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First test of Verlinde's theory of emergent gravity using weak gravitational lensing measurements
Margot M. Brouwer Manus R. Visser Andrej Dvornik Henk Hoekstra Konrad Kuijken Edwin A. Valentijn Maciej Bilicki Chris Blake Sarah Brough Hugo Buddelmeijer ... Show more
MNRAS (2016) 466 (3): 2547-2559. DOI: https://doi.org/10.1093/mnras/stw3192
Published: 09 December 2016 Article history
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Abstract
Verlinde proposed that the observed excess gravity in galaxies and clusters is the consequence of emergent gravity (EG). In this theory, the standard gravitational laws are modified on galactic and larger scales due to the displacement of dark energy by baryonic matter. EG gives an estimate of the excess gravity (described as an apparent dark matter density) in terms of the baryonic mass distribution and the Hubble parameter. In this work, we present the first test of EG using weak gravitational lensing, within the regime of validity of the current model. Although there is no direct description of lensing and cosmology in EG yet, we can make a reasonable estimate of the expected lensing signal of low-redshift galaxies by assuming a background Lambda cold dark matter cosmology. We measure the (apparent) average surface mass density profiles of 33 613 isolated central galaxies and compare them to those predicted by EG based on the galaxiesf baryonic masses. To this end, we employ the ∼180 deg2 overlap of the Kilo-Degree Survey with the spectroscopic Galaxy And Mass Assembly survey. We find that the prediction from EG, despite requiring no free parameters, is in good agreement with the observed galaxy–galaxy lensing profiles in four different stellar mass bins. Although this performance is remarkable, this study is only a first step. Further advancements on both the theoretical framework and observational tests of EG are needed before it can be considered a fully developed and solidly tested theory.
gravitation, gravitational lensing: weak, surveys, galaxies: haloes, cosmology: theory, dark matter
Issue Section: Article
INTRODUCTION

In the past decades, astrophysicists have repeatedly found evidence that gravity on galactic and larger scales is in excess of the gravitational potential that can be explained by visible baryonic matter within the framework of General Relativity (GR). The first evidence through the measurements of the dynamics of galaxies in clusters (Zwicky 1937) and the Local Group (Kahn & Woltjer 1959) and through observations of galactic rotation curves (inside the optical discs by Rubin 1983, and far beyond the discs in hydrogen profiles by Bosma 1981) has been confirmed by more recent dynamical observations (Martinsson et al. 2013; Rines et al. 2013). Furthermore, entirely different methods like gravitational lensing (Hoekstra, Yee & Gladders 2004; von der Linden et al. 2014; Hoekstra et al. 2015; Mandelbaum 2015) of galaxies and clusters, baryon acoustic oscillations (BAOs; Eisenstein et al. 2005; Blake et al. 2011) and the cosmic microwave background (CMB; Spergel et al. 2003; Planck Collaboration XIII 2016) have all acknowledged the necessity of an additional mass component to explain the excess gravity. This interpretation gave rise to the idea of an invisible dark matter (DM) component, which now forms an important part of our standard model of cosmology. In our current Lambda cold dark matter (CDM) model, the additional mass density (the density parameter CDM = 0.266 found by Planck Collaboration XIII 2016) consists of cold (non-relativistic) DM particles, while the energy density in the cosmological constant ( = 0.685) explains the observed accelerating expansion of the Universe. In this paradigm, the spatial structure of the sub-dominant baryonic component (with b = 0.049) broadly follows that of the DM. When a DM halo forms through the gravitational collapse of a small density perturbation (Peebles & Yu 1970), baryonic matter is pulled into the resulting potential well, where it cools to form a galaxy in the centre (White & Rees 1978). In this framework, the excess mass around galaxies and clusters, which is measured through dynamics and lensing, has hitherto been interpreted as caused by this DM halo.

In this paper, we test the predictions of a different hypothesis concerning the origin of the excess gravitational force: the Verlinde (2016) model of emergent gravity (EG). Generally, EG refers to the idea that space–time and gravity are macroscopic notions that arise from an underlying microscopic description in which these notions have no meaning. Earlier work on the emergence of gravity has indicated that an area law for gravitational entropy is essential to derive Einstein's laws of gravity (Jacobson 1995; Padmanabhan 2010; Verlinde 2011; Faulkner et al. 2014; Jacobson 2016). But due to the presence of positive dark energy in our Universe. Verlinde (2016) argues that in addition to the area law, there exists a volume law contribution to the entropy. This new volume law is thought to lead to modifications of the emergent laws of gravity at scales set by the eHubble acceleration scalef a0 = cH0, where c is the speed of light and H0 the Hubble constant. In particular, Verlinde (2016) claims that the gravitational force emerging in the EG framework exceeds that of GR on galactic and larger scales, similar to the MOND phenomenology (Modified Newtonian Dynamics; Milgrom 1983) that provides a successful description of galactic rotation curves (e.g. McGaugh, Lelli & Schombert 2016). This excess gravity can be modelled as a mass distribution of apparent DM, which is only determined by the baryonic mass distribution Mb(r) (as a function of the spherical radius r) and the Hubble constant H0. In a realistic cosmology, the Hubble parameter H(z) is expected to evolve with redshift z. But because EG is only developed for present-day de Sitter space, any predictions on cosmological evolution are beyond the scope of the current theory. The approximation used by Verlinde (2016) is that our Universe is entirely dominated by dark energy, which would imply that H(z) indeed resembles a constant. In any case, a viable cosmology should at least reproduce the observed values of H(z) at low redshifts, which is the regime that is studied in this work. Furthermore, at low redshifts, the exact specifics of the cosmological evolution have a negligible effect on our measurements. Therefore, to calculate distances from redshifts throughout this work, we can adopt an effective CDM background cosmology with m = 0.315 and = 0.685 (Planck Collaboration XIII 2016), without significantly affecting our results. To calculate the distribution of apparent DM, we use the value of H0 = 70 km s|1Mpc|1. Throughout the paper, we use the following definition for the reduced Hubble constant: h h70 = H0/(70 km s|1Mpc|1).

Because, as mentioned above, EG gives an effective description of GR (with apparent DM as an additional component), we assume that a gravitational potential affects the pathway of photons as it does in the GR framework. This means that the distribution of apparent DM can be observed using the regular gravitational lensing formalism. In this work, we test the predictions of EG specifically relating to galaxy–galaxy lensing (GGL): the coherent gravitational distortion of light from a field of background galaxies (sources) by the mass of a foreground galaxy sample (lenses) (see e.g. Fischer et al. 2000; Hoekstra et al. 2004; Mandelbaum et al. 2006; Velander et al. 2014; van Uitert et al. 2016). Because the prediction of the gravitational potential in EG is currently only valid for static, spherically symmetric and isolated baryonic mass distributions, we need to select our lenses to satisfy these criteria. Furthermore, as mentioned above, the lenses should be at relatively low redshifts since cosmological evolution is not yet implemented in the theory. To find a reliable sample of relatively isolated foreground galaxies at low redshift, we select our lenses from the very complete spectroscopic Galaxy And Mass Assembly survey (GAMA; Driver et al. 2011). In addition, GAMA's stellar mass measurements allow us to test the prediction of EG for four galaxy sub-samples with increasing stellar mass. The background galaxies, used to measure the lensing effect, are observed by the photometric Kilo-Degree Survey (KiDS; de Jong et al. 2013), which was specifically designed with accurate shape measurements in mind.

In Section 2 of this paper, we explain how we select and model our lenses. In Section 3, we describe the lensing measurements. In Section 4, we introduce the EG theory and derive its prediction for the lensing signal of our galaxy sample. In Section 5, we present the measured GGL profiles and our comparison with the predictions from EG and CDM. The discussion and conclusions are described in Section 6.

GAMA LENS GALAXIES

The prediction of the gravitational potential in EG that is tested in this work is only valid for static, spherically symmetric and isolated baryonic mass distributions (see Section 4). Ideally, we would like to find a sample of isolated lenses, but since galaxies are clustered, we cannot use GAMA to find galaxies that are truly isolated. Instead, we use the survey to construct a sample of lenses that dominate their surroundings and a galaxy sample that allows us to estimate the small contribution arising from their nearby low-mass galaxies (i.e. satellites). The GAMA survey (Driver et al. 2011) is a spectroscopic survey with the AAOmega spectrograph mounted on the Anglo-Australian Telescope. In this study, we use the GAMA II (Liske et al. 2015) observations over three equatorial regions (G09, G12 and G15) that together span
∼180deg2
∼180deg2

. Over these regions, the redshifts and properties of 180 960 galaxies1 are measured. These data have a redshift completeness of 98.5 per cent down to a Petrosian r-band magnitude of mr = 19.8. This is very useful to accurately determine the positional relation between galaxies, in order to find a suitable lens sample.

Isolated galaxy selection

To select foreground lens galaxies suitable for our study, we consult the 7th GAMA Galaxy Group Catalogue (G3Cv7) which is created by (Robotham et al. 2011) using a Friends-of-Friends group finding algorithm. In this catalogue, galaxies are classified as either the brightest central galaxy (BCG) or a satellite of a group, depending on their luminosity and their mutual projected and line-of-sight distances. In cases where there are no other galaxies observed within the linking lengths, the galaxy remains enon-groupedf (i.e. it is not classified as belonging to any group). Mock galaxy catalogues, which were produced using the Millennium DM simulation (Springel et al. 2005) and populated with galaxies according to the semi-analytical galaxy formation recipe eGALFORMf (Bower et al. 2006), are used to calibrate these linking lengths and test the resulting group properties.

