5. Comparison to Data
We show next how to estimate the new measure of cosmic acceleration,
, using direct astrophysical observations. As an example consider the Supernovae Ia (SNIa) data as given by the ’Pantheon Sample’ compilation ([
27]) consisting on 1048 SNIas between
. Each SNIa provides a direct estimate of the luminosity distance
at a given measured redshift
z. This corresponds to the comoving look-back distance:
so that
gives us directly
. The second derivative gives us the acceleration:
is given by the model prediction in Eq.
10 (arbitrarily fixed at
in both data and models). We adopt here the approach presented in [
18], who used an empirical fit to the luminosity distance measurements, based on a third-order logarithmic polynomial:
where
. [
18] find a good fit to:
and
to the full SNIa ’Pantheon Sample’. We use these values of
A and
B and its corresponding errors to estimate
H,
q and
using the above relations. Results for
H and
q are shown as shaded cyan regions in the left panel
Figure 2. They are compared to the LCDM predictions in Eq.
2 and
3.
There is a very good agreement in
for
. At
, the
estimates are also consistent with the
predictions. But the detailed
evolution with redshift in the SNIa data does not seem to follow any of the model predictions, specially for
. The
estimates are too steep compare to the different models predictions. If we compare instead the
estimates (see right panel of
Figure 2) we find a much better agreement with the model predictions. This seems to validate our
approach, but it is not clear from this comparison alone if this is caused by the fitting function use in Eq.
15.
To test this further we use measurements of the radial BAO data to estimate
. Such measurements give us a direct estimate of
(as first demonstrated by [
15,
16]) so they have the advantage over SNIa that we only need to do a first order derivative, to estimate
q or
:
As an illustration we use
measurements presented in Table 2 in [
20]. This compilation of
is shown as red points with
errorbars in the left panel
Figure 2. The compilation include values from the clustering of galaxies (
) and Ly-alpha forest in QSO (
). The combination of two separate ranges of redshift allows for a very good measurement of
at the intermediate redshift (
), where we found the discrepancies in SNIa for
q and
model comparison (see above). The radial BAO provides a very good constraint on cosmic acceleration, independent of possible calibration errors in
or sampling errors (from small area samples). This is something that we can not yet do with the current SNIa data, but will be very interesting to see in the near future with upcoming data from wider and deeper surveys.
We fit a quadratic polynomial to the radial BAO data:
We have checked that the results presented here are very similar if we use a cubic polynomial. In units of Km/s/Mpc, we find
,
and
, with strong covariance between the errors (the cross-correlation coefficient between
and
is
). The value of
is in good agreement with the Planck CMB fit ([
24]) but in some tension with the SNIa local calibration:
(see [
25]). This corresponds to either a local calibration problem (in SNIa, in radial BAO or in both) or a tension in the
CDM model at different times or distances (see e.g. [
1]). We ignore this normalization problem here and just focus on the evolution of
to measure cosmic acceleration
q or
(which are fairly independent of
).
In the right panel of
Figure 2 we show (as shaded regions) the measurements for
given by combining Eq.
15 with Eq.
14 and Eq.
17 with Eq.
16. The measurements clearly favour models with large negative cosmic event acceleration
, which supports our interpretation of
as a friction term.
Comparing left and right panels in
Figure 2 we see that both
q and
are rougthly consistent with models with
( or
) in good concordance with
in the upper left panel of
Figure 2.
Even when the underlying model for
q and
is the same, note how the measured
q and
data have different tensions with the model predictions as a function of redshift. In particular, the radial BAO and SNIa data sets show inconsistencies among them for
q around
. This is a well known tension (see e.g. 17 in [
4]). This tension disappears when we use the corresponding estimates for
. Thus, data is more consistent with the
than with the
q description.
One would expect that a perfect realizations of the LCDM model in Eq.
2 would produce consistent results in both
q and
. But deviations from LCDM and systematic effects can produce tensions in data, specially if we use a parametrization, like
q, which refers to events that we never observe. The
q and
parametrization of acceleration are more general than the particular LCDM model and the fact that data prefers
is an important indication. Data lives in the light-cone, which corresponds to
rather than
q. At
the difference between a light-cone and space-like separations is very significant and any discrepancies in the data or model will show more pronounced in the
q modeling.
We conclude that the data shows some tensions with LCDM predictions (as indicated by q) but confirms that cosmic expansion is clearly decelerating (as indicated by ) so that events are trapped inside an Event Horizon ().