3. Decomposition in Modes and Stability
Einstein’s gravity is carried by a massless spin-2 field, the metric. Being represented by a symmetric matrix, a metric in four dimensions has 10 degrees of freedom (DOFs). These DOFs can be collected according to how they behave under spatial rotations, i.e., as scalars, vectors and tensors. There are then four scalars (4 DOFs), two divergence-free vectors (4 DOFs), and one traceless, divergence-free tensor (2 DOFs). However, only the tensor DOFs propagate; that is, they are subject to linearized equations of motion that are second-order in the time derivatives. The other DOFs obey constraint equations, fully determined by the matter content. This should have been expected, since a massless tensor field, like the gravitational field, has only two independent degrees of freedom.
The two propagating degrees of freedom are associated with the two polarizations
of the gravitational waves. To see that there are no other propagating DOFs, one can proceed by linearly expanding the metric around Minkowski
and keeping only scalar terms, i.e., functions that can be obtained from scalar or derivatives of scalars. The most general such metric is then
Inserting this metric into the Einstein–Hilbert Lagrangian without matter and developing it to a second order, one finds the second-order action in Minkowski space:
The linearly perturbed equations of motion can be obtained then by the Euler–Lagrange equations with respect to , but here we need only identify the degrees of freedom. When one varies the action with respect to B, one gets the constraint , which then shows that is not a propagating DOF. The same is true for , since there are no time derivatives for it. As we know, in fact, the potentials are determined by the matter distribution through two constraints, the Poisson equations, which do not involve time derivatives. Therefore, there are no scalar propagating DOFs in Einstein gravity without matter.
The same holds for the vector degrees of freedom. If one instead considers the tensor DOFs in
where, after imposing the traceless, divergence-less conditions, and considering a wave propagating in direction
,
one finds that the two modes
obey in vacuum the same gravitational wave equation,
, analogous to electromagnetic waves. GWs propagate therefore with speed
equal to unity.
The same procedure can be applied to the HL. One finds then in the absence of matter fields [
18,
22]
where
is the scalar mode perturbation,
represents the two tensor modes, and
represents their speed of propagation, respectively. As expected, HL has now three propagating DOFs, plus those belonging to the matter sector.
The four coefficients,
, depend on the HL functions. Their expression will be given in
Section 6. From the classical point of view, stability is guaranteed when
(with
) have the same sign. In fact, in this case, the equations of motion are well-behaved wave equations with speed
, whose amplitude is constant (or decaying in an expanding space), rather than growing exponentially as it would happen for
(gradient instability). For the quantum stability, however, one must also require
(or more exactly, the same sign of the kinetic energy of matter particles, assumed by convention to be positive), since otherwise the Hamiltonian is unbounded from below, which means particles can decay into lower and lower energy states, without limit, generating so-called ghosts. Therefore, for the overall stability of the theory, one requires
.
4. The Quasi-Static Approximation
In what follows, we put ourselves in Fourier space. That is, we replace every perturbation variable with a plane wave parametrized by the comoving wavevector , . Since we deal only with linearized equations, this simply means replacing every perturbation variable or their time derivative with its corresponding Fourier coefficient or its time derivative , and every space derivative of order n with . We drop from now on the k subscripts. We then assume that the so-called quasi-static approximation(QSA) is valid for the evolution of perturbations. This implies that we are observing scales well inside the cosmological horizon, , where k is the comoving wavenumber, and inside the Jeans length of the scalar, such that the terms containing k (i.e., the spatial derivatives) dominate over the time-derivative terms. For the scalar field, this means we neglect its wavelike nature and convert its Klein–Gordon differential equation into a Poisson-like constraint equation. If , the scales at which the QSA is valid correspond to all sub-horizon scales, which are also the observed scales in the recent universe. For models with , the QSA might be valid only in a narrow range of scales, or even be completely lost in the non-linear regime.
Let us explain in more detail the QSA procedure by using standard gravity as an example. Let us write down the perturbation equations for a single pressureless matter fluid in
CDM. From now on, we adopt the Friedmann–Lemaître–Robertson–Walker (FLRW) perturbed metric in the so-called longitudinal gauge, namely
If we use
as a time variable, such that
the coefficients of the perturbation variables become dimensionless, and we are left with [
23]
where, instead of the matter density
, we use
,
and where
, and
if
is the peculiar velocity, such that
. A glance at these equations tells us that, as an order of magnitude,
. Moreover, we assume
for every perturbation variable
(unless there is an instability, see below) and, consequently,
. Therefore, for
, the equations become
and one can derive the well-known second-order growth equation with dimensionless coefficients
The same QSA procedure can be followed for more complicated systems. When a coupled scalar field is present, its perturbation is of the same order as the gravitational potentials, .
The QSA says nothing about the background behavior. Additional conditions might be imposed: for instance, that the background scalar field slow rolls are such that the kinetic terms, proportional to the derivatives , are negligible with respect to the potential ones. This is indeed expected in order to produce an accelerated regime not too dissimilar from CDM; however, first, one can have acceleration driven by purely kinetic terms, and second, acceleration can be produced even with a significant fraction of energy in the kinetic terms. Therefore, slow-roll approximation and QSA should be kept well distinguished. However, in some formulas below, we will explicitly make use of the slow-roll approximation on top of the QSA.
Let us emphasize that the QSA applies only for classically stable systems. Imagine a scalar field obeying a second-order equation in Fourier space
where from now on we use the physical wavenumber
instead of the comoving one, and where
are the friction and the source, respectively, depending in general on the background solution and on other coupled fields. If
, the solution
will increase asymptotically as
, and in this case
will not be negligible with respect to
as we assumed in the QSA.
For simplicity, from now on we assume that the space curvature has been found to be vanishing, so
. Using Einstein’s field equations and a pressureless perfect fluid for matter, we can derive from the HL two generalized Poisson equations in Fourier space, one for
and one for
:
where
z is the redshift,
k the physical wavenumber,
the matter density contrast, and
and
Y are two functions of scale and time that parametrize deviations from standard gravity (we remind the reader that, in our units,
). In some papers, the function
Y is also called
. Comparing with Equations (12) and (13), we see that in Einstein’s general relativity they reduce to
. Clearly, the
anisotropic stress , or gravitational slip, is defined as
(From now on, all the perturbation quantities are meant to be root-mean-squares of the corresponding random variables and are therefore positive definite; we can therefore define ratios such as
.) A value of
can be generated in standard general relativity only by off-diagonal spatial elements of the energy-momentum tensor. For a perturbed fluid, these elements are quadratic in the velocity,
, and therefore vanish at first order for non-relativistic particles. Free-streaming relativistic particles can instead induce a deviation from
: this is the case of neutrinos. However, they play a substantial role only during the radiation era and are negligible today [
24]. Therefore,
in the late universe means that gravity is modified, unless there is some hitherto unknown abundant form of hot dark matter.
In the QSA, one can show that for HL [
17,
25]
for suitably defined functions
of time alone that depend only on
. Their full form will be given in
Section 6 along with another popular parametrization of the HL equations proposed in [
22]. In general, the functions
are proportional to
, where
is a mass scale. In the simplest cases,
corresponds to the standard mass
m, i.e., the second derivative of the scalar field potential, plus other terms proportional to
or
. These kinetic terms are expected to be subdominant if
drives acceleration today or, more in general, during an evolution that is not strongly oscillating, so often we can assume that
scale simply as
. This approximation will be adopted in the explicit expression for
and conformal coupling that are given below. If the scalar field drives the acceleration, one expects
m to be very small, of order
eV. In this case, at the observable sub-horizon scales,
and
. If instead this scale is of the order of the linear scales that can be directly observed (e.g., 100 Mpc), then one could observationally detect the
k-dependence of
and find that, at sufficiently large scale, such that
,
.