However, since GAMA is a flux-limited survey, it does not include the satellites of the faintest observed GAMA galaxies when these are fainter than the flux limit. Many fainter galaxies are therefore classified as non-grouped, whereas they are in reality BCGs. This selection effect is illustrated in Fig. 1, which shows that the number of non-grouped galaxies rises towards faint magnitudes whereas the number of BCGs peaks well before. The only way to obtain a sample of eisolatedf GAMA galaxies without satellites as bright as fL times their parents luminosity, would be to select only non-grouped galaxies brighter than 1/fL times the flux limit (illustrated in Fig. 1 for fL = 0.1). Unfortunately, such a selection leaves too small a sample for a useful lensing measurement. Moreover, we suspect that in some cases, observational limitations may have prevented the detection of satellites in this sample as well. Instead, we use this selection to obtain a reasonable estimate of the satellite distribution around the galaxies in our lens sample. Because the mass of the satellites is approximately spherically distributed around the BCG and is sub-dominant compared to the BCG's mass, we can still model the lensing signal of this component using the EG theory. How we model the satellite distribution and its effect on the lensing signal is described in Sections 2.2.3 and 4.3, respectively.

Figure 1.
The magnitude distribution of non-grouped galaxies (blue) and BCGs (red). The green dashed line indicates the selection that removes galaxies that might have a satellite beyond the visible magnitude limit. These hypothetical satellites have at most a fraction fL = 0.1 of the central galaxy luminosity, corresponding to the magnitude limit: mr < 17.3. We use this enearbyf sample to obtain a reliable estimate of the satellite distribution around our centrals.
The magnitude distribution of non-grouped galaxies (blue) and BCGs (red). The green dashed line indicates the selection that removes galaxies that might have a satellite beyond the visible magnitude limit. These hypothetical satellites have at most a fraction fL = 0.1 of the central galaxy luminosity, corresponding to the magnitude limit: mr < 17.3. We use this enearbyf sample to obtain a reliable estimate of the satellite distribution around our centrals.
Because centrals are only classified as BCGs if their satellites are detected, whereas non-grouped galaxies are likely centrals with no observed satellites, we adopt the name ecentralsf for the combined sample of BCGs and non-grouped galaxies (i.e. all galaxies which are not satellites). As our lens sample, we select galaxies that dominate their surroundings in three ways: (i) they are centrals, i.e. not classified as satellites in the GAMA group catalogue; (ii) they have stellar masses below
1011h|270M⊙
1011h70|2M⊙

, since we find that galaxies with higher stellar mass have significantly more satellites (see Section 2.2.3); and (iii) they are not affected by massive neighbouring groups, i.e. there is no central galaxy within
3h|170Mpc
3h70|1Mpc

(which is the maximum radius of our lensing measurement, see Section 3). This last selection suppresses the contribution of neighbouring centrals (known as the e2-halo termf in the standard DM framework) to our lensing signal, which is visible at scales above
∼1h|170Mpc
∼1h70|1Mpc

.

Furthermore, we only select galaxies with redshift quality nQ ≥ 3, in accordance with the standard recommendation by GAMA. After these four cuts (central, no neighbouring centrals,
M∗<1011h|270M⊙
M∗<1011h70|2M⊙

and nQ ≥ 3), our remaining sample of eisolated centralsf amounts to 33 613 lenses.

Baryonic mass distribution

Because there exists no DM component in the Verlinde (2016) framework of EG, the gravitational potential originates only from the baryonic mass distribution. Therefore, in order to determine the lensing signal of our galaxies as predicted by EG (see Section 4), we need to know their baryonic mass distribution. In this work, we consider two possible models: the point mass approximation and an extended mass profile. We expect the point mass approximation to be valid, given that (i) the bulk mass of a galaxy is enclosed within the minimum radius of our measurement (
30h|170kpc
30h70|1kpc

) and (ii) our selection criteria ensure that our isolated centrals dominate the total mass distribution within the maximum radius of our measurement (
Rmax=3h|170Mpc
Rmax=3h70|1Mpc

). If these two assumptions hold, the entire mass distribution of the isolated centrals can be described by a simple point mass. This allows us to analytically calculate the lensing signal predicted by EG, based on only one observable: the galaxiesf mass Mg that consists of a stellar and a cold gas component. To assess the sensitivity of our interpretation to the mass distribution, we compare the predicted lensing signal of the point mass to that of an extended mass distribution. This more realistic extended mass profile consists of four components: stars, cold gas, hot gas and satellites, which all have an extended density profile. In the following sections, we review each component and make reasonable assumptions regarding their model profiles and corresponding input parameters.

Stars and cold gas

To determine the baryonic masses Mg of the GAMA galaxies, we use their stellar masses M* from version 19 of the stellar mass catalogue, an updated version of the catalogue created by Taylor et al. (2011). These stellar masses are measured from observations of the Sloan Digital Sky Survey (SDSS; Abazajian et al. 2009) and the VISTA Kilo-Degree Infrared Galaxy survey (VIKING; Edge et al. 2013), by fitting Bruzual & Charlot (2003) stellar population synthesis models to the ugrizZYJHK spectral energy distributions (constrained to the rest frame wavelength range 3000–11 000 Å). We correct M* for flux falling outside the automatically selected aperture using the eflux-scalef parameter, following the procedure discussed in Taylor et al. (2011).

In these models, the stellar mass includes the mass locked up in stellar remnants, but not the gas recycled back into the interstellar medium. Because the mass distribution of gas in our galaxies is not measured, we can only obtain realistic estimates from literature. There are two contributions to consider: cold gas consisting of atomic hydrogen (H i), molecular hydrogen (H2) and helium and hot gas consisting of ionized hydrogen and helium. Most surveys find that the mass in cold gas is highly dependent on the galaxiesf stellar mass. For low-redshift galaxies (z < 0.5), the mass in H i (H2) ranges from 20 to 30 per cent (8–10 per cent) of the stellar mass for galaxies with M* = 1010 M⊙, dropping to 5 to 10 per cent (4–5 per cent) for galaxies with M* = 1011 M⊙ (Saintonge et al. 2011; Catinella et al. 2013; Boselli et al. 2014; Morokuma-Matsui & Baba 2015). Therefore, in order to estimate the mass of the cold gas component, we consider a cold gas fraction fcold that depends on the measured M* of our galaxies. We use the best-fitting scaling relation found by Boselli et al. (2014) using the Herschel Reference Survey (Boselli et al. 2010):

(1)
log(fcold)=log(Mcold/M∗)=|0.69log(M∗)+6.63.
log⁡(fcold)=log⁡(Mcold/M∗)=|0.69log⁡(M∗)+6.63.

In this relation, the total cold gas mass Mcold is defined as the combination of the atomic and molecular hydrogen gas, including an additional 30 per cent contribution of helium:
Mcold=1.3(MHI+MH2)
Mcold=1.3(MHI+MH2)

. With a maximum measured radius of ∼1.5 times the effective radius of the stellar component, the extent of the cold gas distribution is very similar to that of the stars (Pohlen et al. 2010; Crocker et al. 2011; Mentuch Cooper et al. 2012; Davis et al. 2013). We therefore consider the stars and cold gas to form a single galactic mass distribution with:
(2)
Mg=(M∗+Mcold)=M∗(1+fcold).
Mg=(M∗+Mcold)=M∗(1+fcold).

For both the point mass and the extended mass profile, we use this galactic mass Mg to predict the lensing signal in the EG framework.
In the point mass approximation, the total density distribution of our galaxies consists of a point source with its mass corresponding to the galactic mass Mg of the lenses. For the extended mass profile, we use Mg as an input parameter for the density profile of the estars and cold gasf component. Because starlight traces the mass of this component, we use the Sérsic intensity profile (Sérsic 1963; Sérsic 1968) as a reasonable approximation of the density:

(3)
IS(r)S(r)=eexp{|bn[(rre)1/n|1]}.
IS(r)S(r)=eexp⁡{|bn[(rre)1/n|1]}.

Here re is the effective radius, n is the Sérsic index and bn is defined such that (2n) = 2(2n, bn). The Sérsic parameters were measured for 167 600 galaxies by Kelvin et al. (2012) on the United Kingdom Infrared Telescope (UKIRT) Infrared Deep Sky Survey Large Area Survey images from GAMA and the ugrizYJHK images of SDSS DR7 (where we use the parameter values as measured in the r-band). Of these galaxies, 69 781 are contained in our GAMA galaxy catalogue. Although not all galaxies used in this work (the 33,613 isolated centrals) have Sérsic parameter measurements, we can obtain a realistic estimate of the mean Sérsic parameter values of our chosen galaxy samples. We use re and n equal to the mean value of the galaxies for which they are measured within each sample, in order to model the density profile S(r) of each full galaxy sample. This profile is multiplied by the effective mass density e, which is defined such that the mass integrated over the full S(r) is equal to the mean galactic mass qMgr of the lens sample. The mean measured values of the galactic mass and Sérsic parameters for our galaxy samples can be found in Table 1.
Table 1.
For each stellar mass bin, this table shows the number N and mean redshift qzlr of the galaxy sample. Next to these, it shows the corresponding measured input parameters of the ESD profiles in EG: the mean stellar mass qM*r, galactic mass qMgr, effective radius qrer, Sérsic index qnr, satellite fraction qfsatr and satellite radius qrsatr of the centrals. All masses are displayed in units of
log10(M/h|270M⊙)
log10⁡(M/h70|2M⊙)

and all lengths in
h|170kpc
h70|1kpc

.
M-bin N qzlr qM*r qMgr qrer qnr qfsatr qrsatr
8.5–10.5 14974 0.22 10.18 10.32 3.58 1.66 0.27 140.7
10.5–10.8 10500 0.29 10.67 10.74 4.64 2.25 0.25 143.9
10.8–10.9 4076 0.32 10.85 10.91 5.11 2.61 0.29 147.3
10.9–11 4063 0.33 10.95 11.00 5.56 3.04 0.32 149.0
Hot gas

Hot gas has a more extended density distribution than stars and cold gas and is generally modelled by the -profile (e.g. Cavaliere & Fusco-Femiano 1976; Mulchaey 2000):

