1.51    # LO→NNLO (Pythia-only/inclusive samples)
+# ggZZ: k=1.7 (LO MCFM → NLO) from the same slides
+zz_gg_k_lo_to_nlo = 1.7
+
 zz = vv.add_process(
     name="zz",
     id=8100,
     label="ZZ",
     xsecs={
-        # https://link.springer.com/article/10.1007/JHEP03(2019)070#preview, table 3, nNNLO
-        13: Number(24.97, {"scale": (0.029j, 0.027j)}),
-        # no theory prediction found yet, so take accurate value at 13 TeV and scale by the ratio
-        # of XSDB values at https://xsdb-temp.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=40&searchQuery=process_name%3D%5EZZ_TuneCP5_13.%2Bpythia8%24  # noqa
-        13.6: Number(24.97, {"scale": (0.029j, 0.027j)}) * (12.75 / 12.14),
+        # NNLO+NNLL from https://journals.aps.org/prd/abstract/10.1103/2rr7-5xv3, table 1
+        13: Number(16.518, {"scale": 0.0184j}),
+        13.6: Number(17.627, {"scale": 0.0193j}),
+    },
+)
+
+# qqZZ: each decay mode normalized independently by its NLO XSDB value × k=1.15
+# NLO XS values from XSDB for individual powheg/amcatnlo samples
+qqzz = zz.add_process(
+    name="qqzz",
+    id=8170,
+    label=r"$q\bar{q} \rightarrow ZZ$",
+    xsecs={
+        # XSDB inclusive (LO, Pythia-only) × k(LO→NNLO)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=10&searchQuery=DAS%3DZZ_TuneCP5_13TeV-pythia8
+        13: Number(12.14) * zz_k_lo_to_nnlo,
+        # XSDB inclusive (LO, Pythia-only) × k(LO→NNLO)
+        13.6: Number(12.75) * zz_k_lo_to_nnlo,
+    },
+)
+
+zz_zll_zll = zz.add_process(
+    name="zz_zll_zll",
+    id=8130,
+    xsecs={
+        # 13 TeV: XSDB NLO 1.256 pb (ZZTo4L powheg) × k(NLO→NNLO)
+        # NOTE: ZZTo4L amcatnlo is not on XSDB; CMS AN-19-191 gives 1.5 pb × k=1.15 = 1.725 pb (NNLO+NNLL)
+        13: Number(1.256) * zz_k_nlo_to_nnlo,
+        # 13.6 TeV: XSDB NLO 1.39 pb (ZZto4L powheg) × k(NLO→NNLO)
+        13.6: Number(1.39) * zz_k_nlo_to_nnlo,
     },
 )
 
 zz_zqq_zll = zz.add_process(
     name="zz_zqq_zll",
     id=8110,
-    xsecs=multiply_xsecs(zz, const.br_zz.llqq),
+    xsecs={
+        # 13 TeV: NLO from GenXSecAnalyzer on UL18 MiniAODv2 (1M events) × k=1.15 (NLO→NNLO)
+        # Sample: ZZTo2Q2L_mllmin4p0_TuneCP5_13TeV-amcatnloFXFX-pythia8 (amcatnloFXFX → NLO)
+        # Torben confirmed: XSDB "LO" label is misleading; generator is NLO (amcatnloFXFX)
+        # GenXSecAnalyzer After filter: 3.698 ± 0.004 pb × k=1.15 = 4.253 pb
+        # (consistent with XSDB value 3.676 pb for same sample)
+        # NOTE: 13 TeV sample has mllmin4p0 cut; 13.6 TeV uses powheg without this cut — different phase space
+        13: Number(3.698, {"tot": 0.004}) * zz_k_nlo_to_nnlo,
+        # 13.6 TeV: XSDB NLO 6.788 pb (ZZto2L2Q powheg) × k(NLO→NNLO)
+        13.6: Number(6.788) * zz_k_nlo_to_nnlo,
+    },
 )
 