The same form of
can be obtained also in other theories not based on scalars that produce second-order equations of motion, namely, in bimetric models [
26] and in vector models [
27].
It is worth stressing the fact that the time dependence of
, expressed by the functions
, is essentially arbitrary. Given observations at several epochs, one can always design an HL that exactly fits the data, no matter how precise they are. In contrast, the space dependence, which in Fourier space becomes the
k dependence, is very simple and fixed. The reason is that the HL equations are by definition second-order, and therefore contain at most factors of
. The
k dependence is therefore potentially a more robust test for the validity of the HL than the time one. A model with two coupled scalar fields would instead generate for
a ratio of polynomials of order
(see, e.g., [
28]). Clearly, one has to remember that all this is valid at linear scales: if the
k dependence is important only at non-linear scales, e.g., for
Mpc
, then it might be completely lost.
Another equivalent form that we will employ often is
where
This form has a simple physical interpretation. is the modifier of the -Poisson equation, just as Y is the modifier of the -Poisson equation. The parameters are the strengths of the fifth-force mediated by the scalar field for (the metric time-time perturbed component) and for (the metric space-space perturbed component), respectively. Finally, m is the effective mass of the scalar field, and its spatial range. This interpretation will be discussed in the next section.
A particularly simple case is realized with the
models, where
is the function of the curvature
R that is to be added to the Einstein–Hilbert Lagrangian. In this case in fact,
The derivative is often negligible at the present epoch, in order to reproduce a viable cosmology. In this case, and, for large k, and , regardless of the specific model.
Another simple case is conformal scalar-tensor theory, with
,
, and
, where
. In this form, the strength of the fifth force is
. In this case, we have
where
. When
M is vanishingly small,
and
. Comparing with Equation (26), we see that, for
,
.
5. Potentials in Real Space
In real space, one can derive the modified Newtonian potential for a radial mass density distribution
by inverse Fourier transformation. Let us start with Equation (24):
For a
non-linear static structure (e.g., the Earth or a galaxy) the local density is much higher than the background average density, so
, where
is the background density, and
is the Fourier transform of
. The Poisson Equation (21) becomes then
In real space and for a radial configuration, this reads
where
is the inverse Fourier transform of
, and
V is an arbitrary large volume that encompasses the structure (since we use the physical
k,
r now refers to the physical distance). Assuming that
vanishes at infinity, Equation (31) has the general solution
where
and where
is the standard Newtonian potential, while
is the Yukawa correction proportional to
. This can be solved for any given radial density distribution
. For
(or
, we are back to the Newtonian case.
Let us focus now on the modified gravity part. This can be analytically integrated in some simple cases. We write
where
F has two parts
For a mass point at the origin, for instance, one has
where
is the Dirac delta function in 3D, defined for any regular function
as
; therefore,
i.e., the so-called Yukawa correction. The total potential is then
where we reintroduced for a moment Newton’s constant
. As anticipated,
gives the strength of the Yukawa interaction, and
its spatial range. The prefactor
renormalizes the product
, such that only the product
is then observable (besides
). Sometimes
is denoted
because it can be seen as a renormalization of Newton’s constant.
A typical dark matter halo can be approximated by a Navarro–Frenk–White profile [
29] with scale
and density parameter
,
In this case, we have [
30]
where
is the ExpIntegral function,
Exactly the same procedure can be applied to the second potential
, which obeys another Poisson equation
Notice that the mass
m is the same for
: there is only one boson, not two. The real-space expression for
for a point-mass
M is then identical to the one for
with
in place of
and
in place of
,
Finally, the so-called lensing potential
is responsible for the gravitational lensing of source images in the linear regime. In this regime, given an elliptical source at distance
characterized by semiaxes of angular extent
, the image we see is distorted by intervening matter into a new set of semiaxes
where the distortion matrix is proportional to
All observations of gravitational lensing lead therefore ultimately to an estimation of
. What is observed in practice is the power spectrum of ellipticities, i.e., the correlation of ellipticities of galaxies in the sky due to a non-zero
along the line of sight (see, e.g., [
31], chap. 10).
From Equations (20) and (21), we see then that
In our formalism, the lensing potential in real space amounts then to
where
Since is in general different from unity, the mass one infers at infinity from the potential (often called dynamical mass) is different from the mass that one infers from the potential and from the lensing combination , i.e., (lensing mass). These masses of course coincide in standard gravity. As we will see below, one can indeed compare observationally the estimations and extract by taking suitable ratios.
6. The Parameters of the Yukawa Correction
In [
22], it has been shown that the HL perturbation equations can be entirely written in terms of four functions of time only,
, given as
This parametrization (collectively called
) is linked to the physical properties of the HL. Briefly,
expresses the deviation of the GW speed from
c,
;
is connected to the field kinetic sector, and
to the mixing (“braiding”) of the scalar and gravitational kinetic terms;
is the time-dependent effective reduced Planck mass, and
its running. They are designed such that
for
CDM. They do not vanish, in general, for standard gravity with a non-
CDM background expansion, nor for non-standard gravity with a
CDM expansion. Several observational limits on these parameters in specific models have already been obtained (see, e.g., [
32]).
It is clear that cancellations can occur among terms belonging to different sectors. However, one should distinguish between dynamical cancellations, i.e., involving a particular background solution for , and algebraic cancellations, which only depend on a special choice for the functions . The former ones, if they exist at all and are not unstable, can be guaranteed only for some particular set of initial conditions, and might occur only for some period, unless the solution happens to be an attractor. The algebraic cancellations, however, are independent of the background evolution and therefore valid at all times. Therefore, usually only the second class is regarded as an interesting one.
We can now express the four coefficients introduced in Equation (8) that determine the stability of the HL as [
22]
where
and where
and
(with this last relation one can get rid of
everywhere). Here, “matter” represents all the components in addition to the scalar field, i.e., baryons, dark matter, neutrinos, and radiation. The matter equation of state
is then an effective value for all the matter components. Note that
in the standard minimally coupled scalar field case
, and
.
The relation between the “observable” parameters
that enter the Yukawa correction and the “physical” parameters
is
where
(With respect to the mass defined in [
22], we have
.)
Two remarks are in order. First, the quantity acts as an effective squared mass in the perturbation equation of motion for ; we need to assume therefore that it is non-negative to avoid instability below some finite value of k. Second, the expressions for and are completely general and do not assume the QSA. The QSA is needed only when we connect the theory to observations through .
Considering now only pressureless matter, from the background equations in the
Appendix A, we see that,
where
. In a
CDM background,
, and
simplifies to
. Notice that
does not appear in the
-
relation: this means that the kinetic parameter
is not an observable in the QSA linear regime. In
Section 13, we will discuss which combinations of
are model-independent (MI) observables in cosmology.
Assuming Einstein–Hilbert action for the gravitational sector and a canonical kinetic term for the scalar field, we have
and
, so
and
Therefore,
and
so that, as per construction,
.