(4)
hot(r)=core(1+(r/rcore)2)32,
hot(r)=core(1+(r/rcore)2)32,

which provides a fair description of X-ray observations in clusters and groups of galaxies. In this distribution, rcore is the core radius of the hot gas. The outer slope is characterized by , which, for a hydrostatic isothermal sphere, corresponds to the ratio of the specific energy in galaxies to that in the hot gas (see e.g. Mulchaey 2000, for a review). Observations of galaxy groups indicate ∼ 0.6 (Sun et al. 2009). Fedeli et al. (2014) found similar results using the Overwhelmingly Large Simulations (OWLS; Schaye et al. 2010) for the range in stellar masses that we consider here (i.e. with
M∗∼1010|1011h|270M⊙
M∗∼1010|1011h70|2M⊙

). We therefore adopt = 0.6. Moreover, Fedeli et al. (2014) estimate that the mass in hot gas is at most three times that in stars. As the X-ray properties from the OWLS model of active galactic nuclei match X-ray observations well (McCarthy et al. 2010), we adopt Mhot = 3qM*r. Fedeli et al. (2014) find that the simulations suggest a small core radius rcore (i.e. even smaller than the transition radius of the stars). This implies that hot(r) is effectively described by a single power law. Observations show a range in core radii, but typical values are tens of kiloparsecs (e.g. Mulchaey et al. 1996) for galaxy groups. We take rc = re, which is relatively small in order to give an upper limit; a larger value would reduce the contribution of hot gas and thus move the extended mass profile closer to the point mass case. We define the amplitude core of the profile such that the mass integrated over the full hot(r) distribution is equal to the total hot gas mass Mhot.
Satellites

As described in Section 2.1, we use our nearby (mr < 17.3) sample of centrals (BCGs and non-grouped galaxies) to find that most of the non-grouped galaxies in the GAMA catalogue might not be truly isolated, but are likely to have satellites beyond the visible magnitude limit. Fortunately, satellites are a spherically distributed, sub-dominant component of the lens, which means that its (apparent) mass distribution can be described within EG. In order to assess the contribution of these satellites to our lensing signal, we first need to model their average baryonic mass distribution. We follow van Uitert et al. (2016) by modelling the density profile of satellites around the central as a double power law:2

(5)
sat(r)=sat(r/rsat)(1+r/rsat)2,
sat(r)=sat(r/rsat)(1+r/rsat)2,

where sat is the density and rsat the scale radius of the satellite distribution. The amplitude sat is chosen such that the mass integrated over the full profile is equal to the mean total mass in satellites
⟨Msat∗⟩
⟨M∗sat⟩

measured around our nearby sample of centrals. By binning these centrals according to their stellar mass
Mcen∗
M∗cen

, we find that for centrals within
109<Mcen∗<1011h|270M⊙
109<M∗cen<1011h70|2M⊙

, the total mass in satellites can be approximated by a fraction
fsat=⟨Msat∗⟩/⟨Mcen∗⟩∼0.2|0.3
fsat=⟨M∗sat⟩/⟨M∗cen⟩∼0.2|0.3

. However, for centrals with masses above
1011h|270M⊙
1011h70|2M⊙

, the satellite mass fraction rapidly rises to fsat ∼ 1 and higher. For this reason, we choose to limit our lens sample to galaxies below
1011h|270M⊙
1011h70|2M⊙

. As the value of the scale radius rsat, we pick the half-mass radius (the radius that contains half of the total mass) of the satellites around the nearby centrals. The mean measured mass fraction qfsatr and half-mass radius qrsatr of satellites around centrals in our four M*-bins can be found in Table 1.
LENSING MEASUREMENT

According to GR, the gravitational potential of a mass distribution leaves an imprint on the path of travelling photons. As discussed in Section 1, EG gives an effective description of GR (where the excess gravity from apparent DM detailed in Verlinde 2016 is an additional component). We therefore work under the assumption that a gravitational potential (including that of the predicted apparent DM distribution) has the exact same effect on light rays as in GR. Thus, by measuring the coherent distortion of the images of faraway galaxies (sources), we can reconstruct the projected (apparent) mass distribution (lens) between the background sources and the observer. In the case of GGL, a large sample of foreground galaxies acts as the gravitational lens (for a general introduction, see e.g. Bartelmann & Schneider 2001; Schneider, Kochanek & Wambsganss 2006). Because the distortion of the source images is only ∼1 per cent of their intrinsic shape, the tangential shear t (which is the source ellipticity tangential to the line connecting the source and the centre of the lens) is averaged for many sources within circular annuli around the lens centre. This measurement provides us with the average shear qtr(R) as a function of projected radial distance R from the lens centres. In GR, this quantity is related to the excess surface density (ESD) profile (R). Using our earlier assumption, we can also use the same methodology to obtain the ESD of the apparent DM in the EG framework. The ESD is defined as the average surface mass density qr(<R) within R, minus the surface density (R) at that radius:

(6)
(R)=⟨⟩(<R)|(R)=⟨t⟩(R)crit.
(R)=⟨⟩(<R)|(R)=⟨t⟩(R)crit.

Here crit is the critical surface mass density at the redshift of the lens:
(7)
crit=c24GD(zs)D(zl)D(zl,zs),
crit=c24GD(zs)D(zl)D(zl,zs),

a geometrical factor that is inversely proportional to the strength of the lensing effect. In this equation, D(zl) and D(zs) are the angular diameter distances to the lens and source, respectively, and D(zl, zs) is the distance between the lens and the source.
For a more extensive discussion of the GGL method and the role of the KiDS and GAMA surveys therein, we refer the reader to previous KiDS-GAMA lensing papers: (Sifón et al. 2015, van Uitert et al. 2016, Brouwer et al. 2016) and especially section 3 of (Viola et al. 2015).

KiDS source galaxies

The background sources used in our GGL measurements are observed by KiDS (de Jong et al. 2013). The KiDS photometric survey uses the OmegaCAM instrument (Kuijken et al. 2011) on the VLT Survey Telescope (Capaccioli & Schipani 2011) that was designed to provide a round and uniform point spread function (PSF) over a square degree field of view, specifically with weak lensing measurements in mind. Of the currently available
454deg2
454deg2

area from the eKiDS-450f data release (Hildebrandt et al. 2017), we use the
∼180deg2
∼180deg2

area that overlaps with the equatorial GAMA fields (Driver et al. 2011). After masking bright stars and image defects, 79 per cent of our original survey overlap remains (de Jong et al. 2015).

The photometric redshifts of the background sources are determined from ugri photometry as described in Kuijken et al. (2015) and Hildebrandt et al. (2017). Due to the bias inherent in measuring the source redshift probability distribution p(zs) of each individual source (as was done in the previous KiDS-GAMA studies), we instead employ the source redshift number distribution n(zs) of the full population of sources. The individual p(zs) is still measured, but only to find the ebestf redshift zB at the p(zs)-peak of each source. Following Hildebrandt et al. (2017), we limit the source sample to: zB < 0.9. We also use zB in order to select sources which lie sufficiently far behind the lens: zB > zl + 0.2. The n(zs) is estimated from a spectroscopic redshift sample, which is re-weighted to resemble the photometric properties of the appropriate KiDS galaxies for different lens redshifts (for details, see section 3 of van Uitert et al. 2016 and Hildebrandt et al. 2017). We use the n(z) distribution behind the lens for the calculation of the critical surface density from equation (7):

(8)
|1crit=4Gc2D(zl)zl+0.2D(zl,zs)D(zs)n(zl,zs)dzs,
crit|1=4Gc2D(zl)zl+0.2D(zl,zs)D(zs)n(zl,zs)dzs,

By assuming that the intrinsic ellipticities of the sources are randomly oriented, qtr from equation (6) can be approximated by the average tangential ellipticity qtr given by:
(9)
ϵt=|ϵ1cos(2ϕ)|ϵ2sin(2ϕ),
ϵt=|ϵ1cos⁡(2ϕ)|ϵ2sin⁡(2ϕ),

where 1 and 2 are the measured source ellipticity components and ϕ is the angle of the source relative to the lens centre (both with respect to the equatorial coordinate system). The measurement of the source ellipticities is performed on the r-band data, which is observed under superior observing conditions compared to the other bands (de Jong et al. 2015; Kuijken et al. 2015). The images are reduced by the theli pipeline (Erben et al. 2013 as described in Hildebrandt et al. 2017). The sources are detected from the reduced images using the SExtractor algorithm (Bertin & Arnouts 1996), whereafter the ellipticities of the source galaxies are measured using the improved self-calibrating lensfit code (Miller et al. 2007; Miller et al. 2013; Fenech Conti et al. 2016). Each shape is assigned a weight ws that reflects the reliability of the ellipticity measurement. We incorporate this lensfit weight and the lensing efficiency
|1crit
crit|1

into the total weight:
(10)
Wls=ws|2crit,
Wls=wscrit|2,

which is applied to each lens–source pair. This factor downweights the contribution of sources that have less reliable shape measurements and of lenses with a redshift closer to that of the sources (which makes them less sensitive to the lensing effect).
Inside each radial bin R, the weights and tangential ellipticities of all lens–source pairs are combined according to equation (6) to arrive at the ESD profile:

(11)
(R)=11+KlsWlsϵtcrit,llsWls.
(R)=11+KlsWlsϵtcrit,llsWls.

In this equation, K is the average correction of the multiplicative bias m on the lensfit shear estimates. The values of m are determined using image simulations (Fenech Conti et al. 2016) for eight tomographic redshift slices within 0.1 ≤ zB < 0.9 (Dvornik et al., in preparation). The average correction is computed for the lens–source pairs in each respective redshift slice as follows:
(12)
K=lsWlsmslsWls,
K=lsWlsmslsWls,

where the mean value of K over the entire source redshift range is |0.014.
We also correct the ESD for systematic effects that arise from the residual shape correlations due to PSF anisotropy. This results in non-vanishing contributions to the ESD signal on large scales and at the survey edges, because the averaging is not done over all azimuthal angles. This spurious signal can be determined by measuring the lensing signal around random points. We use ∼18 million locations from the GAMA random catalogue and find that the resulting signal is small (below 10 per cent for scales up to
∼1h|170Mpc
∼1h70|1Mpc

). We subtract the lensing signal around random locations from all measured ESD profiles.