 zz_zll_znunu = zz.add_process(
     name="zz_zll_znunu",
     id=8120,
-    xsecs=multiply_xsecs(zz, const.br_zz.llnunu),
+    xsecs={
+        # 13 TeV: NLO from GenXSecAnalyzer on UL18 MiniAODv2 (1M events) × k=1.15 (NLO→NNLO)
+        # Sample: ZZTo2L2Nu_TuneCP5_13TeV_powheg_pythia8/RunIISummer20UL18MiniAODv2 (Powheg NLO, ~0% neg. weights)
+        # Gridpack: ZZ_slc7_amd64_gcc820_CMSSW_11_0_1_ZZ2L2Nu.tgz (UL v2, mll > 4 GeV)
+        # GenXSecAnalyzer After filter: 0.9738 ± 0.001 pb × k=1.15 = 1.1199 pb
+        # (sanity: 1.120 pb at 13 TeV < 1.186 pb at 13.6 TeV → ~5.5% energy scaling ✓)
+        # NOTE (Torben): the Autumn18 sample (RunIIAutumn18MiniAOD, gridpack v1 with mll > 40 GeV) gives 0.6008 pb —
+        # a different phase space; treat as ZZTo2L2Nu_mll40 if needed.
+        # The UL value (0.9738 pb, mll > 4 GeV) is used here.
+        13: Number(0.9738, {"tot": 0.001}) * zz_k_nlo_to_nnlo,
+        # 13.6 TeV: XSDB NLO 1.031 pb (ZZto2L2Nu powheg) × k(NLO→NNLO)
+        13.6: Number(1.031) * zz_k_nlo_to_nnlo,
+    },
 )
 
-zz_zll_zll = zz.add_process(
-    name="zz_zll_zll",
-    id=8130,
-    xsecs=multiply_xsecs(zz, const.br_zz.llll),
+zz_znunu_zqq = zz.add_process(
+    name="zz_znunu_zqq",
+    id=8150,
+    xsecs={
+        # 13 TeV: NLO from GenXSecAnalyzer on UL18 MiniAODv2 (1M events) × k=1.15 (NLO→NNLO)
+        # Sample: ZZTo2Q2Nu_TuneCP5_13TeV-amcatnloFXFX-pythia8 (ZZTo2Q2Nu01j_5f_NLO_FXFX gridpack → amcatnloFXFX)
+        # Torben confirmed: XSDB "LO" label is misleading; generator is NLO (amcatnloFXFX)
+        # GenXSecAnalyzer After filter: 4.487 ± 0.008 pb × k=1.15 = 5.160 pb
+        # (sanity check: 5.160 pb at 13 TeV < 5.5499 pb at 13.6 TeV — physically consistent)
+        13: Number(4.487, {"tot": 0.008}) * zz_k_nlo_to_nnlo,
+        # 13.6 TeV: XSDB NLO 4.826 pb (ZZto2Nu2Q powheg) × k(NLO→NNLO)
+        13.6: Number(4.826) * zz_k_nlo_to_nnlo,
+    },
 )
 
 zz_zqq_zqq = zz.add_process(
     name="zz_zqq_zqq",
     id=8140,
-    xsecs=multiply_xsecs(zz, const.br_zz.qqqq),
+    xsecs={
+        # 13 TeV: NLO from XSDB × k=1.15 (NLO→NNLO)
+        # Sample: ZZTo4Q_13TeV_amcatnloFXFX_madspin_pythia8
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=40&searchQuery=process_name%3D%5EZZTo4Q_13TeV_amcatnloFXFX_madspin_pythia8
+        # XSDB NLO: 6.912 pb × k(NLO→NNLO)
+        # NOTE: GenXSecAnalyzer on ZZTo4Q_5f (no madspin) gives only 3.305 pb — different generator setup,
+        # likely a mass cut difference (Torben). The madspin sample is consistent with the 13.6 TeV setup.
+        # (sanity: 6.912×k at 13 TeV < 7.832×k at 13.6 TeV → ~12% energy scaling ✓)
+        13: Number(6.912) * zz_k_nlo_to_nnlo,
+        # 13.6 TeV: XSDB NLO 7.832 pb (ZZto4Q amcatnlo) × k(NLO→NNLO)
+        13.6: Number(7.832) * zz_k_nlo_to_nnlo,
+    },
 )
 
