Data-MC Final Level

The data-mc comparisons are performed on final level. 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, resulting 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 final level. The rates and the rescaling factors are shown in Table 14. 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 14 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

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

Final Level / mHz

1.29

1.33

1.09

1.33

1.41

Rescale factor Final Level

1.12

1.09

1.32

1.09

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. 135 shows the rate per month for the different primary flux models.

../_images/rate_per_month_finallevel.png

Fig. 135 : 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. 136, the rates are rescaled. The shape is in agreement for all primary flux models.

../_images/rate_per_month_finallevel_scaled_weights.png

Fig. 136 : 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. For the analysis, only Fig. 138 is relevant.

Energy

Bundle energy at entry

../_images/data_mc_energy_hist_DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_at_entry_NuGen_astro_atmo_all_weightings.png

Fig. 137 : Bundle energy at entry reconstructed by DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02.

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_NuGen_astro_atmo_all_weightings.png

Fig. 138 : 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_NuGen_astro_atmo_all_weightings.png

Fig. 139 : 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_NuGen_astro_atmo_all_weightings.png

Fig. 140 : 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_NuGen_astro_atmo_all_weightings.png

Fig. 141 : 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_weightings.png

Fig. 142 : 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_weightings.png

Fig. 143 : 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_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02_bundle_energy_in_mctree_all_weightings.png

Fig. 144 : Uncertainty of bundle energy at surface reconstructed by DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02.

../_images/data_mc_energy_hist_log_uncertainty_DeepLearningReco_precut_surface_bundle_energy_3inputs_6ms_01_bundle_energy_in_mctree_all_weightings.png

Fig. 145 : 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_weightings.png

Fig. 146 : Uncertainty of leading muon energy at surface reconstructed by DeepLearningReco_leading_bundle_surface_leading_bundle_energy_OC_inputs9_6ms_large_log_02.

Zenithsine zenith

../_images/data_mc_cos_zenith_hist_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_all_weightings.png

Fig. 147 : Cosine zenith reconstructed by DeepLearningReco_direction_9inputs_6ms_medium_02_03.

Zenith - uncertainty

../_images/data_mc_cos_zenith_hist_uncertainty_DeepLearningReco_direction_9inputs_6ms_medium_02_03_cos_zenith_all_weightings.png

Fig. 148 : Uncertainty of zenith reconstructed by DeepLearningReco_direction_9inputs_6ms_medium_02_03.

Azimuth

Azimuth

../_images/data_mc_azimuth_hist_DeepLearningReco_direction_9inputs_6ms_medium_02_03_azimuth_all_weightings.png

Fig. 149 : Azimuth reconstructed by DeepLearningReco_direction_9inputs_6ms_medium_02_03.

Azimuth - uncertainty

../_images/data_mc_azimuth_hist_uncertainty_DeepLearningReco_direction_9inputs_6ms_medium_02_03_azimuth_all_weightings.png

Fig. 150 : 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_weightings.png

Fig. 151 : 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_weightings.png

Fig. 152 : 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_weightings.png

Fig. 153 : 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_weightings.png

Fig. 154 : 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_weightings.png

Fig. 155 : 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_weightings.png

Fig. 156 : 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_weightings.png

Fig. 157 : 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_weightings.png

Fig. 158 : 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_weightings.png

Fig. 159 : 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_weightings.png

Fig. 160 : 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_weightings.png

Fig. 161 : 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_weightings.png

Fig. 162 : 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_weightings.png

Fig. 163 : 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_weightings.png

Fig. 164 : 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_weightings.png

Fig. 165 : 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_weightings.png

Fig. 166 : 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_weightings.png

Fig. 167 : Propagation length reconstructed by DeepLearningReco_track_geometry_9inputs_6ms_medium_01.

Length in detector

../_images/data_mc_length_in_detector_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings.png

Fig. 168 : Length in detector reconstructed by DeepLearningReco_track_geometry_9inputs_6ms_medium_01.

Total propagation length - uncertainty

../_images/data_mc_Length_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings.png

Fig. 169 : Uncertainty of propagation length reconstructed by DeepLearningReco_track_geometry_9inputs_6ms_medium_01.

Length in detector - uncertainty

../_images/data_mc_LengthInDetector_uncertainty_DeepLearningReco_track_geometry_9inputs_6ms_medium_01_all_weightings.png

Fig. 170 : Uncertainty of length in detector reconstructed by DeepLearningReco_track_geometry_9inputs_6ms_medium_01.