Following previous KiDS-GAMA lensing papers, we measure the ESD profile for 10 logarithmically spaced radial bins within
0.02<R<2h|1100Mpc
0.02<R<2h100|1Mpc

, where our estimates of the signal and uncertainty are thoroughly tested.3 However, since we work with the h h70 definition, we use the approximately equivalent
0.03<R<3h|170Mpc
0.03<R<3h70|1Mpc

as our radial distance range. The errors on the ESD values are given by the diagonal of the analytical covariance matrix. Section 3.4 of Viola et al. (2015) includes the computation of the analytical covariance matrix and shows that up to a projected radius of
R=2h|1100Mpc
R=2h100|1Mpc

, the square root of the diagonal is in agreement with the error estimate from bootstrapping.

LENSING SIGNAL PREDICTION

According to Verlinde (2016), the gravitational potential (r) caused by the enclosed baryonic mass distribution Mb(r) exceeds that of GR on galactic and larger scales. In addition to the normal GR contribution of Mb(r) to (r), there exists an extra gravitational effect. This excess gravity arises due to a volume law contribution to the entropy that is associated with the positive dark energy in our Universe. In a universe without matter, the total entropy of the dark energy would be maximal, as it would be non-locally distributed over all available space. In our Universe, on the other hand, any baryonic mass distribution Mb(r) reduces the entropy content of the Universe. This removal of entropy due to matter produces an elastic response of the underlying microscopic system, which can be observed on galactic and larger scales as an additional gravitational force. Although this excess gravity does not originate from an actual DM contribution, it can be effectively described by an apparent DM distribution MD(r).

The apparent DM formula

Verlinde (2016) determines the amount of apparent DM by estimating the elastic energy associated with the entropy displacement caused by Mb(r). This leads to the following relation:4:

(13)
r02D(r)A(r)dr=VMb(r),
0rD2(r)A(r)dr=VMb(r),

where we integrate over a sphere with radius r and area A(r) = 4r2. The strain D(r) caused by the entropy displacement is given by
(14)
D(r)=8GcH0MD(r)A(r),
D(r)=8GcH0MD(r)A(r),

where c is the speed of light, G the gravitational constant and H0 the present-day Hubble constant (which we choose to be H0 = 70 km s|1Mpc|1). Furthermore,
VMb(r)
VMb(r)

is the volume that would contain the amount of entropy that is removed by a mass Mb inside a sphere of radius r, if that volume were filled with the average entropy density of the universe:
(15)
VMb(r)=8GcH0Mb(r)r3.
VMb(r)=8GcH0Mb(r)r3.

Now inserting the relations (14) and (15) into (13) yields:
(16)
r0GM2D(r)r2dr=Mb(r)rcH06.
0rGMD2(r)r2dr=Mb(r)rcH06.

Finally, by taking the derivative with respect to r on both sides of the equation, one arrives at the following relation:
(17)
M2D(r)=cH0r26Gd(Mb(r)r)dr.
MD2(r)=cH0r26Gd(Mb(r)r)dr.

This is the apparent DM formula from Verlinde (2016) that translates a baryonic mass distribution into an apparent DM distribution. This apparent DM only plays a role in the regime where the elastic response of the entropy of dark energy SDE takes place: where
V(r)>VMb(r)
V(r)>VMb(r)

, i.e. SDE V(r) is large compared to the entropy that is removed by Mb(r) within our radius r. By substituting equation (15) into this condition, we find that this is the case when:
(18)
r>2GcH0Mb(r)|||||||||.
r>2GcH0Mb(r).

For a lower limit on this radius for our sample, we can consider a point source with a mass of
M=1010h|270M⊙
M=1010h70|2M⊙

, close to the average mass qMgr of galaxies in our lowest stellar mass bin. In this simple case, the regime starts when
r>2h|170kpc
r>2h70|1kpc

. This shows that our observations (which start at
30h|170kpc
30h70|1kpc

) are well within the EG regime.
However, it is important to keep in mind that this equation does not represent a new fundamental law of gravity, but is merely a macroscopic approximation used to describe an underlying microscopic phenomenon. Therefore, this equation is only valid under the specific set of circumstances that have been assumed for its derivation. In this case, the system considered was a static, spherically symmetric and isolated baryonic mass distribution. With these limitations in mind, we have selected our galaxy sample to meet these criteria as closely as possible (see Section 2.1).

Finally, we note that in order to test the EG predictions with gravitational lensing, we need to make some assumptions about the used cosmology (as discussed in Section 1). These concern the geometric factors in the lensing equation (equation 7) and the evolution of the Hubble constant (which enters in equation 17 for the apparent DM). We assume that if EG is to be a viable theory, it should predict an expansion history that agrees with the current supernova data (Riess, Press & Kirshner 1996; Kessler et al. 2009; Betoule et al. 2014), specifically over the redshift range that is relevant for our lensing measurements (0.2 < zs < 0.9). If this is the case, the angular diameter distance–redshift relation is similar to what is used in CDM. We therefore adopt a CDM background cosmology with m = 0.315 and = 0.685, based on the Planck Collaboration XIII (2016) measurements. Regarding H0 in equation (17), we note that a Hubble parameter that changes with redshift is not yet implemented in the EG theory. However, for the lens redshifts considered in this work (qzlr ∼ 0.2), the difference resulting from using H0 or H(zl) to compute the lensing signal prediction is ∼5 per cent. This means that considering the statistical uncertainties in our measurements (≳40 per cent, see e.g. Fig. 2), our choice to use H0 = 70 km s|1Mpc|1 instead of an evolving H(zl) has no significant effect on the results of this work.

Figure 2.
The ESD profile predicted by EG for isolated centrals, both in the case of the point mass approximation (dark red, solid) and the extended galaxy model (dark blue, solid). The former consists of a point source with the mass of the stars and cold gas component (red), with the lensing signal evaluated for both the baryonic mass (dash–dotted) and the apparent DM (dashed). The latter consists of a stars and cold gas component modelled by a Sérsic profile (blue), a hot gas component modelled by a -profile (magenta) and a satellite distribution modelled by a double power law (orange), all with the lensing signal evaluated for both the baryonic mass (dash–dotted) and the apparent DM (dashed). Note that the total ESD of the extended mass distribution is not equal to the sum of its components, due to the non-linear conversion from baryonic mass to apparent DM. All profiles are shown for our highest mass bin ($10^{10.9} < M_{\ast } < 10^{11} \,h_{70}^{-2}\,{\rm M_{\odot }}$), but the difference between the two models is similar for the other galaxy sub-samples. The difference between the ESD predictions of the two models is comparable to the median 1 uncertainty on our lensing measurements (illustrated by the grey band).
The ESD profile predicted by EG for isolated centrals, both in the case of the point mass approximation (dark red, solid) and the extended galaxy model (dark blue, solid). The former consists of a point source with the mass of the stars and cold gas component (red), with the lensing signal evaluated for both the baryonic mass (dash–dotted) and the apparent DM (dashed). The latter consists of a stars and cold gas component modelled by a Sérsic profile (blue), a hot gas component modelled by a -profile (magenta) and a satellite distribution modelled by a double power law (orange), all with the lensing signal evaluated for both the baryonic mass (dash–dotted) and the apparent DM (dashed). Note that the total ESD of the extended mass distribution is not equal to the sum of its components, due to the non-linear conversion from baryonic mass to apparent DM. All profiles are shown for our highest mass bin (
1010.9<M∗<1011h|270M⊙
1010.9<M∗<1011h70|2M⊙

), but the difference between the two models is similar for the other galaxy sub-samples. The difference between the ESD predictions of the two models is comparable to the median 1 uncertainty on our lensing measurements (illustrated by the grey band).
From equation (17), we now need to determine the ESD profile of the apparent DM distribution, in order to compare the predictions from EG to our measured GGL profiles. The next steps towards this EG(R) depend on our assumptions regarding the baryonic mass distribution of our lenses. We compute the lensing signal in EG for two models (which are discussed in Section 2.2): the point mass approximation and the more realistic extended mass distribution.

Point mass approximation

In this work, we measure the ESD profiles of galaxies at projected radial distances
R>30h|170kpc
R>30h70|1kpc

. If we assume that beyond this distance, the galaxy is almost entirely enclosed within the radius r, we can approximate the enclosed baryonic mass as a constant: Mb(r) = Mb. Re-writing equation (17) accordingly yields:

(19)
MD(r)=cH06G||||rMb|||CDrMb|||,
MD(r)=cH06GrMbCDrMb,

where CD is a constant factor determined by c, G and H0. In order to calculate the resulting D(R), we first need to determine the spherical density distribution D(r). Under the assumption of spherical symmetry, we can use:
(20)
D(r)=14r2dMD(r)dr=CDMb|||4r2.
D(r)=14r2dMD(r)dr=CDMb4r2.

We calculate the corresponding surface density D(R) as a function of projected distance R in the cylindrical coordinate system (R, ϕ, z), where z is the distance along the line of sight and r2 = R2 + z2, such that:
(21)
D(R)=|D(R,z)dz.
D(R)=|D(R,z)dz.

Substituting D(R, z) provides the surface density of the apparent DM distribution associated with our point mass:
(22)
D(R)=CDMb|||420dzR2+z2=CDMb|||4R.
D(R)=CDMb420dzR2+z2=CDMb4R.

We can now use equation (6) to find the ESD:
(23)
(R)==⟨⟩(<R)|(R)2΁R0(R)RdRR2|(R).
(R)=⟨⟩(<R)|(R)=2΁0R(R)RdRR2|(R).

In the case of our point mass:
(24)
D(R)=CDMb|||2R|CDMb|||4R=CDMb|||4R,
D(R)=CDMb2R|CDMb4R=CDMb4R,

which happens to be equal to D(R) from equation (22).5
Apart from the extra contribution from the apparent DM predicted by EG, we also need to add the standard GR contribution from baryonic matter to the ESD. Under the assumption that the galaxy is a point mass we know that b(R) = 0 for R > 0, and that the integral over b(R) must give the total mass Mb of the galaxy. Substituting this into equation (23) gives us

(25)
b(R)=MbR2.
b(R)=MbR2.