-zz_znunu_zqq = zz.add_process(
-    name="zz_znunu_zqq",
-    id=8150,
-    xsecs=multiply_xsecs(zz, const.br_zz.qqnunu),
+# ggZZ: each decay mode normalized independently by its LO MCFM value × k=1.7
+# LO XS values in fb from XSDB for individual mcfm samples
+# See slides: https://indico.cern.ch/event/1677270/contributions/7200886/attachments/3317393/5938464/ZZXS.pdf
+#
+# Same-flavor modes (4e, 4μ, 4τ) have the same XSDB LO value;
+# different-flavor modes (2e2μ, 2e2τ, 2μ2τ) also share a common value.
+# Store these as variables to avoid repetition and make the origin clear.
+
+# XSDB LO values (in fb) for same-flavor ggZZ modes (GluGlu2Zto4L mcfm)
+gg_zz_lo_same_13 = Number(2.703e-03)    # GluGlu2Zto4E / 4Mu / 4Tau, 13 TeV
+gg_zz_lo_same_13p6 = Number(5.199467e-03)  # GluGlu2Zto4E / 4Mu / 4Tau, 13.6 TeV
+
+# XSDB LO values (in fb) for different-flavor ggZZ modes (GluGlu2Zto2L2L' mcfm)
+gg_zz_lo_diff_13 = Number(5.423e-03)       # GluGlu2Zto2E2Mu / 2E2Tau / 2Mu2Tau, 13 TeV
+gg_zz_lo_diff_13p6 = Number(10.610669e-03)  # GluGlu2Zto2E2Mu / 2E2Tau / 2Mu2Tau, 13.6 TeV
+
+ggzz = zz.add_process(
+    name="ggzz",
+    id=8180,
+    label=r"$gg \rightarrow ZZ$",
+    xsecs={
+        # sum of ggZZ decay modes: 3 same-flavor + 3 different-flavor
+        13: (gg_zz_lo_same_13 + gg_zz_lo_diff_13) * const.n_leps,
+        13.6: (gg_zz_lo_same_13p6 + gg_zz_lo_diff_13p6) * const.n_leps,
+    },
 )
 
 zz_zee_zee = zz.add_process(
     name="zz_zee_zee",
     id=8160,
-    xsecs=multiply_xsecs(zz, const.br_zz.eeee),
+    xsecs={
+        13: gg_zz_lo_same_13,
+        13.6: gg_zz_lo_same_13p6,
+    },
 )
 
 zz_zee_zmm = zz.add_process(
     name="zz_zee_zmm",
     id=8161,
-    xsecs=multiply_xsecs(zz, const.br_zz.eemm),
+    xsecs={
+        13: gg_zz_lo_diff_13,
+        13.6: gg_zz_lo_diff_13p6,
+    },
 )
 
 zz_zee_ztt = zz.add_process(
     name="zz_zee_ztt",
     id=8162,
-    xsecs=multiply_xsecs(zz, const.br_zz.eett),
+    xsecs={
+        13: gg_zz_lo_diff_13,
+        13.6: gg_zz_lo_diff_13p6,
+    },
 )
 
 zz_zmm_zmm = zz.add_process(
     name="zz_zmm_zmm",
     id=8163,
-    xsecs=multiply_xsecs(zz, const.br_zz.mmmm),
+    xsecs={
+        13: gg_zz_lo_same_13,
+        13.6: gg_zz_lo_same_13p6,
+    },
 )
 
 zz_zmm_ztt = zz.add_process(
     name="zz_zmm_ztt",
     id=8164,
-    xsecs=multiply_xsecs(zz, const.br_zz.mmtt),
+    xsecs={
+        13: gg_zz_lo_diff_13,
+        13.6: gg_zz_lo_diff_13p6,
+    },
 )
 
 zz_ztt_ztt = zz.add_process(
     name="zz_ztt_ztt",
     id=8165,
-    xsecs=multiply_xsecs(zz, const.br_zz.tttt),
+    xsecs={
+        13: gg_zz_lo_same_13,
+        13.6: gg_zz_lo_same_13p6,
+    },
 )
 
-# WZ xsec values at NLO from https://arxiv.org/pdf/1105.0020.pdf v1
+# WZ inclusive NLO xsec values from https://arxiv.org/pdf/1105.0020.pdf v1
 wp_z_xsec = {
     13: Number(28.55, {"scale": (0.041j, 0.032j)}),
 }
@@ -2321,34 +2457,70 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     },
 )
 