It is worth noticing that the stability conditions
imply
and therefore
if one also requires
. As we have seen,
is the range of the fifth-force interaction, so it makes sense that it is positive definite for stable systems. In the standard Brans–Dicke model with a potential
, for instance, and neglecting several subdominant kinetic terms, we have
where
; therefore, finally,
where
(notice that in Brans–Dicke
has dimensions
mass, and
is therefore dimensionless), so the fifth-force range is
Assuming a
CDM expansion and
, the conditions for stability during the matter era simplify to
and
Generalizing, we have that for a background parametrized by a (possibly time-dependent) EOS
and for matter with an effective
, one has
To these stability conditions, arising from Equations (60) and (61), one should add the requirement that the friction term in the perturbation equations for , or equivalently, for the gravitational potentials , is positive. This condition is quite milder than those from Equations (60) and (61). While a negative , for instance, even for a short period, induces a unbounded growth for , a negative friction term typically leads to a power-law growth , which might be a problem only if it lasts for too long. However, in order to obtain the friction instability condition, one should carefully investigate the existence of growing modes also when the various coefficient are time-dependent and no simple criteria have been identified so far. Therefore, we just quote the condition for negative friction (i.e., stability) for the gravitational waves, best obtained by writing down the equation in conformal time, since in this case the term is time-independent (provided ). The condition is simply .
From the
relations (64), we can derive the Yukawa strengths
The Yukawa strength
is always positive, so the fifth force is attractive if
. We also notice that if
, then
and the two strengths become equal, and
. Therefore,
, and, finally,
, even if both potentials do actually have a non-vanishing Yukawa correction, such that
. In order for the parameters
to vanish, the gravity sector of the HL must be standard,
, barring the case of accidental dynamical cancellation for some particular background evolution. Therefore, we conclude that
implies, and is implied by, modified gravity, at least when matter is represented by a perfect fluid [
33]. One cannot make a similar statement for
Y. This is a crucial statement for what follows. Notice, however, that, as we show below, although modified gravity implies
, a value
does not necessarily imply standard gravity, but only scale-free gravity, at least at the quasi-static level. In [
34], it has been shown that
at all scales implies indeed standard gravity.
We can draw more conclusions from Equations (79).
The two strengths are equal also if . In this case, and has no scale dependence.
The
limit of the modified gravity parameters (provided we are still in the linear regime) is
This coincides with Equation (4.9) of [
22]. If
, then
It turns out that, if one imposes stability,
, then
Y is always larger than, or equal to,
, such that matter perturbations in Horndeski with
always grow faster, in the quasi-static regime, than any standard gravity model with the same
and the same background. It also follows that the lensing combination that appears in Equation (52) amounts to
Since the denominator has to be positive for stability, the sign of the effect on the gravitational lensing depends only on .
The Yukawa corrections disappear completely if
, i.e., for
This is therefore the general condition to have a scale-free gravity, corresponding to
(we recently noticed that this relation was first provided in an unpublished draft by Mariele Motta in early 2016). If we also assume
and consequently
(
conformal coupling) in the HL, as required by the GW speed constraints we discuss in
Section 8, it follows that
[
35,
36] (note that in [
35]
is defined as our
), and that
which gives an algebraic cancellation for
and
. In this particular model, the local gravity experiments would not detect a Yukawa correction, even if gravity actually couples to the scalar field. Gravity then becomes
scale free. The Planck mass would still vary with time, however. Therefore, in this model,
even if gravity is actually modified. Assuming a
CDM background, for this model to be stable,
implies the condition
. For
constant or slowly varying, the stability condition amounts to
, so
; therefore,
Y, or the effective Newton’s constant, will decrease with time. A larger
Y in the past means faster perturbation growth for the same
. Once again, however, since
is not an MI observable quantity, whether this means that perturbations grow faster than in
CDM or not is a model-dependent statement.
From Equation (52), we find also that the lensing potential lacks a Yukawa term whenever
, defined in (54), i.e.,
, which amounts to
We then see that
, not only when
but also for
. Again imposing the GW speed constraint, this becomes
. On the HL functions, this implies
which actually means that the
sector, after an integration by parts, can be absorbed in
. Therefore, for the conformal coupling and when the
term is absent or does not depend on
X, the lensing potential becomes simply twice the standard Newtonian potential
This means that radiation, being conformally invariant (the electromagnetic Lagrangian does not change for ), does not feel the modification of gravity, except for the overall factor , which, if time-dependent, induces a time-dependent mass or Newton’s constant.
In the same case as above,
and
, one has
which becomes
when the kinetic component
is small. Similarly,
. For
, one obtains a Yukawa strength of
for the
potential. This case is exactly realized for the
models.
Finally, in the uncoupled case , in which only the kinetic sector of the scalar field is modified, one has that , such that there is a Yukawa correction, but at all quasi-static scales.
7. Local Tests of Gravity
Gravity has been tested for a long time in the laboratory and within the solar system (see, e.g., [
37]). The generic outcome of these experiments is that Einsteinian gravity works well at all of the scales that have been probed so far. In many experiments one assumes the existence of the same type of “fifth-force” Yukawa correction to the static Newtonian potential predicted by the HL model,
(Here we drop the subscript from
since we need to consider only
; moreover, any overall parameter can be absorbed in
.) Current limits on
and
have been obtained in a range of scales from micrometers to astronomical units. The constraints on the strength
obviously weakens for very small
. To give an idea, at the smallest scales probed in the laboratory, one has [
38]
at
m and
at
m (Casimir-force experiments probe even shorter scales, but the constraints on
become correspondingly weaker). At planetary scales, one has
for
m (Earth–Moon distance), and
at
m (planetary orbits). Beyond this distance, the constraints from direct tests of the Newtonian
potential weaken again.
However, the scalar field responsible for the Yukawa term induces also two post-Newtonian corrections to the Minkowski metric. For a mass distribution with velocity field
and density distribution
, we define
U as the potential that solves the standard Poisson equation for non-relativistic particles, i.e., [
37]
and
as a velocity-weighted potential
We can then write the parametrized post-Newtonian metric as follows:
(The full post-Newtonian metric includes several other terms that are not excited by a conformally coupled scalar field, see, e.g., [
2]). Clearly,
produces the standard weak-field metric. Taking the extreme case of
, one has
where
. The parameter
can be seen as the local-gravity analogue of the anisotropic stress
, both being the ratio of
at a linear level.
Local tests of gravity can, therefore, measure the Yukawa correction for both
, i.e.,
and
, and the ratio
, in a model-independent way. The parameter
, for instance, is constrained to be less than
[
39], inducing a similar constraint on
at large scales. A similar constraint applies also to
. With such a small strength, there would hardly be any interesting effect in cosmology.
However, all these tests are performed within a limited range of scales, both spatial and temporal. Moreover, the tests are performed with (some of) the standard matter particles and not with, say, dark matter. Therefore, they are completely escaped if standard model particles do not feel modified gravity, for instance, because the scalar field that carries the modification of gravity does not couple to them or because of screening effects, as we discuss next.
So far we have considered only linear scales. At strongly non-linear scales, e.g., in the galaxy or in the solar system, the effects of modified gravity depend on the actual configuration of the scalar field. If such a configuration is static and homogeneous within a scale
, then the effects of modified gravity can be screened within
, since they are proportional to the variation of
. This is the so-called chameleon effect [
40,
41]. On the other hand, screening can occur also because of non-linearities in the kinetic part of the Klein–Gordon equation: this is the Vainshtein effect [
42,
43]. Finally, a third mechanism appears if the coupling
sets on a vanishing value in structures (high density regions), via a symmetry restoration, while being different from zero at the background (low density) [
44,
45,
46,
47]. In all cases, the strong deviation from standard gravity that we might see in cosmology are no longer visible by local experiments. In this sense, one can always build models that escape the local gravity constraints. This can be achieved also by assuming that the baryons are completely decoupled from the scalar field.