Ultimately, the total ESD predicted by EG in the point mass approximation is
(26)
EG(R)=b(R)+D(R),
EG(R)=b(R)+D(R),

where the contributions are the ESDs of a point source with mass Mg of our galaxies, both in GR and EG.
Extended mass distribution

The above derivation only holds under the assumption that our galaxies can be considered point masses. To test whether this is justified, we wish to compare the point mass prediction to a more realistic lens model. This model includes the extended density profile for stars, cold gas, hot gas and satellites as described in Section 2.2. To determine the ESD profile of the extended galaxy model as predicted by EG, we cannot perform an analytical calculation as we did for the point mass approximation. Instead, we need to calculate the apparent DM distribution
MextD(r)
MDext(r)

and the resulting
extD(R)
Dext(R)

numerically for the sum of all baryonic components. We start out with the total spherical density distribution
extb(r)
bext(r)

of all components:

(27)
extb(r)=Sb(r)+hotb(r)+satb(r),
bext(r)=bS(r)+bhot(r)+bsat(r),

where the respective contributions are: the Sérsic model for stars and cold gas, the -profile for hot gas and the double power law for satellites. We numerically convert this to the enclosed mass distribution:
(28)
Mextb(r)=4΁0rextb(r)r2dr.
Mbext(r)=4΁0rbext(r)r2dr.

We rewrite equation (17) in order to translate
Mextb(r)
Mbext(r)

to its corresponding distribution of apparent DM in EG:
(29)
MextD(r)=CDrdMextb(r)rdr|||||||||,
MDext(r)=CDrdMbext(r)rdr,

which is numerically converted into the apparent DM density distribution
extD(r)
Dext(r)

by substituting
MextD(r)
MDext(r)

into equation (20).
The projected surface density
extD(R)
Dext(R)

from equation (21) is calculated by computing the value of
extD(R,z)
Dext(R,z)

in cylindrical coordinates for 103 values of z and integrating over them. The last step towards computing the ESD profile is the subtraction of
extD(R)
Dext(R)

from the average surface density within R, as in equation (23), where
⟨extD⟩(<R)
⟨Dext⟩(<R)

is calculated by performing the cumulative sum over
2RextD(R)
2RDext(R)

and dividing the result by its cumulative area. In addition to the lensing signal from apparent DM, we need to include the baryonic ESD profile. We numerically compute
extb(R)
bext(R)

from
extb(r)
bext(r)

in the same way as we computed
extD(R)
Dext(R)

from
extD(r)
Dext(r)

. This makes the total ESD predicted by EG for the extended mass distribution:

(30)
extEG(R)=extb(R)+extD(R).
EGext(R)=bext(R)+Dext(R).

When considering the resulting ESD profiles of the extended density models, we must keep in mind that they only represent reasonable estimates that contain uncertainties for two different reasons.

The extended baryonic density distribution of each component is approximated using reasonable assumptions on the used model profiles and their corresponding input parameters. These assumptions are based on observations of the galaxies in our sample and of other galaxies and also on simulations. Although we try to find suitable input parameters corresponding to the measured stellar mass of our galaxy samples, we cannot be certain that our modelled density distributions are completely correct.
We cannot model the extended density distribution for each individual GAMA galaxy, but have to assume one average profile per lens sample (based on the average stellar mass qM*r of that sample). Translating the extended baryonic mass model to the lensing profile of its corresponding apparent DM distribution (as explained above) is a highly non-linear operation. Therefore, we cannot be certain that the calculated lensing profile of an average density distribution is exactly the same as the lensing profile of all individual galaxies combined, although these would only differ greatly in the unlikely case that there is a large spread in the input parameters of the extended mass profiles within each stellar mass sub-sample.
For these two reasons, we cannot use the average profile as a reliable model for the apparent DM lensing signal of our galaxy samples. In the point mass approximation, we do have the measured input parameter (the stellar mass) for each individual galaxy and we can compute the apparent DM lensing profile for each individual galaxy. However, this approach can only be used when the contribution from hot gas and satellites is small. We therefore compare our estimate of the apparent DM lensing profile of the extended mass distribution to that of the point masses, to assess the error margins in our EG prediction.

The total ESD profile predicted for the extended density distribution, and that of each component,6 is shown in Fig. 2. We only show the profiles for the galaxies in our highest stellar mass bin:
1010.9<M∗<1011h|270M⊙
1010.9<M∗<1011h70|2M⊙

, but since the relations between the mass in hot gas, satellites and their galaxies are approximately linear, the profiles look similar for the other sub-samples. At larger scales, we find that the point mass approximation predicts a lower ESD than the extended mass profile. However, the difference between the (R) predictions of these two models is comparable to the median 1 uncertainty on the ESD of our sample (which is illustrated by the grey band in Fig. 2). We conclude that given the current statistical uncertainties in the lensing measurements, the point mass approximation is adequate for isolated centrals within the used radial distance range (
0.03<R<3h|170Mpc
0.03<R<3h70|1Mpc

).

RESULTS

We measure the ESD profiles (following Section 3) of our sample of isolated centrals, divided into four sub-samples of increasing stellar mass. The boundaries of the M*-bins:
log(M∗/h|270M⊙)=[8.5,10.5,10.8,10.9,11.0]
log⁡(M∗/h70|2M⊙)=[8.5,10.5,10.8,10.9,11.0]

, are chosen to maintain an approximately equal signal to noise in each bin. Fig. 3 shows the measured ESD profiles (with 1 error bars) of galaxies in the four M*-bins. Together with these measurements, we show the ESD profile predicted by EG, under the assumption that our isolated centrals can be considered point masses at scales within
0.03<R<3h|170Mpc
0.03<R<3h70|1Mpc

. The masses Mg of the galaxies in each bin serve as input in equation (26) that provides the ESD profiles predicted by EG for each individual galaxy. The mean baryonic masses of the galaxies in each M*-bin can be found in Table 1. The ESDs of the galaxies in each sample are averaged to obtain the total EG(R). It is important to note that the shown EG profiles do not contain any free parameters: both their slope and amplitudes are fixed by the prediction from the EG theory (as stated in equation 17) and the measured masses Mg of the galaxies in each M*-bin. Although this is only a first attempt at testing the EG theory using lensing data, we can perform a very simple comparison of this prediction with both the lensing observations and the prediction from the standard CDM model.

Figure 3.
The measured ESD profiles of isolated centrals with 1 error bars (black), compared to those predicted by EG in the point source mass approximation (blue) and for the extended mass profile (blue, dashed). Note that none of these predictions are fitted to the data: they follow directly from the EG theory by substitution of the baryonic masses Mg of the galaxies in each sample (and, in the case of the extended mass profile, reasonable assumptions for the other baryonic mass distributions). The mean measured galaxy mass is indicated at the top of each panel. For comparison, we show the ESD profile of a simple NFW profile as predicted by GR (red), with the DM halo mass Mh fitted as a free parameter in each stellar mass bin.
The measured ESD profiles of isolated centrals with 1 error bars (black), compared to those predicted by EG in the point source mass approximation (blue) and for the extended mass profile (blue, dashed). Note that none of these predictions are fitted to the data: they follow directly from the EG theory by substitution of the baryonic masses Mg of the galaxies in each sample (and, in the case of the extended mass profile, reasonable assumptions for the other baryonic mass distributions). The mean measured galaxy mass is indicated at the top of each panel. For comparison, we show the ESD profile of a simple NFW profile as predicted by GR (red), with the DM halo mass Mh fitted as a free parameter in each stellar mass bin.
Model comparison

In standard GGL studies performed within the CDM framework, the measured ESD profile is modelled by two components: the baryonic mass of the galaxy and its surrounding DM halo. The baryonic component is often modelled as a point source with the mean baryonic mass of the galaxy sample, whereas the DM halo component usually contains several free parameters, such as the mass and concentration of the halo, which are evaluated by fitting a model to the observed ESD profiles. Motivated by N-body simulations, the DM halo is most frequently modelled by the NFW density profile (Navarro et al. 1995), very similar to the double power law in equation (5). This profile has two free parameters: the halo mass Mh that gives the amplitude and the scale radius rs that determines where the slope changes. Following previous GAMA-KiDS lensing papers (see e.g. Sifón et al. 2015; Viola et al. 2015; Brouwer et al. 2016; van Uitert et al. 2016), we define Mh as M200: the virial mass contained within r200, and we define the scale radius in terms of the concentration: c r200/rs. In these definitions, r200 is the radius that encloses a density of 200 times m(z), the average matter density of the Universe. Using the Duffy et al. (2008) mass–concentration relation, we can define c in terms of Mh. We translate the resulting density profile that depends exclusively on the DM halo mass, into the projected ESD distribution following the analytical description of Wright & Brainerd (2000). We combine this NFW model with a point mass that models the baryonic galaxy component (as in equation 25). Because our lens selection minimizes the contribution from neighbouring centrals (see Section 2.1), we do not need to add a component that fits the 2-halo term. We fit the NFW model to our measured ESD profiles using the emcee sampler (Foreman-Mackey et al. 2013) with 100 walkers performing 1000 steps. The model returns the median posterior values of Mh (including 16th and 84th percentile error margins) displayed in Table 2. The best-fitting ESD profile of the NFW model (including 16th and 84th percentile bands) is shown in Fig. 3.