+# WZto3LNu cross sections for the powheg decay-mode sample (W->lnu, Z->ll).
+# Each decay mode is normalized independently by its XSDB NLO value × k-factor (NNLO QCD x NLO EW).
+# k-factor is between NNLO QCD x NLO EW (MATRIX) and NLO POWHEG (not NLO MATRIX).
+# MATRIX paper: https://arxiv.org/abs/1912.00068
+
+# k-factors for WZ decay modes (NLO POWHEG -> NNLO QCD x NLO EW)
+wz_k_run2 = 1.19  # from WZ Run2 paper: https://arxiv.org/pdf/2110.11231
+wz_k_run3 = 1.08  # from WZ Run3 paper: https://arxiv.org/pdf/2412.02477
 wz_wlnu_zll = wz.add_process(
     name="wz_wlnu_zll",
     id=8210,
-    xsecs=multiply_xsecs(wz, const.br_w.lep * const.br_z.clep),
+    xsecs={
+        # XSDB NLO (powheg) 4.42965 pb × k(NLO POWHEG -> NNLO QCD x NLO EW)
+        # https://twiki.cern.ch/twiki/bin/view/CMS/SummaryTable1G25ns#Diboson (NLO: 4.42965 pb)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=10&searchQuery=DAS=WZto3LNu_TuneCUETP8M1_13TeV-powheg-pythia8  # noqa
+        13: Number(4.42965) * wz_k_run2,
+        # XSDB NLO (powheg) 4.924 pb × k(NLO POWHEG -> NNLO QCD x NLO EW)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=10&searchQuery=DAS=WZto3LNu_TuneCP5_13p6TeV_powheg-pythia8  # noqa
+        13.6: Number(4.924) * wz_k_run3,
+    },
 )
 
 wz_wqq_zll = wz.add_process(
     name="wz_wqq_zll",
     id=8220,
-    xsecs=multiply_xsecs(wz, const.br_w.had * const.br_z.clep),
+    xsecs={
+        13: wz.get_xsec(13) * const.br_w.had * const.br_z.clep,
+        # XSDB NLO (powheg) 7.568 pb × k(NLO POWHEG -> NNLO QCD x NLO EW)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/ DAS=WZto2L2Q_TuneCP5_13p6TeV_powheg-pythia8
+        # verified from CMS AN-2023/179
+        # MATRIX paper: https://arxiv.org/abs/1912.00068
+        13.6: Number(7.568) * wz_k_run3,
+    },
 )
 
 wz_wqq_zqq = wz.add_process(
     name="wz_wqq_zqq",
     id=8240,
-    xsecs=multiply_xsecs(wz, const.br_w.had * const.br_z.qq),
+    xsecs={
+        13: wz.get_xsec(13) * const.br_w.had * const.br_z.qq,
+        # XSDB labels this as "LO" but it is actually NLO (amcatnloFXFX = NLO + FxFx jet merging):
+        #   - 21% negative weights (impossible at LO)
+        #   - FxFx matching efficiency ~63% (before: 39.31 pb, after: 24.97 pb)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/ DAS=WZto4Q-1Jets-4FS_TuneCP5_13p6TeV_amcatnloFXFX-pythia8
+        # GenXSecAnalyzer (Run3Summer22EEMiniAODv4, 1M events): 24.97 ± 0.03314 pb (after matching)
+        # NLO (amcatnlo) 24.97 pb × k(NLO -> NNLO QCD x NLO EW)
+        # MATRIX paper: https://arxiv.org/abs/1912.00068
+        13.6: Number(24.97, {"tot": 0.03314}) * wz_k_run3,
+    },
 )
 
-# no additional cut found in generator card in MCM:
-# dataset: /WZTo1L1Nu2Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM  # noqa
-# therefore, value obtained from branching ratio.
-# Log for GenXSecAnalyzer of
-# for WZTo1L1Nu2Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8 (Summer20UL16, NLO) -> value : Number(9.159, {"tot": 0.008259})
-# also available, but not used here
+# GenXSecAnalyzer of WZTo1L1Nu2Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8 (Summer20UL16, NLO)
+# -> value: Number(9.159, {"tot": 0.008259}), also available but not used for 13 TeV
 wz_wlnu_zqq = wz.add_process(
     name="wz_wlnu_zqq",
     id=8230,
-    xsecs=multiply_xsecs(wz, const.br_w.lep * const.br_z.qq),
+    xsecs={
+        13: wz.get_xsec(13) * const.br_w.lep * const.br_z.qq,
+        # XSDB NLO (powheg) 15.87 pb × k(NLO POWHEG -> NNLO QCD x NLO EW)
+        # https://xsecdb-xsdb-official.app.cern.ch/xsdb/ DAS=WZtoLNu2Q_TuneCP5_13p6TeV_powheg-pythia8
+        # GenXSecAnalyzer (Run3Summer22EEMiniAODv4, 1M events): 15.87 ± 0.007874 pb — exact match with XSDB
+        # MATRIX paper: https://arxiv.org/abs/1912.00068
+        13.6: Number(15.87, {"tot": 0.007874}) * wz_k_run3,
+    },
 )
 