In light of these arguments, let us consider for instance in more detail the constraint on
associated with the big bang nucleosynthesis (BBN), sometimes quoted as one of the most stringent cosmological bound. The yields of light elements during the primordial expansion depends on both the baryon-to-photon constant ratio
and the cosmic expansion rate during nucleosynthesis, which in turn depend on
at that time and on various standard model parameters. Fixing the standard model parameters and estimating
by CMB measurements, one can find constraints on
[
48] by comparing the predicted abundances with the observed ones, for instance deuterium in quasar absorption systems. This means that
at nucleosynthesis was close to
on Earth today. The easiest explanation, which is that
did not vary at all or at least in any way less than 0.2 throughout the expansion, implies
(equal to
in
CDM), where
is the cosmic age. However,
in the solar system might be screened, as we have mentioned, and therefore equal to the “bare”
of standard gravity. Therefore, any model which is standard general relativity in the early universe, like essentially all models built to explain present day’s acceleration, will automatically pass the BBN constraint. Moreover, one should notice that this constraint depends on an estimate of
from CMB that assumes
CDM. Additionally,
is, in fact, degenerate with the number
of relativistic degrees of freedom at nucleosynthesis, such that the bound applies to
rather than to
alone. Finally, a simultaneous change in the other standard-model parameters might considerably weaken the constraint (see [
49,
50]).
8. The Impact of Gravitational Waves
The Horndeski model predict an anomalous propagation speed
for gravitational waves (or rather,
), since the scalar field is coupled in a non-conformal way. As already mentioned, one has [
25,
51],
The almost simultaneous detection of GWs and the electromagnetic counterparts tells us that, within 40 Mpc (at
) from us, GWs propagate essentially at the speed of light [
3]. Since the signals arrived within a 1s difference and since the light took
s to reach us, we have that
. Such a tight constraint immediately ruled out most of the scalar-tensor theories containing derivative couplings to gravity or at least those models which show this effect in the nearby universe (in cosmological scales) [
35,
52,
53,
54,
55,
56]. That is, we need to have
and
. In other words, the surviving Lagrangian has an arbitrary
but a vanishing
and an
X-independent
. This kind of Lagrangian is just a form of Brans–Dicke gravity (plus a scalar field potential and a non-canonical kinetic term). It is also equivalent to standard gravity with matter conformally coupled to a scalar field, i.e., coupled to a metric
. A dynamical cancellation among the terms depending on
and
appears extremely fine-tuned. A possible way out is to design a model with an attractor on which the conformal coupling holds, as proposed in [
57]. In this case, after the attractor is reached, we measure
, but this does not have to be true in the past. Deviations from the speed of light in the past could be detected in B-mode CMB polarization [
58].
The constraints on
also affect directly
. From Equation (65), one has in fact
Hence, the GW constraint
implies that
should also be equal to unity for sufficiently large scales (small
k) [
59]; i.e., it should recover its general relativity value. The obvious exception are theories
without a mass scale in addition to the Planck mass [
60], in which case
at all scales. On the other hand, no obvious GW constraint affects
Y.
Gravitational waves might in principle measure another HL parameter: the running of the Planck mass,
. In fact, as it has been shown, for instance, in [
33], the GW amplitude
h obeys the equation
Assuming
, this equation in the sub-horizon limit is solved by [
61]
where the prefactor is the ratio of the Planck mass values at emission and at observation, and
is the standard amplitude expression that, for merging binaries, can be approximated as (see, e.g., [
62], Equation (4.189))
Here, is the luminosity distance, the so-called chirp mass, and the GW frequency measured by the observer.
GWs in standard gravity can measure the luminosity distance
because the chirp mass and the frequency can be independently measured by the interferometric signal. In modified gravity, what is really measured is therefore a GW distance [
61,
63,
64]
Comparing this with an optical determination of leads to a direct measurement of at various epochs, and therefore of .
It is, however, likely that both the emission and the observation occur in heavily screened environments. In this case, is the same at both ends, and no deviation from would be observed. If emission occurs in a partially unscreened environment, then one should see instead some deviation, although not necessarily connected to the cosmological, unscreened, value of .
9. Model Dependence
The standard model of cosmology,
CDM, is amazingly simple. It consists of a flat, homogeneous, and isotropic background space with perturbations that, at scales above some Megaparsec, have been evolving linearly until recently. The initial conditions for perturbations are set by the inflationary mechanism and provide an initially linear and scale-invariant spectrum of scalar, vector, and tensor perturbations, i.e., power-law spectra
, where
x stands for the three types of perturbations that can be excited in general relativity. These are encoded in a spin-2 massless field that mediates gravitational interactions via Einstein’s equations. The energy content is shared among relativistic particles (photons) as well as quasi-relativistic particles, neutrinos, pressureless “cold” dark matter particles, standard model particles (“baryons”), and a cosmological constant. The density of photons can be directly measured via the CMB temperature: it amounts to
; the density of neutrinos depends on their mass and is known to be less than 1% of the total content today. Therefore, today, only the last three components are important. The density of baryons can be fixed by the primordial BBN [
65]. Since the space curvature has been measured (although so far only in a model-dependent way) to be negligible, only a single parameter is left free: the present fraction of the total energy density in pressureless matter,
. The fraction in the cosmological constant is then
.
With this one free parameter, the fraction of energy in the cosmological constant, , CDM fits all the current cosmological data: the cosmic microwave background (CMB), the weak lensing data, the redshift distortion data (RSD), and the distance indicators (supernovae Ia, SNIa; baryon acoustic oscillations, BAOs; cosmic chronometers, CCH; gravitational waves, GW).
There are indeed a few discrepancies. In particular, two seem to be more robust. The first is the value of
obtained through local measurements, in particular through Cepheids,
km/s/Mpc [
66], independent of cosmology, which deviates from the Planck [
67] value obtained through extrapolation from the last scattering epoch performed assuming
CDM,
km/s/Mpc [
67]. The second one is the level of linear matter clustering embodied in the normalization parameter
: here again, the value from CMB (
[
67] differs from the late-universe value delivered by weak lensing,
[
68] and by RSD data [
69],
.
Another source of discrepancies is related to the dark matter clustering [
70]. Dark-matter-only simulations fail at reproducing some of the observed properties of the DM distribution. Although the inclusion of baryon physics may solve this, so far there is no conclusive statement, and some of these issues may in fact be due to a modification of gravity.
These conflicting results already display a basic problem of cosmological parameter estimation, namely the fact that it is very often model-dependent. The Planck satellite estimates of the cosmological parameters, from
to
h, from the equation of state of dark energy
to the clustering amplitude
, can be obtained only by assuming, among others, a particular model of initial conditions (inflation) and of later evolution (
CDM). For instance, if we assume
instead of the cosmological constant value
, one obtains
km/sec/Mpc ([
67], Figure 27), outside the error range given above.