Table 2.
For each stellar mass bin, this table shows the median values (including 16th and 84th percentile error margins) of the halo mass Mh obtained by the NFW fit and the ebestf amplitude AB that minimizes the 2 if the EG profile were multiplied by it (for the point mass and extended mass profile). The halo masses are displayed in units of
log10(M/h|270M⊙)
log10⁡(M/h70|2M⊙)

.
M-bin Mh AB
AextB
ABext

8.5–10.5
12.15+0.10|0.11
12.15|0.11+0.10

1.36+0.21|0.21
1.36|0.21+0.21

1.21+0.19|0.19
1.21|0.19+0.19

10.5–10.8
12.45+0.10|0.11
12.45|0.11+0.10

1.32+0.19|0.19
1.32|0.19+0.19

1.20+0.18|0.18
1.20|0.18+0.18

10.8–10.9
12.43+0.17|0.22
12.43|0.22+0.17

1.07+0.27|0.27
1.07|0.27+0.27

0.94+0.25|0.25
0.94|0.25+0.25

10.9–11
12.62+0.13|0.16
12.62|0.16+0.13

1.33+0.25|0.26
1.33|0.26+0.25

1.20+0.23|0.24
1.20|0.24+0.23

For both the EG predicted by EG (in the point source approximation) and the simple NFW fit NFW, we can compare the mod of the model with the observed obs by calculating the 2 value:

(31)
2=(obs|mod)⊺⋅C|1(obs|mod),
2=(obs|mod)⊺⋅C|1(obs|mod),

where C|1 is the inverse of the analytical covariance matrix (see Section 3). From this quantity, we can calculate the reduced 2 statistic:7
2red=2/NDOF
red2=2/NDOF

. It depends on the number of degrees of freedom (DOF) of the model: NDOF = Ndata | Nparam, where Ndata is the number of data points in the measurement and Nparam is the number of free parameters. Due to our choice of 10 R-bins and 4 M*-bins, we use 4 ~ 10 = 40 data points. In the case of EG, there are no free parameters, which means
NEGDOF=40
NDOFEG=40

. Our simple NFW model has one free parameter Mh for each M*-bin, resulting in
NNFWDOF=40|4=36
NDOFNFW=40|4=36

. The resulting total
2red
red2

over the four M*-bins is 44.82/40 = 1.121 for EG and 33.58/36 = 0.933 for the NFW fit. In other words, both the NFW and EG prediction agree quite well with the measured ESD profile, where the NFW fit has a slightly better
2red
red2

value. Since the NFW profile is an empirical description of the surface density of virialized systems, the apparent correspondence of both the NFW fit and the EG prediction with the observed ESD essentially reflects that the predicted EG profile roughly follows that of virialized systems.
A more appropriate way to compare the two models, however, is in the Bayesian framework. We use a very simple Bayesian approach by computing the Bayesian Information Criterion (BIC; Schwarz 1978). This criterion, which is based on the maximum likelihood
Lmax
Lmax

of the data given a model, penalizes model complexity more strongly than the
2red
red2

. This model comparison method is closely related to other information criteria such as the Akaike Information Criterion (AIK; Akaike 1973) which have become popular because they only require the likelihood at its maximum value, rather than in the whole parameter space, to perform a model comparison (see e.g. Liddle 2007). This approximation only holds when the posterior distribution is Gaussian and the data points are independent. Calculating the BIC, which is defined as:

(32)
BIC=|2ln(Lmax)+Nparamln(Ndata),
BIC=|2ln⁡(Lmax)+Nparamln⁡(Ndata),

allows us to consider the relative evidence of two competing models, where the one with the lowest BIC is preferred. The difference BIC gives the significance of evidence against the higher BIC, ranging from e0 - 2: Not worth more than a bare mentionf to e>10: Very strongf (Kass & Raftery 1995). In the Gaussian case, the likelihood can be rewritten as:
|2ln(Lmax)=2
|2ln⁡(Lmax)=2

. Using this method, we find that BICEG = 44.82 and BICNFW = 48.33. This shows that, when the number of free parameters is taken into account, the EG model performs at least as well as the NFW fit. However, in order to really distinguish between these two models, we need to reduce the uncertainties in our measurement, in our lens modelling, and in the assumptions related to EG theory and halo model.
In order to further assess the quality of the EG prediction across the M*-range, we determine the ebestf amplitude AB and index nB: the factors that minimize the 2 statistic when we fit:

(33)
EG(AB,nB,R)=ABCDMb|||4(Rh|170kpc)|nB,
EG(AB,nB,R)=ABCDMb4(Rh70|1kpc)|nB,

We find that the slope of the EG prediction is very close to the observed slope of the ESD profiles, with a mean value of
⟨nB⟩=1.01+0.02|0.03
⟨nB⟩=1.01|0.03+0.02

. In order to obtain better constraints on AB, we set nB = 1. The values of AB (with 1 errors) for the point mass are shown in Table 2. We find the amplitude of the point mass prediction to be consistently lower than the measurement. This is expected since the point mass approximation only takes the mass contribution of the central galaxy into account, and not that of extended components like hot gas and satellites (described in Section 2.2). However, the ESD of the extended profile (which is shown in Fig. 3 for comparison) does not completely solve this problem. When we determine the best amplitude for the extended mass distribution by scaling its predicted ESD, we find that the values of
AextB
ABext

are still larger than 1, but less so than for the point mass (at a level of ∼1, see Table 2). Nevertheless, the comparison of the extended ESD with the measured lensing profile yields a slightly higher reduced 2: 45.50/40 = 1.138. However, accurately predicting the baryonic and apparent DM contribution of the extended density distribution is challenging (see Section 4.3). Therefore, the extended ESD profile can primarily be used as an indication of the uncertainty in the lens model.
CONCLUSION

Using the
∼180deg2
∼180deg2

overlap of the KiDS and GAMA surveys, we present the first test of the theory of EG proposed in Verlinde (2016) using weak gravitational lensing. In this theory, there exists an additional component to the gravitational potential of a baryonic mass, which can be described as an apparent DM distribution. Because the prediction of the apparent DM profile as a function of baryonic mass is currently only valid for static, spherically symmetric and isolated mass distributions, we select 33,613 central galaxies that dominate their surrounding mass distribution, and have no other centrals within the maximum radius of our measurement (
Rmax=3h|170Mpc
Rmax=3h70|1Mpc

). We model the baryonic matter distribution of our galaxies using two different assumptions for their mass distribution: the point mass approximation and the extended mass profile. In the point mass approximation we assume that the bulk of the galaxy's mass resides within the minimum radius of our measurement (
Rmin=30h|170kpc
Rmin=30h70|1kpc

), and model the lens as a point source with the mass of the stars and cold gas of the galaxy. For the extended distribution, we not only model the stars and cold gas component as a Sérsic profile, but also try to make reasonable estimates of the extended hot gas and satellite distributions. We compute the lensing profiles of both models and find that, given the current statistical uncertainties in our lensing measurements, both models give an adequate description of isolated centrals. In this regime (where the mass distribution can be approximated by a point mass) the lensing profile of apparent DM in EG is the same as that of the excess gravity in MOND,8 for the specific value a0 = cH0/6.

When computing the observed and predicted ESD profiles, we need to make several assumptions concerning the EG theory. The first is that, because EG gives an effective description of GR in empty space, the effect of the gravitational potential on light rays remains unchanged. This allows us to use the regular gravitational lensing formalism to measure the ESD profiles of apparent DM in EG. Our second assumption involves the used background cosmology. Because EG is only developed for present-day de Sitter space, we need to assume that the evolution of cosmological distances is approximately equal to that in CDM, with the cosmological parameters as measured by the Planck Collaboration XIII (2016). For the relatively low redshifts used in this work (0.2 < zs < 0.9), this is a reasonable assumption. The third assumption is the value of H0 that we use to calculate the apparent DM profile from the baryonic mass distribution. In an evolving universe, the Hubble parameter H(z) is expected to change as a function of the redshift z. This evolution is not yet implemented in EG. Instead it uses the approximation that we live in a dark energy dominated universe, where H(z) resembles a constant. We follow Verlinde (2016) by assuming a constant value, in our case: H0 = 70 km s|1Mpc|1, which is reasonable at a mean lens redshift of qzlr ∼ 0.2. However, in order to obtain a more accurate prediction for the cosmology and the lensing signal in the EG framework, all these issues need to be resolved in the future.

Using the mentioned assumptions, we measure the ESD profiles of isolated centrals in four different stellar mass bins, and compare these with the ESD profiles predicted by EG. They exhibit a remarkable agreement, especially considering that the predictions contain no free parameters: both the slope and the amplitudes within the four M*-bins are completely fixed by the EG theory and the measured baryonic masses Mg of the galaxies. In order to perform a very simple comparison with CDM, we fit the ESD profile of a simple NFW distribution (combined with a baryonic point mass) to the measured lensing profiles. This NFW model contains one free parameter, the halo mass Mh, for each stellar mass bin. We compare the reduced 2 of the NFW fit (which has 4 free parameters in total) with that of the prediction from EG (which has no free parameters). Although the NFW fit has fewer degrees of freedom (which slightly penalizes
2red
red2

) the reduced 2 of this model is slightly lower than that of EG, where
2red,NFW=0.933
red,NFW2=0.933

and
2red,EG=1.121
red,EG2=1.121

in the point mass approximation. For both theories, the value of the reduced 2 is well within reasonable limits, especially considering the very simple implementation of both models. The fact that our observed density profiles resemble both NFW profiles and the prediction from EG, suggests that this theory predicts a phenomenology very similar to a virialized DM halo. Using the Bayesian Information Criterion, we find that BICEG = 44.82 and BICNFW = 48.33. These BIC values imply that taking the number of data points and free parameters into account, the EG prediction describes our data at least as well as the NFW fit. However, a thorough and fair comparison between CDM and EG would require a more sophisticated implementation of both theories and a full Bayesian analysis that properly takes the free parameters and priors of the NFW model into account. None the less, given that the model uncertainties are also addressed, future data should be able to distinguish between the two theories.

We propose that this analysis should not only be carried out for this specific case, but on multiple scales and using a variety of different probes. From comparing the predictions of EG to observations of isolated centrals, we need to expand our studies to the scales of larger galaxy groups, clusters and eventually to cosmological scales: the cosmic web, BAOs and the CMB power spectrum. Furthermore, there are various challenges for EG, especially concerning observations of dynamical systems such as the Bullet Cluster (Randall et al. 2008) where the dominant mass component appears to be separate from the dominant baryonic component. There is also ongoing research to assess whether there exists an increasing mass-to-light ratio for galaxies of later type (Martinsson et al. 2013), which might challenge EG if confirmed. We conclude that although this first result is quite remarkable, it is only a first step. There is still a long way to go, for both the theoretical groundwork and observational tests, before EG can be considered a fully developed and solidly tested theory. In this first GGL study, however, EG appears to be a good parameter-free description of our observations.

