Data-MC Level5

The data-mc comparisons are performed on level 5. From the years 2012, 2016 und 2020 the first and 15th day of each month is processed. This results in a total experimental livetime of \(2487\,\mathrm{h}\). The quality cuts used for level 5 are shown as a vertical black line in the plots. All plots also include the impact of the neutrinos, which are treated as background in this analysis. For the neutrino contamination, NuGen dataset for electrons, muons and taus are weighted with both atmospheric fluxes and an astrophysical component. For the atmospheric flux, the neutrinos are weighted with the respective cosmic-ray model. However, since the differences are very small, all predictions are presented in the same color (pink). For the astrophysical component, a single power law (SPL) with a normalizatoin of n = 1.8e-18 and a spectral index of gamma = 2.52 is assumed, taken from Measurement of the astrophysical diffuse neutrino flux in a combined fit of IceCube’s high energy neutrino data.

Note

In Table 6 the rates for the different primary flux models are shown for level 4. There is a mismatch of the normalization of the data and the MC. For the data-mc comparisons, the following plots use scaled weights. Therefore, the weights are normalized to the data for each weighting. This helps to analyze the shape of the different primary flux models. The rescaling is done based on the rates on level 5. The rates and the rescaling factors are shown in Table 13. Additional data-mc plots to investigate cuts and all primary flux models are dumped here. For the unfolding, only the relative transition from the reconstructed proxy to the target variable matters, thus the normalization is completely negligible.

Table 13 Rates on level 4 after applying the muon filter and a \(500\,\mathrm{TeV}\) bundle energy cut at surface for different primary models and level 5 with the quality cuts are shown. The rescale factors are the ratio between the experimental rate and the MC rate. The rescaling is done based on the rates on level 4.
Model	H3a	H4a	GST	GSF	Exp
Level 4 / mHz	21.62	21.09	20.92	14.07	18.55
Rescale factor L4	0.86	0.88	0.89	1.32
Level 5 / mHz	15.16	14.76	14.79	9.68	12.36
Rescale factor L5	0.82	0.84	0.84	1.28

Seasonal Variations

As presented in the analysis of Karolin Hymon, there are seasonal variations in the production of leptons in the atmosphere (wiki page). These variations are caused by the temperature and pressure changes in the atmosphere. Our new dataset allows us to investigate these variations, since we have simulated all 12 months/atmospheres per year (usually, only 4 atmospheres are simulated). The following plot Fig. 84 shows the rate per month for the different primary flux models.

../_images/rate_per_month_level5.png — Fig. 84 : Rate per month for different primary flux models.

As already mentioned above, there is a mismatch of the normalization of the data and the MC. In Fig. 85, the rates are rescaled. The shape is in agreement for all primary flux models.

../_images/rate_per_month_level5_scaled_weights.png — Fig. 85 : Rate per month for different primary flux models with scaled weights.

Note

The data-MC comparisons below are presented to investigate different properties of this dataset and the new DNN reconstructions after the quality cuts have been applied. However, for the unfolding, only the leading muon energy at entry is utilized, and thus, data-MC mismatches in other variables do not affect the unfolding result.

Energy

Bundle energy at entry

Leading muon energy at entry

../_images/data_mc_energy_hist_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_entry_energy_all_weightings1.png — Fig. 87 : Leading muon energy at entry reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Bundle energy at surface

../_images/data_mc_energy_hist_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_in_mctree_all_weightings1.png — Fig. 88 : Bundle energy at surface reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

../_images/data_mc_energy_hist_DeepLearningReco_precut_surface_bundle_energy_3inputs_6ms_01_bundle_energy_in_mctree_all_weightings1.png — Fig. 89 : Bundle energy at surface reconstructed by pre-cut network `DeepLearningReco_precut_surface_bundle_energy_3inputs_6ms_01`.

Leading muon energy at surface

../_images/data_mc_energy_hist_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_muon_energy_first_mctree_all_weightings1.png — Fig. 90 : Leading muon energy at surface reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Energy uncertainty

Bundle energy at entry - uncertainty

../_images/data_mc_energy_hist_log_uncertainty_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_at_entry_all_weightings2.png — Fig. 91 : Uncertainty of bundle energy at entry reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Leading muon energy at entry - uncertainty

../_images/data_mc_energy_hist_log_uncertainty_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_entry_energy_all_weightings2.png — Fig. 92 : Uncertainty of leading muon energy at entry reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Bundle energy at surface - uncertainty

../_images/data_mc_energy_hist_log_uncertainty_DeepLearningReco_precut_surface_bundle_energy_3inputs_6ms_01_bundle_energy_in_mctree_all_weightings2.png — Fig. 94 : Uncertainty of bundle energy at surface reconstructed by pre-cut network `DeepLearningReco_precut_surface_bundle_energy_3inputs_6ms_01`.