Another example of model-dependency comes from distance indicators and the dark energy equation of state. Cosmological distance indicators, whether based on SNIa, BAOs, or otherwise, basically measure the comoving distance
where
is the present amount of spatial curvature
k expressed as a fraction of total energy density. We see that
depends only on
and
. However, since distance indicators depend on the assumption of a standard candle or ruler or clock, whose absolute value we do not know, the absolute scale of
, i.e.,
, cannot be measured (except for “standard sirens”, i.e., gravitational waves [
71]). Assuming for simplicity that
, the only direct observable is
. If we also neglect radiation (a very good approximation for observations at redshift less than a few) and assume that, besides pressureless matter, we have a dark energy component with EOS
, we have
where
We can then invert the Relation (107) and obtain
where
means differentiation with respect to redshift. It appears then that, in order to reconstruct
, one needs to know
, in addition to
. For instance, if the true cosmology were
CDM with
and we assumed erroneously that
, we would infer
and
, which is much different from the true value
.
The problem is that
is not a model-independent observable. Whenever an estimate of
is given, e.g., from CMB or lensing or SNIa, it always depends on assuming a model. The reason is that there is no way, with phenomena based on gravity alone (clustering and velocity of galaxies, lensing, integrated Sachs–Wolfe, etc.), to distinguish between various components of matter, since matter responds universally to gravity, unless one breaks the equivalence principle (see the “dark degeneracy” of [
72]). Therefore, to measure
, one has to assume a model, i.e., a parametrization, with extremely precise measurements. For instance, if
, then we reduce the complexity to just two parameters, and a measurement of
at at least three different redshifts can simultaneously fix
. Without a parametrization,
cannot be reconstructed. With a parametrization, the result depends on the parametrization itself.
On the other hand, it is clear that we can always perform null tests on , as for most other cosmological parameters. That is, we can assume a specific , e.g., , and test whether it is consistent with the data. In this case, in flat space, one needs just three distance measurements at three different redshifts, since there are only two parameters, and . If the system of three equations in two parameters has no solution, the CDM model is falsified. While it is relatively easy to test, i.e., falsify, a model of gravity, it is much more complicated to measure the properties of gravity in a way that does not demand too many assumptions. This explains why the title of this paper mentions “measuring”, and not “testing”, gravity.
The rest of the paper will discuss what kind of model-independent measurements we can perform in cosmology, with emphasis on parameters of modified gravity. As is obvious, one cannot claim absolute model independence. The point is rather to clearly isolate the assumptions, and see how far can one reach with a minimum amount of them. In the following, we will assume. the following:
(a) the universe is well-described by a homogeneous and isotropic geometry with small (linear) perturbations;
(b) gravity is universal;
(c) standard model particles behave from inflation onwards in the same way as we test them in our laboratories;
(d) dark matter is “cold”.
One can replace the last statement with the assumption that we know the equation of state and sound speed of dark matter, provided it is not relativistic and that the fluid remains barotropic, i.e., , as we will show later on. Unless otherwise specified, however, for the rest of this work, we assume pressureless, cold dark matter.
Notice that we are not assuming any particular form of gravity, standard or otherwise: in fact, we refer to “gravity” as to one or more forces that act universally and without screening, at least beyond a certain scale. Therefore, we include in our treatment gravity plus at least one scalar, vector, and tensor field. Later on, we will use the Horndeski generalized scalar-tensor model for a specific example, but the methods discussed here are not restricted to this case.
10. Model-Independent Determination of the Homogeneous and Isotropic Geometry
What we observe in cosmology are redshifts and angular positions of sources. However, we need to build models for and test distances. Can we convert redshifts and angles into distances in an MI way? If this turns out not to be possible, then there is no reason to continue our investigation to the perturbation level. Fortunately, it appears we can.
The FLRW metric of a homogeneous and isotropic universe in spherical coordinates is
where
is the scale factor normalized at present time to
. If we measure
in units of the natural scale length
, the metric can be rewritten as
The value of
has been estimated by Planck to be extremely small,
([
67], Table 5, last column), but, again, this is a model-dependent estimate, and for now we consider it as a free parameter. We see that, up to an overall scale, the FLRW metric depends only on
and on
, from which
is obtained by inverting
where again
t is in units of
.
BAOs are the remnant of primordial pressure waves propagating through the plasma of baryons and photons before their decoupling. By assumption (
, we assume their interaction at all times is the same as in our laboratories. Therefore, we can predict that the comoving scale of the BAO today is a constant
R independent of the redshift at which it is observed. For instance, in
CDM,
R (in units of
) is equal to
where the indexes
refer to radiation, baryons, and dark matter, respectively; moreover,
,
is the redshifts of the
drag epoch (see the numerical formula given in [
73]), and
is the redshift at equivalence. The value
R can be used as a standard ruler: as for SNIa, we do not need to know
R; we need only to assume that it is constant. Therefore, we can search in the clustering of galaxies for such a scale, in particular by identifying a peak in the correlation function. The angle under which we observe
R gives us the “transverse BAO”. In turn, this angle gives us the dimensionless angular diameter distance
The correlation function, however, depends both on the angle between sources and on their redshift difference. That is, one can observe also a “longitudinal BAO” scale, which, for a small redshift separation
, amounts to
This means that BAOs can estimate at every redshift two combinations involving
and
and therefore determine both in an MI way. Therefore, the FLRW metric can in principle be reconstructed within the range covered by BAO observations, without assumptions in addition to (
a). Clearly, SNIa and other distance indicators can contribute to the statistics, but do not offer information on alternative combinations of cosmological parameters. Once we have the FLRW metric, the redshifts and angles can be converted to distance by solving
. Given two sources at redshifts
separated by an angle
, their relative distance
is [
74]
where the comoving distance
is defined in (106). The background geometry is then recoverable in an MI way. However, this is not a test of gravity.
We move then to the next layer: perturbations.
11. Measuring Gravity: The Anisotropic Stress
We have seen that the gravitational slip
is defined as the ratio between the two gravitational potentials
The lensing potential
is the combination that exerts a force on the relativistic particles (i.e., for our purposes, light), while
exerts a force on non-relativistic particles (i.e., for our purposes, galaxies). The explicit form of the equation of motion for a generic particle moving with velocity
and relativistic factor
in a weak-field Minkowski metric is in fact [
75]
For small velocities, only the last term on the rhs survives; for relativistic velocities, only the square bracket term. This means that, in order to test gravity at cosmological scales, we need to combine observations of lensing and of the clustering and velocity of galaxies.
The linear gravitational perturbation theory provides the growth of the matter density contrast
at any redshift
z and any wavenumber
k, given a background cosmology and a gravity model. It is convenient to also define the growth function
and the growth rate
where, as usual, the prime stands for derivative with respect to
.
However, what we observe is the galaxy number density contrast in redshift space, usually expressed in terms of the galaxy power spectrum as a function of wavenumber
k and redshift,
. Since galaxies are expected to be a biased tracer of mass, we need to introduce a bias function
that, in general, depends on time and space (that is, on
). If
, then the number density of galaxies in a given place is proportional to the amount of underlying total matter,
. If
(
), then galaxies are more (or less) clustered than matter. Moreover, since we observe in redshift space, which means we observe a sum of cosmic expansion and the radial component of the local peculiar velocity, to convert to real space, we need the Kaiser transformation [
76], which induces a correction factor
that depends on the cosine
of the angle between the line of sight and the wavevector
.