M. Brouwer and M. Visser would like to thank Erik Verlinde for helpful clarifications and discussions regarding his EG theory. We also thank the anonymous referee for the useful comments that helped to improve this paper.

The work of M. Visser was supported by the European Research Council (ERC) Advanced Grant 268088-EMERGRAV, and is part of the Delta Institute for Theoretical Physics (ITP) consortium, a program of the Netherlands Organisation for Scientific Research (NWO). M. Bilicki, H. Hoekstra and C. Sifon acknowledge support from the ERC under FP7 grant number 279396. K. Kuijken is supported by the Alexander von Humboldt Foundation. M. Bilicki acknowledges support from the NWO through grant number 614.001.103. H. Hildebrandt is supported by an Emmy Noether grant (No. Hi 1495/2-1) of the Deutsche Forschungsgemeinschaft. R. Nakajima acknowledges support from the German Federal Ministry for Economic Affairs and Energy (BMWi) provided via DLR under project no. 50QE1103. Dominik Klaes is supported by the Deutsche Forschungsgemeinschaft in the framework of the TR33 eThe Dark Universef.

This research is based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme IDs 177.A-3016, 177.A-3017 and 177.A-3018, and on data products produced by Target OmegaCEN, INAF-OACN, INAF-OAPD and the KiDS production team, on behalf of the KiDS consortium. OmegaCEN and the KiDS production team acknowledge support by NOVA and NWO-M grants. Members of INAF-OAPD and INAF-OACN also acknowledge the support from the Department of Physics and Astronomy of the University of Padova, and of the Department of Physics of Univ. Federico II (Naples).

GAMA is a joint European-Australasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the Sloan Digital Sky Survey and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programs including GALEX MIS, VST KiDS, VISTA VIKING, WISE, Herschel-ATLAS, GMRT and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO and the participating institutions. The GAMA website is www.gama-survey.org.

This work has made use of python (www.python.org), including the packages numpy (www.numpy.org), scipy (www.scipy.org) and ipython (Pérez & Granger 2007). Plots have been produced with matplotlib (Hunter 2007).

All authors contributed to the development and writing of this paper. The authorship list is given in three groups: the lead authors (M. Brouwer and M. Visser), followed by two alphabetical groups. The first alphabetical group includes those who are key contributors to both the scientific analysis and the data products. The second group covers those who have either made a significant contribution to the data products or to the scientific analysis.

1
These are all galaxies with redshift quality nQ ≥ 2. However, the recommended redshift quality of GAMA (that we use in our analysis) is nQ ≥ 3.
2
Although this double power law is mathematically equivalent to the Navarro–Frenk–White (NFW) profile (Navarro, Frenk & White 1995) that describes virialized DM haloes, it is, in our case, not related to any (apparent) DM distribution. It is merely an empirical fit to the measured distribution of satellite galaxies around their central galaxy.
3
Viola et al. (2015) used the following definition of the reduced Hubble constant: h h100 = H0/(100 km s|1 Mpc|1).
4
Although Verlinde (2016) derives his relations for an arbitrary number of dimensions d; for the derivation in this paper, we restrict ourselves to four space–time dimensions.
5
Note that the ESD of the apparent DM distribution,
D(R)H0Mb|||||/Rh||
D(R)H0Mb/Rh

, is explicitly dependent on the Hubble constant, which means that an incorrect measured value of H0 would affect our conclusions.
6
Note that due to the non-linear nature of the calculation of the apparent DM distribution, the total ESD profile of the extended mass distribution is not the sum of the components shown in Fig. 2.
7
While the reduced 2 statistic is shown to be a sub-optimal goodness-of-fit estimator (see e.g. Andrae, Schulze-Hartung & Melchior 2010), it is a widely used criterion and we therefore discuss it here for completeness.
8
After this paper was accepted for publication, it was pointed out to us that (Milgrom 2013) showed that galaxy-galaxy lensing measurements from the Canada-France-Hawaii Telescope Legacy Survey (Brimioulle 2013) are consistent with predictions from relativistic extensions of MOND up to a radius of
140h|172kpc
140h72|1kpc

