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tokens: data set in the context of ΛCDM is less than . This is an effect approximately at 2σ level. In fact, this probability is even smaller if we consider the exact σ differences that are shown in Table 1 and find the fraction of simulated data sets with simultaneous σ differences larger that the exact corresponding σ differences of the real data. In particular we find that the probability to have simultaneously 1.14σ difference (or larger) in the first bin, 1.48σ difference (or larger) in the second bin, and 0.99σ difference (or larger) in the third bin for , is . Similarly, for we find the same probability to be . Even though this decrease of probability is interesting to note, it is not generic as it is based on the fine tuned σ deviations of the real data bins from the full data best fits (1.14σ, 1.48σ, and 0.99σ). Thus, this is an aposteriori statistic constructed after looking at the data. Therefore, we adopt the more generic and conservative statistical level of significance of corresponding to the simultaneous deviation of at least 1σ for all three lowest z bins. Note that a similar oscillating effect was also observed in Refs. Kazantzidis Perivolaropoulos ( 2020 ), Sapone et al. ( 2020 ) even though its statistical significance was not quantified using simulated data as in the present analysis. Moreover, it is interesting to check if this behaviour is also evident for any three out of four bins. In 1000 Monte Carlo realizations we find that the number of simulated data sets where the derived in any 3 bins is more than 1σ away from the best fit to the whole (random) data sample is while the corresponding number of cases for is as it is demonstrated in Fig. 3 . The probability is smaller if we consider the exact σ difference of Table 1 . In particular, we derive the number of cases where the derived in any 3 bins is more than away from the best fit to the whole (random) data sample is , while the corresponding number of cases for is . A summary of the results can be seen in Table 2 . These results indicate that the aforementioned oscillating effect is much more prominent at low z ≲ 0.5 where the dark energy density is more prominent than in the fourth bin, which involves higher z . This fact favours the possibility that the effect has a physical origin since a systematic effect would probably affect equally all four redshift bins. Figure 3. Left-hand panel: Percent of simulated Pantheon dataset (including systematics) where any three out of four bins all differ simultaneously more than from the best fit of the full data set. Right-hand panel: Same as the left-hand panel for the parameter instead of . Table 2. Summary of the Monte Carlo deviations from the simulated and real data. The obtained results considering the exact σ real differences should be treated with care, since this decrease of the probabilities is not generic and it is based on a fine tuned σ value. 3 CONCLUSION – OUTLOOK We performed a redshift tomography of the Pantheon