This means that the relation between what we observe, namely the galaxy power spectrum in redshift space, and what we need to test gravity, namely
, can be written as [
77]
where
where
is the root-mean-square matter density contrast today. (
are mnemonics for amplitude and redshift, respectively.) With this definition,
is normalized as
where
is the window function for an 8
Mpc sphere, and
. Sometimes one defines
, which is then normalized to unity.
can be referred to as the shape of the present power spectrum. Equation (122) shows that
are the only two observables one can derive from linear galaxy clustering. This dataset is often collectively called redshift distortion (RSD).
There is then a third observable that one can obtain from weak lensing. From Equation (52), we see that by estimating the shear distortion, one can measure the quantity
Since
can be estimated independently, we define another observable, to be denoted
L [
25], as follows:
Together with
, the quantities
are the only cosmological information one can directly gather at the linear level (as we have seen,
is also a direct observable, but for simplicity, we have assumed that is negligible at all relevant epochs). Other observations, like the integrated Sachs–Wolfe or velocity fields, only give combinations of
, rather than new information. A direct measurement of the peculiar velocity field and its time derivative, for instance, would produce through the Euler Equation (10) an estimation of the combination
; however, this is equivalent to
. At least at the linear level, one could add more statistics, but will always end up with these four quantities rather than, say, a direct estimate of
or
Y. A preliminary non-linear analysis [
78] shows that, employing higher-order statistics, we can obtain more MI information, but we will not consider this here.
We can now write the lensing equation in Fourier space in the following way (see [
79]):
where
. The linearized matter conservation equations, i.e., the continuity equation and the Euler equation, can be combined in a single second-order equation,
which depends only on the pressureless assumption (
d) and not on the gravitational model. In terms of our observational variables and for slowly varying potentials, this becomes
These equations show clearly that lensing and matter growth can measure some combination of
and their derivatives, as will be seen explicitly below. For now, let us just rewrite Equation (129), employing also Equation (21) as
We see then that Y is not, unfortunately, an MI quantity. Even if we have precise information on , we would still need, at any , the combination , which is not an observable. Only a null test of standard gravity plus a specific cosmological model, say CDM, is possible: in this case in fact, , and are known, and we have that is uniquely measured by a combination of . Any two measures at different k or z values must then give the same . We show below that , in contrast to Y, is an MI quantity.
Although
might be interesting statistics on their own, our goal here is to test gravity. Now, the bias function depends on complicated, possibly non-linear and hydrodynamical processes; thus, even if
b depends on gravity, we do not know how. Additionally, the shape
of the power spectrum depends on initial conditions (inflation) and, possibly, on processes that distorted the initial spectrum during the cosmic evolution. In fact, even if we could exactly measure the power spectrum shape from CMB without a parametrization such as
or its “running”, nothing precludes the possibility that an unknown process, for instance the presence of early dark energy or early modified gravity, has distorted the spectrum at some intermediate redshift between the last scattering and today. Therefore, in order to obtain model-independent measures, we should eliminate both
b and
. It was shown in [
25,
79] that one can obtain only three statistics where the effects of the shape of the primordial power spectrum is canceled out, namely
In the last equation, we introduced the often-employed quantity
Notice that we are not defining as an integral over the power spectrum at z, as in Equation (124), because we are interested in the k-dependence. These quantities depend in general on in an arbitrary way. Every other ratio of or their derivatives can be obtained through or their derivatives.
Let us discuss the three statistics in turn. The first quantity, , often called in the literature, contains the bias function. Since we do not know how to extract gravitational information, if any, from the bias, we do not consider it any longer.
Concerning
, we notice that, although related, what is observed is
R and not
. In order to determine the latter from the observable
R, one has to assume a value of
(typically chosen to be given by
CDM), such that it is not a model-independent observable. One could imagine that
alone is instead a direct test of gravity, since it depends only on
f. However, to predict the theoretical value of
R (or
f) as a function of the gravity parameter
Y from Equation (130), one needs to choose a value of
and the initial condition
at some epoch
for every
k. In almost all the papers on this topic since [
80], this initial condition is assumed to be given by a purely matter-dominated universe at some high redshift (this is, for instance, how the well-known approximated formula
is obtained). However, in models of early dark energy or early modified gravity, this assumption is broken. Therefore, once again,
alone cannot provide an MI measurement of gravity. Exactly as we have seen for the dark energy EOS
, if one parametrizes
with a sufficiently small number of free parameters, then the RSD data alone, which provide
, can fix both
and
.
We can also see that
is trivially related to the
statistics, whose expected value at a scale
k is (see [
81] and references therein)
In
CDM and with Planck 2015 parameters, its present value is
. With our definitions, the relation with
is given by
The
statistics has been used several times as a test of modified gravity [
81,
82,
83,
84]. However, it is not
per se a model-independent test. In fact, the theoretical value of
depends on
and on
f. As already stressed,
is not an observable quantity. Moreover, the growth rate
f is estimated by solving the differential equation of the perturbation growth, and this requires initial conditions and
Y. As a consequence of this, when we compare
to the predicted value (131), we can never know whether any discrepancy is due to a different value of
, to different initial conditions, or to non-standard modified gravity parameters
. As previously shown, one can employ
only to perform a null test of standard gravity plus
CDM, or other specific models. This is, of course, a task of primary importance, but is different from measuring the properties of gravity in a model-independent way.
In contrast, we can define MI statistics to measure gravity, in particular the parameter
by combining the equation for the growth of structure formation, Equation (129), with the lensing Equation (127) and with Equations (14) and (21). We see then that the gravitational slip as a function of model-independent observables is given by
In order to distinguish the observables from the theoretical expectations, we denoted the combination on the lhs of this equation as
. The statistics
is model-independent because it estimates
directly without any need to assume a model for the bias, nor to guess
or
, nor to assume initial conditions for
f. Therefore, if observationally one finds
1, then
CDM and all of the models in standard gravity and in which dark energy is a perfect fluid are ruled out. As a consequence, cautionary remarks such as those in [
85], namely, that their results about
cannot be employed until the tension between
in different observational dataset is resolved, do not apply to
. The price to pay is that Equation (137) depends on derivatives of
E and, through
, of
. Derivatives of random variables are notoriously very noisy. In the next sections, we will compare several methods to extract the signal.
If we abandon the linear regime then, of course, new observables can be devised, see e.g., [
78]. One interesting case is provided by relaxed galaxy clusters, for which we can reasonably expect that the virial theorem is at least approximately respected. In this case, we can directly measure the potential
by the Jeans equation, i.e., the equilibrium equation between the motion of the member galaxies and the gravitational force (note that the potential remains linear for galaxies and clusters, even for a non-linear distribution of matter). The lensing potential can instead be mapped through weak and strong lensing of background galaxies. In this case, one can gather much more information on the modified gravity parameters than in the linear regime [
30]. However, the validity of this approach relies entirely on two important assumptions. First, we must assume the validity of the virial theorem, which can be more or less reasonable, but cannot be proved independently. Second, since we have access only to the radial component of the member galaxy velocities, we must assume a model for the velocity anisotropy, i.e., how the other components are distributed within the cluster.
Concluding this section, we recap and emphasize the main points. are the only independent linear observables in cosmology. The ratios are independent of the initial conditions (i.e., of the power spectrum shape). are also independent of the galaxy bias. The combination is, therefore, a model-independent test of gravity: it does not depend on the bias, on initial conditions, nor on other unobservable quantities such as and . If , gravity is not Einsteinian; if does not have the same dependence as the Horndeski’s theory, the entire Horndeski model is rejected. All this, of course, assumes that our conditions (a)–(d) are verified.