 # wz + photon
@@ -2370,21 +2542,255 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     },
 )
 
+# w + photon
+wg_wlnu = Process(
+    name="wg_wlnu",
+    id=9600,
+    label=r"$W\gamma \rightarrow \ell\nu\gamma$",
+    xsecs={
+        # NLO from XSDB: https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=40&searchQuery=process_name%3D%5EWGtoLNuG-1Jets_TuneCP5_13p6TeV  # noqa
+        13.6: Number(671.5, {
+            "tot": 0.7548,
+        }),
+    },
+)
+
+# DY + photon (Zγ)
+# Run 3 naming: DYGto2LG-1Jets (was ZGTo2LG in Run 2)
+# NLO cross sections from XSDB for inclusive samples
+# LO cross sections from XSDB for PTG-binned samples (bounded bins, 2022/2023)
+# NLO cross sections from XSDB for PTG-binned samples (open thresholds, 2024 Bin- convention)
+
+dyg = Process(
+    name="dyg",
+    id=9700,
+    label=r"DY+$\gamma$",
+)
+
+dyg_m50toinf = dyg.add_process(
+    name="dyg_m50toinf",
+    id=9710,
+    label=r"DY+$\gamma$ ($m_{\ell\ell} \geq 50$)",
+    xsecs={
+        # NLO from XSDB: DYGto2LG-1Jets_MLL-50_TuneCP5_13p6TeV_amcatnloFXFX-pythia8
+        13.6: Number(127.0, {
+            "tot": 0.1484,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+    },
+)
+
+# bounded PTG bins (used in 2022/2023 campaigns)
+
+dyg_m50toinf_ptg10to100 = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg10to100",
+    id=9711,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(126.6, {
+            "tot": 0.4287,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (10.0, 100.0),
+    },
+)
+
+dyg_m50toinf_ptg100to200 = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg100to200",
+    id=9712,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.3493, {
+            "tot": 0.001778,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (100.0, 200.0),
+    },
+)
+
+dyg_m50toinf_ptg200to400 = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg200to400",
+    id=9713,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.04331, {
+            "tot": 0.000221,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (200.0, 400.0),
+    },
+)
+
+dyg_m50toinf_ptg400to600 = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg400to600",
+    id=9714,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.00313, {
+            "tot": 0.00001539,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (400.0, 600.0),
+    },
+)
+
+dyg_m50toinf_ptg600toinf = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg600toinf",
+    id=9715,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.0006528, {
+            "tot": 0.000002983,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (600.0, const.inf),
+    },
+)
+
+# open-threshold PTG bins (used in 2024 Bin- convention)
+
+dyg_m50toinf_ptg100toinf = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg100toinf",
+    id=9716,
+    xsecs={
+        # NLO from XSDB: DYGto2LG-1Jets_Bin-MLL-50-PTG-100
+        13.6: Number(0.3942, {