Leading muon energy at surface - uncertainty

../_images/data_mc_energy_hist_log_uncertainty_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_muon_energy_first_mctree_all_weightings2.png — Fig. 95 : Uncertainty of leading muon energy at surface reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Zenith

Cosine zenith

Zenith - uncertainty

../_images/data_mc_cos_zenith_hist_uncertainty_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_all_weightings2.png — Fig. 97 : Uncertainty of zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

Azimuth

Azimuth - uncertainty

../_images/data_mc_azimuth_hist_uncertainty_DeepLearningReco_direction_9inputs_6ms_medium_02_03_azimuth_all_weightings2.png — Fig. 99 : Uncertainty of azimuth reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

Center position

Time

../_images/data_mc_center_pos_t_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 100 : Center time reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Time - uncertainty

../_images/data_mc_center_pos_t_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 101 : Uncertainty of center time reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position x

../_images/data_mc_center_pos_x_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 102 : Center position x reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position x - uncertainty

../_images/data_mc_center_pos_x_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 103 : Uncertainty of center position x reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position y

../_images/data_mc_center_pos_y_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 104 : Center position y reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position y - uncertainty

../_images/data_mc_center_pos_y_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 105 : Uncertainty of center position y reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position z

Further investigations of the z-vertex can be found in the Appendix/Z-vertex investigations (L5).

../_images/data_mc_center_pos_z_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 106 : Center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position z - uncertainty

../_images/data_mc_center_pos_z_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 107 : Uncertainty of center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Entry position

Time

../_images/data_mc_entry_pos_t_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 108 : Entry time reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Time - uncertainty

../_images/data_mc_entry_pos_t_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 109 : Uncertainty of entry time reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position x

../_images/data_mc_entry_pos_x_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 110 : Entry position x reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position x - uncertainty

../_images/data_mc_entry_pos_x_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 111 : Uncertainty of entry position x reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position y

../_images/data_mc_entry_pos_y_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 112 : Entry position y reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position y - uncertainty

../_images/data_mc_entry_pos_y_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 113 : Uncertainty of entry position y reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position z

Further investigations of the z-vertex can be found in the Appendix/Z-vertex investigations (L5).

../_images/data_mc_entry_pos_z_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 114 : Entry position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Position z - uncertainty

../_images/data_mc_entry_pos_z_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 115 : Uncertainty of entry position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Propagation length

Total propagation length

../_images/data_mc_length_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 116 : Propagation length reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Length in detector

Total propagation length - uncertainty

../_images/data_mc_Length_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings2.png — Fig. 118 : Uncertainty of propagation length reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

Length in detector - uncertainty

Systematics

Detailed information about the systematics used for this analysis can be found here.

Further plots with all 4 primary models can be found in the Google docs here.

Note

In the following, the impact of the ice systematics is investigated for three different properties: the bundle energy at entry, the cos(zenith) and the z-vertex. However, these variables are not used for the unfolding, and thus they are negligible for the analysis. They are presented here to visualize the impact of the ice systematics on different variables at this selection stage, level 5.

Bundle energy at entry

../_images/data_mc_sys_energy_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_at_entry_HoleiceForward_Unified_p0_GSF_5_sys_bins1.png — Fig. 122 : **Hole ice forward unified p0** effect on bundle energy at entry reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

../_images/data_mc_sys_energy_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_at_entry_Scattering_GSF_5_sys_bins1.png — Fig. 124 : **Scattering** effect on bundle energy at entry reconstructed by `DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02`.

Cosine zenith

../_images/data_mc_sys_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_Absorption_GSF_5_sys_bins1.png — Fig. 125 : **Absorption** effect on cosine zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

../_images/data_mc_sys_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_DOMEfficiency_GSF_5_sys_bins1.png — Fig. 126 : **DOM efficiency** effect on cosine zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

../_images/data_mc_sys_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_HoleIceForward_Unified_p0_GSF_5_sys_bins1.png — Fig. 127 : **Hole ice forward unified p0** effect on cosine zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

../_images/data_mc_sys_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_HoleIceForward_Unified_p1_GSF_5_sys_bins1.png — Fig. 128 : **Hole ice forward unified p1** effect on cosine zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

../_images/data_mc_sys_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_Scattering_GSF_5_sys_bins1.png — Fig. 129 : **Scattering** effect on cosine zenith reconstructed by `DeepLearningReco_direction_9inputs_6ms_medium_02_03`.

Center position z

../_images/data_mc_sys_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_center_pos_z_Absorption_GSF_5_sys_bins1.png — Fig. 130 : **Absorption** effect on center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

../_images/data_mc_sys_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_center_pos_z_DOMEfficiency_GSF_5_sys_bins1.png — Fig. 131 : **DOM efficiency** effect on center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

../_images/data_mc_sys_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_center_pos_z_HoleIceForward_Unified_p0_GSF_5_sys_bins1.png — Fig. 132 : **Hole ice forward unified p0** effect on center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

../_images/data_mc_sys_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_center_pos_z_HoleIceForward_Unified_p1_GSF_5_sys_bins1.png — Fig. 133 : **Hole ice forward unified p1** effect on center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.

../_images/data_mc_sys_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_center_pos_z_Scattering_GSF_5_sys_bins1.png — Fig. 134 : **Scattering** effect on center position z reconstructed by `DeepLearningReco_track_geometry_9inputs_6ms_medium_01`.