14. Data
In the next sections, we obtain an estimate of
using all the currently available data (This section and the next two are a summary of a published paper by A. M. Pinho, S. Casas, and L. Amendola, entitled Model-Independent Reconstruction of the Linear Anisotropic Stress
, arXiv:1805.00025, JCAP11(2018)027). The first step is to reconstruct
(and therefore
),
, and
using all the currently available relevant data, shown in
Figure 1, where we also plot the
CDM the curves of the different functions using the cosmological parameters from the TT+lowP+lensing Planck 2015 best-fits [
67]. A similar analysis, with a much smaller dataset than is available, was carried out also in [
86].
For the Hubble parameter measurements, we have used the most recent compilation of
data from [
87], including the measurements from [
88,
89,
90,
91], the Baryon Oscillation Spectroscopic Survey (BOSS) [
92,
93,
94], and the Sloan Digital Sky Survey (SDSS) [
95,
96]. In this compilation, the majority of the measurements were obtained using the cosmic chronometric technique. This method infers the expansion rate
by taking the difference in redshift of a pair passively-evolving galaxies. The remaining measurements were obtained through the position of the BAO peaks in the power spectrum of a galaxy distribution for a given redshift. For this case, the measurements from [
92] and [
93] are obtained using the BAO signal in the Lyman-
forest distribution alone or cross-correlated with quasi-stellar objects (QSOs) (for the details of the method, we refer the reader to the original papers). The reference [
96] provides the covariance matrix of three
measurements from the radial BAO galaxy distribution. To this compilation, we add the results from WiggleZ [
97]. In addition to these, we use the recent results from [
98] where a compilation of type Ia supernovae from CANDELS and CLASH Multi-cycle Treasury programs were analyzed, yielding a few tight measurements of the expansion rate
.
The
data include the results from KiDS+2dFLenS+GAMA [
85], i.e., a joint analysis of weak gravitational lensing, galaxy clustering, and redshift space distortions. We also include image and spectroscopic measurements of the Red Cluster Sequence Lensing Survey (RCSLenS) [
99], where the analysis combines the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS), the WiggleZ Dark Energy Survey, and the Baryon Oscillation Spectroscopic Survey (BOSS). The work of VIMOS Public Extragalactic Redshift Survey (VIPERS) [
84] is also accounted for in our data. The latter reference uses redshift-space distortions and galaxy–galaxy lensing.
These sources provide measurements in real space within the scales
h
Mpc and in the linear regime, which is the one in which we are interested. They have been obtained over a relatively narrow range of scales
, meaning that we can consider them relative to the
-th Fourier component, as a first approximation. In any case, the discussion about the
k-dependence of
is beyond the scope of this work, so the final result can be seen as an average over the range of scales effectively employed in the observations. Moreover, in the estimation of
, based on [
81], one assumes that the redshift of the lens galaxies can be approximated by a single value. With these approximations, indeed
is equivalent to
; otherwise,
represents some sort of average value along the line of sight. We caution that these approximations can have a systematic effect both on the measurement of
and on our derivation of
. In future work, we will quantify the level of bias possibly introduced by these approximations in our estimate.
Finally, the quantity
is connected to the
parameter. Our data include measurements from the 6dF Galaxy Survey [
100], the Subaru FMOS galaxy redshift survey (FastSound) [
101], WiggleZ [
97], the VIMOS-VLT Deep Survey (VVDS) [
102], the VIMOS Public Extragalactic Redshift Survey (VIPERS) [
84,
103,
104,
105], and the Sloan Digital Sky Survey (SDSS) [
96,
106,
107,
108,
109,
110,
111,
112]. The values from [
113,
114] will not be considered since the
value is not directly reported.
15. Reconstruction of Functions from Data
The only difficulty in obtaining is that we need to take the ratios at the same redshift, while we have data points at different redshifts, and that we need to take derivatives of and . This essentially means we need to have a reliable way to interpolate the data to reconstruct the underlying behavior.
There is no universally accepted method to interpolate data. Depending on how many assumptions one makes regarding the theoretical model, e.g., whether the reconstructed functions need just to be continuous, or smooth, depending on few or many parameters, etc., one obtains unavoidably different results, especially in the final errors. Here, we consider and compare three methods to obtain the value of : binning, the Gaussian process (GP), and generalized linear regression.
The first, and simplest, method assembles the data into bins. This consists of dividing the data into a particular redshift interval (bin), and for each of these intervals one calculates the average value of the subset of the data contained in that bin. The corresponding redshift and error of each bin are computed as weighted averages.
Another way to reconstruct a continuous function from a dataset is by using a Gaussian process algorithm as explained in [
115]. This process can be regarded as the generalization of Gaussian distributions to function space since it provides a distribution over functions instead of a distribution of a random variable. Considering a dataset
, where
represents deterministic variables and
random variables, the goal is to obtain a continuous function
that best describes the dataset. A function
f evaluated at a point
x is a Gaussian random variable with mean
and variance
. The
values depend on the function value evaluated at other
points (particularly if they are close points). The relation between these can be given by a covariance function
. The covariance function
is in principle arbitrary. Since we are interested in reconstructing the derivatives of the data, a Gaussian covariance function expressed as
is the chosen function since it is the most common and has the least number of additional parameters. This function depends on the hyperparameters
and
ℓ, which allow us to set the strength of the covariance function. These hyperparameters can be regarded as the typical scale and change in the
x and
y direction. The full covariance function takes the data covariance matrix
C into account by
. The log likelihood is then
where
is the determinant of
. The distribution Equation (146) is usually sharply peaked and so we maximize the distribution to optimize the hyperparameters, although this is an approximation to the marginalization process and it may not be the best approach for all datasets. We employ the Python publicly available GaPP code from Seikel et al. (2012) [
116].
As a third method, we use a generalized linear regression. Let us assume we have
N data
, one for each value of the
independent variable
and that
where
are errors (random variables) which are assumed to be distributed as Gaussian variables. Here,
represents theoretical functions that depend linearly on a number of parameters
:
where
are functions of the variable
, chosen to be simple powers, and
, such that
represents polynomials of order
n.
The order of the polynomial is in principle arbitrary, up to the number N of datapoints. However, it is clear that, with too many free parameters, the resulting will be very close to zero, i.e., statistically unlikely. At the same time, too many parameters also render the numerical Fisher matrix computationally unstable (producing, e.g., a non-positive definite matrix) and the polynomial wildly oscillating. On the other hand, too few parameters restrict the allowed family of functions. Therefore, we select the order of the polynomial function by choosing the degree for which the reduced chi-squared , is closest to unity and such that the Fisher matrix is positive definite.
16. Results
Let us now discuss the results of the final observable for each of these methods. The binning method contains fewer assumptions compared to the polynomial regression or Gaussian process methods. It is essentially a weighted average over the data points and the error bars at each redshift bin. Since we need to take derivatives in order to calculate and , and we have few data points, we opt to compute finite difference derivatives. This has the caveat that it introduces correlations among the errors of the function and its derivatives, that we cannot take into account with this simple method. Moreover, for the binning method, we do not take into account possible non-diagonal covariance matrices for the data, which we do for polynomial regression and the Gaussian process reconstruction.