+            "tot": 0.0007196,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (100.0, const.inf),
+    },
+)
+
+dyg_m50toinf_ptg200toinf = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg200toinf",
+    id=9717,
+    xsecs={
+        # NLO from XSDB: DYGto2LG-1Jets_Bin-MLL-50-PTG-200
+        13.6: Number(0.04738, {
+            "tot": 0.00008731,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (200.0, const.inf),
+    },
+)
+
+dyg_m50toinf_ptg400toinf = dyg_m50toinf.add_process(
+    name="dyg_m50toinf_ptg400toinf",
+    id=9718,
+    xsecs={
+        # NLO from XSDB: DYGto2LG-1Jets_Bin-MLL-50-PTG-400
+        13.6: Number(0.003741, {
+            "tot": 0.00002272,
+        }),
+    },
+    aux={
+        "mll": (50.0, const.inf),
+        "ptg": (400.0, const.inf),
+    },
+)
+
+dyg_m4to50 = dyg.add_process(
+    name="dyg_m4to50",
+    id=9720,
+    label=r"DY+$\gamma$ ($4 \leq m_{\ell\ell} < 50$)",
+    xsecs={
+        # NLO from XSDB: DYGto2LG-1Jets_Bin-MLL-4to50 (2024)
+        13.6: Number(88.13, {
+            "tot": 0.09618,
+        }),
+    },
+    aux={
+        "mll": (4.0, 50.0),
+    },
+)
+
+dyg_m4to50_ptg10to100 = dyg_m4to50.add_process(
+    name="dyg_m4to50_ptg10to100",
+    id=9721,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(88.17, {
+            "tot": 0.2807,
+        }),
+    },
+    aux={
+        "mll": (4.0, 50.0),
+        "ptg": (10.0, 100.0),
+    },
+)
+
+dyg_m4to50_ptg100to200 = dyg_m4to50.add_process(
+    name="dyg_m4to50_ptg100to200",
+    id=9722,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.2413, {
+            "tot": 0.001249,
+        }),
+    },
+    aux={
+        "mll": (4.0, 50.0),
+        "ptg": (100.0, 200.0),
+    },
+)
+
+dyg_m4to50_ptg200toinf = dyg_m4to50.add_process(
+    name="dyg_m4to50_ptg200toinf",
+    id=9723,
+    xsecs={
+        # LO from XSDB
+        13.6: Number(0.02224, {
+            "tot": 0.0001052,
+        }),
+    },
+    aux={
+        "mll": (4.0, 50.0),
+        "ptg": (200.0, const.inf),
+    },
+)
+
 # NNLO QCD from https://twiki.cern.ch/twiki/bin/view/CMS/StandardModelCrossSectionsat13TeV?rev=28
 # itself from https://arxiv.org/pdf/1408.5243.pdf v1
+#
+# 13.6 TeV: WW_TuneCP5_13p6TeV_pythia8 is LO Pythia (WeakDoubleBoson:ffbar2WW, qq only).
+# McM fragment: BTV-Run3Summer22GS-00015, crossSection = 75.8 (hardcoded LO).
+# GenXSecAnalyzer: 80.22 pb (LO). XSDB: 80.23 pb.
+# k(LO→NNLO) ≈ 1.75 from Grazzini et al., JHEP 08 (2016) 140 [arXiv:1605.02716], Table 2:
+#   13 TeV: NNLO/LO = 1370.9/778.99 = 1.76
+#
+# k-factors for WW
+#   qqWW: k=1.14 (NLO→NNLO) from arXiv:1605.02716 (Grazzini et al., JHEP 08 (2016) 140)
+#   ggWW: k=1.41 (LO→NLO) from arXiv:1511.08617 (Caola et al., Phys. Lett. B 754 (2016) 275)
+#   LO→NNLO (Pythia inclusive): k≈1.75 from the same Grazzini et al. paper
+ww_k_lo_to_nnlo = 1.75    # LO→NNLO (Pythia inclusive)
+ww_k_nlo_to_nnlo = 1.14   # qqWW: NLO→NNLO
+ww_gg_k_lo_to_nlo = 1.41  # ggWW: LO MCFM → NLO
 