Figure 2 shows the reconstructed functions obtained by the binning method, the Gaussian process, and polynomial regression, alongside the theoretical prediction of the standard
CDM model. In all cases, the error bars or the bands represent the
uncertainty.
With the binning method, the number of bins is limited by the maximum number of existing data redshifts from the smallest data set corresponding to one of our model-independent observables. In this case, this is the quantity
, for which we have effectively only three redshift bins. There are nine
data points, but most of them are very close to each other in redshift, due to being measured by different collaborations or at different scales in real space for the same
z. As explained in the data section above, we only regard this data as an average over different scales, assuming that non-linear corrections have been correctly taken into account by the respective experimental collaboration. Since we do not have to take derivatives of
, or equivalently
, this leaves us with three possible redshift bins, centered at
,
, and
, all of them with an approximate bin width of
. At these redshifts, we obtain
,
, and
. These values and the estimation of the intermediate model-independent quantities can be seen in
Table A2.
Regarding the Gaussian process method, we computed the normalized Hubble function and its derivative, and , with the dgp module of the GaPP code. We reconstructed and for the redshift interval of the data using the Gaussian function as the covariance function and the initial values of the hyperparameters that were later estimated by the code. The same procedure was done for the data. We obtained, for the and functions, the hyperparameters and and, for the function, and .
For the
observable, the hyperparameters obtained by the GaPP code led to a very flat and unrealistic reconstruction, so we took another approach for obtaining the optimal hyperparameters. We sampled the logarithm of the marginal likelihood on a grid of hyperparameters
,
from 0.01 to 2, setting thus a prior with the redshift range of the dataset, and 300 points equally separated in log-space for each dimension. We remind the reader that the hyperparameter
constrains the typical scale on the independent variable
z. Thus, as an additional prior, we impose that
needs to be smaller than the redshift range of the data, which was not guaranteed by the default GaPP code. We then chose a pair of hyperparameters corresponding to the maximum of the log-marginal likelihood. Therefore, for the
data, we obtained
and
. Its reconstructed derivative
can be seen in the lower right panel of
Figure 2. The function remains relatively flat, compared to the one given by other methods, but this approach has improved the determination of this observable.
Regarding the choice of the kernel function, several functions were compared, each of them with a different number of parameters, to see the impact on the output. We tested the Gaussian kernel with two parameters, (
): the rational quadratic kernel with three parameters and the double Gaussian kernel with four parameters (see the original reference for the explicit implemented formula [
116]). We performed tests using the
data obtained with the cosmic chronometer technique and the
data. Our tests show that the different choices shift the reconstructed function up to
on its central value compared to the Gaussian kernel function. This happens for
, but the effect is negligible for
. Taking into account the above choices and procedure, we report that with the Gaussian process method we obtain
,
, and
.
For the polynomial regression method, we find
,
, and
. Note that we applied the criteria of a
closest to one and a positive definite Fisher matrix to choose the order of the polynomial for each of the datasets. These criteria led to a choice of a polynomial of order 3 for the
and
data and order 6 for the
data. These polynomials can be seen in
Figure 2 as solid yellow lines, together with their
uncertainty bands. The higher order of the polynomial of
explains the “bumpiness” of the reconstruction of
, leading to larger errors on this observable in comparison to the GP method.
In
Figure 3, we show the reconstructed
as a function of redshift with the three different methods, again with GP in a green dashed line, polynomial regression in a yellow solid line, and the binning method in blue squares with error bars. It is possible to conclude that the methods are consistent with each other, within their
uncertainties, and that in most bins the results are consistent with the standard gravity scenario. We find that the error bars of the Gaussian process reconstruction are generally smaller than the other methods, such that at the lowest redshift, GP is not compatible with
at nearly
, while in the case of the binning method at the intermediate redshift,
, the tension is nearly
.
Finally, we can combine the estimates at three redshifts of
Table A2 into a single value. Assuming a constant
in this entire observed range and performing a simple weighted average, we find
(binning),
(Gaussian process), and
(polynomial regression). The Gaussian process method yields the smallest error and excludes standard gravity. However, despite being sometimes advertised as “model-independent”, we believe that this method actually makes a strong assumption, since it compresses the ignorance of the reconstruction into a kernel function that depends on two or a small number of parameters, which are often not even fully marginalized over, which was done in our case. Furthermore, the binning method taken at face value would rule out standard gravity. However, as already mentioned, we did not take into account the correlation induced by the finite differences, and this might have decreased the overall error. Overall, we think the polynomial regression method is the most satisfactory one, providing the best compromise between the least number of assumptions and the best estimation of the data derivative. Therefore, we consider it as our “fiducial” result.
17. Conclusions
Measuring the properties of gravity at large scales will be one of the main tasks of cosmology for the next few years. Several large observational campaigns that are underway, or will soon be [
117,
118,
119,
120,
121], will collect enough data on galaxy clustering and lensing to render this task possible to a high level of accuracy.
In order to test gravity, one has to provide an alternative, either a full model or at least some parametrization, that goes beyond Einstein’s gravity. Here we chose to consider the Horndeski Lagrangian because, although it is based on a single scalar field, it displays most of the properties that make modified gravity models such a rich area of research. We connected a more theoretically oriented parameterization, the
parameters of [
22], with more phenomenologically oriented ones, the
parameters. To gain a deeper physical understanding, we also discussed some interesting limiting cases: how the Newtonian potentials look in real space, and the impact of the constraints from gravitational wave speed.
The first practical goal in cosmology is to test and possibly rule out specific models of gravity and background expansion. For instance, one can rule out CDM in a number of ways, the simplest of which being measuring a deviation from the predicted behavior (which is not equivalent, as we have seen, to simply finding deviations from a equation of state). Models in which gravity is modified can often be designed to have a perfect CDM background, so it is necessary to test them at the perturbation level.
Here, however, a problem arises, namely that many more assumptions generally need to be made. Some of them, listed in
Section 9, are in some sense of fundamental character, and we follow them in this work. However, most cosmological analyses that test gravity assume, in addition, one or more of the following assumptions: (1) that the initial conditions are given by a simple inflationary spectrum described by one or two parameters; (2) that the cosmological evolution at a
z value larger than a few is given by a pure CDM-dominated universe living in standard gravity; (3) that the linear bias depends only on time and not on scale; and (4) that the value of some parameters, such as
obtained from CMB analyses assuming
CDM, can also be applied to different models.
We have shown that the statistics called
can be measured without any of these four assumptions. These statistics can be used as an estimator of the anisotropic stress parameter
, one of the two phenomenological functions of linearized, scalar, sub-horizon modified gravity. In this sense, we say that
is (relatively) model-independent. If
differs from unity, either gravity is modified, or at least one of the four “fundamental” assumptions of
Section 9 are false.
We have provided a preliminary estimate of
based on currently available data,
in the redshift range
. The full
k- and
z-dependence is still inaccessible with current data. According to [
25], the Euclid mission will be able to measure
to a few percent, which is thus almost two orders of magnitude better than current values, and will be able to begin placing interesting limits on the
k- and
z-dependence. As the philosopher of science Alexandre Koyré said concerning the emergence of modern science (Koyré, A. (1948).
Du monde de l’à peu près à l’univers de la précision. In A. Koyré (Ed.), Etudes d’histoire de la pensée philosophique (pp. 341–362). Paris: Gallimard.), and with regard to measuring gravity at cosmological scales, we will finally move “from the world of approximation to the universe of precisi on.”