-# old value before update:
-# https://cms.cern.ch/iCMS/jsp/db_notes/noteInfo.jsp?cmsnoteid=CMS%20AN-2019/197 (v3) Number(75.91) (LO)
 ww = vv.add_process(
     name="ww",
     id=8300,
     label="WW",
     xsecs={
         13: Number(118.7, {"scale": (0.025j, 0.022j)}),
-        # 13.6 from GenXSecAnalyzer:
-        13.6: Number(80.22, {
-            "tot": 0.01677,  # xsdb: Number(80.23, {"tot": 0.3733})
-        }),
+        # 13.6: LO Pythia GenXSecAnalyzer × k(LO→NNLO)
+        13.6: Number(80.22, {"tot": 0.01677}) * ww_k_lo_to_nnlo,
     },
 )
 
@@ -2392,9 +2798,28 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
 for cme in [13]:
     vv.set_xsec(cme, ww.get_xsec(cme) + wz.get_xsec(cme) + zz.get_xsec(cme))
 
+# qqWW: each decay mode normalized independently by its NLO XSDB value × k(NLO→NNLO)
+# NLO XS values from XSDB for individual Powheg samples (WWto2L2Nu, WWtoLNu2Q, WWto4Q)
+
+# XSDB NLO values (pb) for individual qqWW decay modes at 13.6 TeV
+ww_dl_nlo_13p6 = Number(11.79, {"tot": 0.004216})
+ww_sl_nlo_13p6 = Number(48.94, {"tot": 0.0175})
+ww_fh_nlo_13p6 = Number(50.79, {"tot": 0.01816})
+
+qqww = ww.add_process(
+    name="qqww",
+    id=8370,
+    label=r"$q\bar{q} \rightarrow WW$",
+    xsecs={
+        13: ww.get_xsec(13),  # at 13 TeV, qqWW ≈ inclusive (ggWW is small)
+        # 13.6: sum of Powheg NLO decay modes × k(NLO→NNLO)
+        13.6: (ww_dl_nlo_13p6 + ww_sl_nlo_13p6 + ww_fh_nlo_13p6) * ww_k_nlo_to_nnlo,
+    },
+)
+
 # no additional cut found in generator card:
 # https://raw.githubusercontent.com/cms-sw/genproductions/master/bin/Powheg/production/2017/13TeV/WWTo2L2Nu_NNPDF31nnlo_13TeV/WWTo2L2Nu_NNPDF31nnlo_13TeV.input  # noqa
-# therefore, value obtained from branching ratio.
+# therefore, 13 TeV value obtained from branching ratio.
 # Log for GenXSecAnalyzer of
 # WWTo2L2Nu_TuneCP5_13TeV-powheg-pythia8 (Summer20UL16, NLO) with Number(11.09, {"tot": 0.00704})
 # also available, but not used here
@@ -2403,12 +2828,14 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     id=8310,
     xsecs={
         13: ww.get_xsec(13) * const.br_ww.dl,  # value around 12.6 for comparison to GenXSecAnalyzer NLO result
+        # 13.6: XSDB NLO × k(NLO→NNLO)
+        13.6: ww_dl_nlo_13p6 * ww_k_nlo_to_nnlo,
     },
 )
 
 # no additional cut found in generator card in MCM:
 # dataset: /WWTo1L1Nu2Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM  # noqa
-# therefore, value obtained from branching ratio.
+# therefore, 13 TeV value obtained from branching ratio.
 # Log for GenXSecAnalyzer of
 # for WWTo1L1Nu2Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8 (Summer20UL16, NLO) -> value : Number(50.94, {"tot": 0.042})
 # also available, but not used here
@@ -2417,12 +2844,14 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     id=8320,
     xsecs={
         13: ww.get_xsec(13) * const.br_ww.sl,  # value around 50.06 for comparison to GenXSecAnalyzer NLO result
+        # 13.6: XSDB NLO × k(NLO→NNLO)
+        13.6: ww_sl_nlo_13p6 * ww_k_nlo_to_nnlo,
     },
 )
 
 # no additional cut found in generator card in MCM:
 # dataset: /WWTo4Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM  # noqa
-# therefore, value obtained from branching ratio.
+# therefore, 13 TeV value obtained from branching ratio.
 # Log for GenXSecAnalyzer of
 # for WWTo4Q_4f_TuneCP5_13TeV-amcatnloFXFX-pythia8 (Summer20UL16, NLO) -> value : Number(51.53, {"tot": 0.04349})
 # also available, but not used here
@@ -2431,43 +2860,103 @@ def get_dy_ll_m50toinf_xsec_13p6(*name):
     id=8330,
     xsecs={
         13: ww.get_xsec(13) * const.br_ww.fh,  # value around 53.94 for comparison to GenXSecAnalyzer NLO result
+        # 13.6: XSDB NLO × k(NLO→NNLO)
+        13.6: ww_fh_nlo_13p6 * ww_k_nlo_to_nnlo,
     },
 )
 
-ww_wenu_wenu = ww_dl.add_process(
+# ggWW: each decay mode normalized independently by its LO MCFM value × k(LO→NLO)
+# LO XS values in fb from XSDB for individual mcfm samples (XSDB mistakenly lists as pb; MCFM outputs in fb)
+# See also CMS AN-2023/179.
+#
+# NOTE on same-flavor vs different-flavor:
+# MCFM gridpacks give the same XS for all channels (per-sample).
+# Same-flavor (ee, μμ, ττ): 1 sample per pair → XS = mcfm_lo × k
+# Different-flavor (eμ, eτ, μτ): 2 samples per pair (e.g., ENuMuNu + MuNuENu) → XS = 2 × mcfm_lo × k
+# Total ggWW→2l2ν = (same + diff) × n_leps
+
+# MCFM LO value (pb, converted from fb) — same for all channels at 13.6 TeV
+gg_ww_mcfm_lo_13p6 = Number(49.63e-03)  # 49.63 fb from XSDB
+
+# per-channel: same-flavor = 1× and different-flavor = 2× (two sample orderings)
+gg_ww_same_13p6 = gg_ww_mcfm_lo_13p6 * ww_gg_k_lo_to_nlo
+gg_ww_diff_13p6 = 2 * gg_ww_mcfm_lo_13p6 * ww_gg_k_lo_to_nlo
+
+ggww = ww.add_process(
+    name="ggww",
+    id=8380,
+    label=r"$gg \rightarrow WW$",
+    xsecs={
+        # sum of ggWW decay modes: (same + diff) × n_leps
+        13.6: (gg_ww_same_13p6 + gg_ww_diff_13p6) * const.n_leps,
+    },
+)
+
+ww_wenu_wenu = ww.add_process(
     name="ww_wenu_wenu",
     id=8311,
-    xsecs=multiply_xsecs(ww, const.br_ww.enuenu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.enuenu,
+        13.6: gg_ww_same_13p6,  # same-flavor, 1 sample
+    },
 )
 
-ww_wenu_wmnu = ww_dl.add_process(
+ww_wenu_wmnu = ww.add_process(
     name="ww_wenu_wmnu",
     id=8312,
-    xsecs=multiply_xsecs(ww, const.br_ww.enumnu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.enumnu,
+        13.6: gg_ww_diff_13p6,  # different-flavor, 2 samples (ENuMuNu + MuNuENu)
+    },
 )
 
-ww_wenu_wtnu = ww_dl.add_process(
+ww_wenu_wtnu = ww.add_process(
     name="ww_wenu_wtnu",
     id=8313,
-    xsecs=multiply_xsecs(ww, const.br_ww.enutnu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.enutnu,
+        13.6: gg_ww_diff_13p6,  # different-flavor, 2 samples
+    },
 )
 
-ww_wmnu_wmnu = ww_dl.add_process(
+ww_wmnu_wmnu = ww.add_process(
     name="ww_wmnu_wmnu",
     id=8314,
-    xsecs=multiply_xsecs(ww, const.br_ww.mnumnu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.mnumnu,
+        13.6: gg_ww_same_13p6,  # same-flavor, 1 sample
+    },
 )
 
-ww_wmnu_wtnu = ww_dl.add_process(
+ww_wmnu_wtnu = ww.add_process(
     name="ww_wmnu_wtnu",
     id=8315,
-    xsecs=multiply_xsecs(ww, const.br_ww.mnutnu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.mnutnu,
+        13.6: gg_ww_diff_13p6,  # different-flavor, 2 samples
+    },
 )
 
-ww_wtnu_wtnu = ww_dl.add_process(
+ww_wtnu_wtnu = ww.add_process(
     name="ww_wtnu_wtnu",
     id=8316,
-    xsecs=multiply_xsecs(ww, const.br_ww.tnutnu),
+    xsecs={
+        13: ww.get_xsec(13) * const.br_ww.tnutnu,
+        13.6: gg_ww_same_13p6,  # same-flavor, 1 sample
+    },
+)
+
+# same-sign WW (EWK+QCD)
+ww_ss_2j = Process(
+    name="ww_ss_2j",
+    id=8400,
+    label=r"$W^{\pm}W^{\pm}jj$",
+    xsecs={
+        # LO from XSDB: https://xsecdb-xsdb-official.app.cern.ch/xsdb/?columns=67108863&currentPage=0&pageSize=40&searchQuery=process_name%3D%5EWpWpJJ-EWK-QCD_TuneCP5_13p6TeV  # noqa
+        13.6: Number(0.0587, {
+            "tot": 0.00001523,
+        }),
+    },
 )
 
 #