.
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@

JHEP04(2011)029
Published for SISSA by Springer
Accepted: March 19, 2011
Published: April 7, 2011
On the origin of gravity and the laws of Newton
Erik Verlinde
Institute for Theoretical Physics, University of Amsterdam,
Valckenierstraat 65, 1018 XE, Amsterdam, The Netherlands
E-mail: e.p.verlinde@uva.nl
Abstract: Starting from first principles and general assumptions we present a heuristic
argument that shows that Newtonfs law of gravitation naturally arises in a theory in which
space emerges through a holographic scenario. Gravity is identified with an entropic force
caused by changes in the information associated with the positions of material bodies. A
relativistic generalization of the presented arguments directly leads to the Einstein equations.
When space is emergent even Newtonfs law of inertia needs to be explained. The
equivalence principle auggests that it is actually the law of inertia whose origin is entropic.
Keywords: Gauge-gravity correspondence, Models of Quantum Gravity
ArXiv ePrint: 1001.0785
Open Access doi:10.1007/JHEP04(2011)029
JHEP04(2011)029
Contents
1 Introduction 1
2 Entropic force 3
3 Emergence of the laws of Newton 5
3.1 Force and inertia 6
3.2 Newtonfs law of gravity 8
3.3 Naturalness and robustness of the derivation 9
3.4 Inertia and the Newton potential 10
4 Emergent gravity for general matter distributions 11
4.1 The Poisson equation for general matter distributions 12
4.2 The gravitational force for arbitrary particle locations 14
5 The equivalence principle and the Einstein equations 15
5.1 The law of inertia and the equivalence principle 15
5.2 Towards a derivation of the Einstein equations 18
5.3 The force on a collection of particles at arbitrary locations 19
6 Conclusion and discussion 20
6.1 The end of gravity as a fundamental force 20
6.2 Implications for string theory and relation with AdS/CFT 21
6.3 Black hole horizons revisited 23
1 Introduction
Of all forces of Nature gravity is clearly the most universal. Gravity influences and is influenced
by everything that carries an energy, and is intimately connected with the structure
of space-time. The universal nature of gravity is also demonstrated by the fact that its
basic equations closely resemble the laws of thermodynamics and hydrodynamics.1 So far,
there has not been a clear explanation for this resemblance.
Gravity dominates at large distances, but is very weak at small scales. In fact, its basic
laws have only been tested up to distances of the order of a millimeter. Gravity is also
considerably harder to combine with quantum mechanics than all the other forces. The
quest for unification of gravity with these other forces of Nature, at a microscopic level,
may therefore not be the right approach. It is known to lead to many problems, paradoxes
1An incomplete list of references includes [1–7].
– 1 –
JHEP04(2011)029
and puzzles. String theory has to a certain extent solved some of these, but not all. And
we still have to figure out what the string theoretic solution teaches us.
Many physicists believe that gravity, and space-time geometry are emergent. Also
string theory and its related developments have given several indications in this direction.
Particularly important clues come from the AdS/CFT, or more generally, the open/closed
string correspondence. This correspondence leads to a duality between theories that contain
gravity and those that donft. It therefore provides evidence for the fact that gravity can
emerge from a microscopic description that doesnft know about its existence.
The universality of gravity suggests that its emergence should be understood from
general principles that are independent of the specific details of the underlying microscopic
theory. In this paper we will argue that the central notion needed to derive gravity is
information. More precisely, it is the amount of information associated with matter and
its location, in whatever form the microscopic theory likes to have it, measured in terms
of entropy. Changes in this entropy when matter is displaced leads to a reaction force.
Our aim is to show that this force, given certain reasonable assumptions, takes the form
of gravity.
The most important assumption will be that the information associated with a part
of space obeys the holographic principle [8, 9]. The strongest supporting evidence for the
holographic principle comes from black hole physics [1, 3] and the AdS/CFT correspondence
[10]. These theoretical developments indicate that at least part of the microscopic
degrees of freedom can be represented holographically either on the boundary of space-time
or on horizons.
The concept of holography appears to be much more general, however. For instance,
in the AdS/CFT correspondence one can move the boundary inwards by exploiting a
holographic version of the renormalization group. Similarly, in black hole physics there exist
ideas that the information can be stored on stretched horizons. Furthermore, by thinking
about accelerated observers, one can in principle locate holographic screens anywhere in
space. In all these cases the emergence of the holographic direction is accompanied by
redshifts, and related to a coarse graining procedure. If all these combined ideas are
correct there should exist a general framework that describes how space emerges together
with gravity.
Usually holography is studied in relativistic contexts. However, the gravitational force
is also present in the non-relativistic world. The origin of gravity, whatever it is, should
therefore also naturally explain why this force appears the way it does, and obeys Newton
law of gravitation. In fact, when space is emergent, also the other laws of Newton have
to be re-derived, because standard concepts like position, velocity, acceleration, mass and
force are far from obvious. Hence, in such a setting the laws of mechanics have to appear
alongside with space itself. Even a basic concept like inertia is not given, and needs to be
explained again.
In this paper we present a holographic scenario for the emergence of space and address
the origins of gravity and inertia, which are connected by the equivalence principle. Starting
from first principles, using only space independent concepts like energy, entropy and
temperature, it is shown that Newtonfs laws appear naturally and practically unavoidably.
– 2 –
JHEP04(2011)029
A crucial ingredient is that only a finite number of degrees of freedom are associated
with a given spatial volume, as dictated by the holographic principle. The energy, that is
equivalent to the matter, is distributed evenly over the degrees of freedom, and thus leads
to a temperature. The product of the temperature and the change in entropy due to the
displacement of matter is shown to be equal to the work done by the gravitational force.
In this way we find that Newtonfs law of gravity emerges in a surprisingly simple fashion.
The holographic principle has not been easy to extract from the laws of Newton and
Einstein, and is deeply hidden within them. Conversely, starting from holography, we find
that these well known laws come out. By reversing the logic that lead people from the laws
of gravity to holography, one obtains a simpler picture of what gravity is.
The presented ideas are consistent with our knowledge of string theory, but if correct
they should have important implications for this theory as well. In particular, the description
of gravity as being due to the exchange of closed strings has to be explained from an
emergent scenario.
We start in section 2 with an exposition of the concept of entropic force. Section 3
illustrates the main heuristic argument in a simple non relativistic setting. Its generalization
to arbitrary matter distributions is explained in section 4. In section 5 we extend
these results to the relativistic case, and derive the Einstein equations. The conclusions
are presented in section 6.
2 Entropic force
An entropic force is an effective macroscopic force that originates in a system with many
degrees of freedom by the statistical tendency to increase its entropy. The force equation
is expressed in terms of entropy differences, and is independent of the details of the microscopic
dynamics. In particular, there is no fundamental field associated with an entropic
force. Entropic forces occur typically in macroscopic systems such as in colloid or biophysics.
Big colloid molecules suspended in a thermal environment of smaller particles,
for instance, experience entropic forces due to excluded volume effects. Osmosis is another
phenomenon driven by an entropic force.
Perhaps the best known example is the elasticity of a polymer. A single polymer
molecule can be modeled by joining together many monomers of fixed length, where each
monomer can freely rotate around the points of attachment and direct itself in any spatial
direction. Each of these configurations has the same energy. When the polymer molecule
is immersed into a heat bath, it likes to put itself into a randomly coiled configuration
since these are entropically favored. There are many more such configurations when the
molecule is short compared to when it is stretched into an extended configuration. The
statistical tendency to return to a maximal entropy state translates into a macroscopic
force, in this case the elastic force.
By using tweezers one can pull the endpoints of the polymer apart, and bring it out of
its equilibrium configuration by an external force F, as shown in figure 1. For definiteness,
we keep one end fixed, say at the origin, and move the other endpoint along the x-axis.
– 3 –
JHEP04(2011)029
Figure 1. A free jointed polymer is immersed in a heat bath with temperature T and pulled out
of its equilibrium state by an external force F. The entropic force points the other way.
The entropy equals
S(E, x) = kB log Ω(E, x) (2.1)
where kB is Boltzmanfs constant and Ω(E, x) denotes the volume of the configuration space
for the entire system as a function of the total energy E of the heat bath and the position
x of the second endpoint. The x dependence is entirely a configurational effect: there is
no microscopic contribution to the energy E that depends on x.
In the canonical ensemble the force F is introduced in the partition function2
Z(T, F) =Z
dEdx Ω(E, x) e
|(E+F x)/kBT
. (2.2)
as an external variable dual to the length x of the polymer. The force F required to keep
the polymer at a fixed length x for a given temperature E can be deduced from the saddle
point equations
1
T
=
S
E ,
F
T
=
S
x . (2.3)
By the balance of forces, the external force F should be equal to the entropic force, that
tries to restore the polymer to its equilibrium position. An entropic force is recognized
by the facts that it points in the direction of increasing entropy, and, secondly, that it is
proportional to the temperature. For the polymer the force can be shown to obey Hookefs
law
Fpolymer ∼ |const · kBT hxi.
This example makes clear that at a macroscopic level an entropic force can be conservative,
at least when the temperature is kept constant. The corresponding potential has no
microscopic meaning, however, and is emergent.
It is interesting to study the energy and entropy balance when one gradually lets the
polymer return to its equilibrium position, while allowing the force to perform work on an
external system. By energy conservation, this work must be equal to the energy that has
been extracted from the heat bath. The entropy of the heat bath will hence be reduced.
For an infinite heat bath this would be by the same amount as the increase in entropy of
the polymer. Hence, in this situation the total entropy will remain constant.
2We like to thank B. Nienhuis and M. Shigemori for enlightening discussions on the following part.
– 4 –
JHEP04(2011)029
This can be studied in more detail in the micro-canonical ensemble, because it takes the
total energy into account including that of the heat bath. To determine the entropic force,
one again introduces an external force F and examines the balance of forces. Specifically,
one considers the micro-canonical ensemble given by Ω(E + F x, x), and imposes that the
entropy is extremal. This gives
d
dxS(E+F x, x) = 0 (2.4)
One easily verifies that this leads to the same equations (2.3). However, it illustrates that
micro-canonically the temperature is in general position dependent, and the force also
energy dependent. The term F x can be viewed as the energy that was put into the system
by pulling the polymer out of its equilibrium position. This equation tells us therefore that
the total energy is reduced when the polymer slowly returns to its equilibrium position,
but that the entropy stays the same. In this sense the force acts adiabatically.
Note added. In the following our discussion of the polymer is used as a metaphor to
illustrate that changes in the amount of information, measured by entropy, can lead to a
force. Our aim is to argue that gravity is also an entropic force in this sense. Indeed, we will
see that the same kind of reasonings apply to gravity, with some slight modifications. In
particular, the notions of entropy and temperature used in this paper should be interpreted
as a way of characterizing the amount of information associated with the microscopic
degrees of freedom and the energy costs that is associated with changes in this amount of
of the phase space occupied by the microscopic states.
Another example of an emergent adiabatic force is the reaction force of a fast system
when it is influenced by a slowly varying system. In the Born-Oppenheimer approximation
this force can be obtained by requiring that the phase space volume of all states with
energies below the given state remains constant. This leads to exactly a similar expression
as the entropic force in a thermodynamic situation. In this paper we will merge this
concept with that of an entropic force. A more detailed explanation of the connection
between adiabatic reaction forces with entropic forces, and the relevance for gravity, will
be explained in a future publication [16]
3 Emergence of the laws of Newton
Space is in the first place a device introduced to describe the positions and movements
of particles. Space is therefore literally a storage space for information associated with
matter. Given that the maximal allowed information is finite for each part of space, it is
impossible to localize a particle with infinite precision at a point of a continuum space. In
fact, points and continuous coordinates should eventually arise only as derived concepts.
One could assume that information is stored in points of a discretized space (like in a lattice
model). But if all the associated information would be without duplication, one would not
obtain a holographic description, and in fact, one would not recover gravity.
– 5 –
JHEP04(2011)029
Thus we are going to assume that information is stored on surfaces, or screens. Screens
separate points, and in this way are the natural place to store information about particles
that move from one side to the other. Thus we imagine that this information about the
location particles is stored in discrete bits on the screens. The dynamics on each screen
is given by some unknown rules, which can be thought of as a way of processing the
information that is stored on it. Hence, it does not have to be given by a local field theory,
or anything familiar. The microscopic details are irrelevant for us.
Let us also assume that (like in AdS/CFT) there is one special direction corresponding
to scale or a coarse graining variable of the microscopic theory. This is the direction in which
space is emergent. So the screens that store the information are like stretched horizons.
On one side we image that we are using the variables associated with space and time. On
the other side of the screen we describe everything still in terms of the microscopic data
from which space is derived. We will assume that the microscopic theory has a well defined
notion of time, and its dynamics is time translation invariant. This allows one to define
energy, and by employing techniques of statistical physics, temperature. These will be the
basic ingredients together with the entropy associated with the amount of information.
3.1 Force and inertia
Our starting assumption is directly motivated by Bekensteinfs original thought experiment
[1]from which he obtained his famous entropy formula. He considered a particle with
mass m attached to a fictitious gstringh that is lowered towards a black hole. Just before
the horizon the particle is dropped in. Due to the infinite redshift the mass increase
of the black hole can be made arbitrarily small, classically. If one would take a thermal
gas of particles, this fact would lead to problems with the second law of thermodynamics.
Bekenstein solved this by arguing that when a particle is one Compton wavelength from
the horizon, it is considered to be part of the black hole. Therefore, it increases the mass
and horizon area by a small amount, which he identified with one bit of information. This
led him to his area law for the black hole entropy.
We want to mimic this reasoning not near a black hole horizon, but in flat nonrelativistic
space. So we consider a small piece of a holographic screen, and a particle
of mass m that approaches it from the side at which space time has already emerged.
Concretely this means that on one side the physics is described in macroscopic variables
such as the positions of particles. The physics of the other side of the screen is still
formulated in term of microscopic degrees of freedom. The holographic principle tells us
that we can imagine that its associated information can be mapped on to the screen that
separates the two region. Eventually the particle merges with these microscopic degrees of
freedom, but before it does so it already influences the amount of its associated information.
The situation is depicted in figure 2.
Motivated by Bekensteinfs argument, let us postulate that the change of entropy associated
with the information on the boundary equals
∆S = 2kB when ∆x =
~
mc
. (3.1)
– 6 –
JHEP04(2011)029
Figure 2. A particle with mass approaches a part of the holographic screen. The screen bounds
the emerged part of space, which contains the particle, and stores data that describe the part of
space that has not yet emerged, as well as some part of the emerged space.
The reason for putting in the factor of 2, will become apparent soon. Let us rewrite this
formula in the slightly more general form by assuming that the change in entropy near the
screen is linear in the displacement ∆x.
∆S = 2kB
mc
~
∆x. (3.2)
To understand why it is also proportional to the mass m, let us imagine splitting the
particle into two or more lighter sub-particles. Each sub-particle then carries its own
associated change in entropy after a shift ∆x. Since entropy and mass are both additive,
it is natural to expect that the entropy change should be proportional to the mass. How
does force arise? The basic idea is to use the analogy with osmosis across a semi-permeable
membrane. When a particle has an entropic reason to be on one side of the membrane and
the membrane carries a temperature, it will experience an effective force equal to
F ∆x = T ∆S. (3.3)
This is the entropic force. Thus, in order to have a non zero force, we need to have a
non vanishing temperature. From Newtonfs law we know that a force leads to a non zero
acceleration. Of course, it is well known that acceleration and temperature are closely
related. Namely, as Unruh showed, an observer in an accelerated frame experiences a
temperature
kBT =
1
2
~a
c
, (3.4)
where a denotes the acceleration. Let us take this as the temperature associated with the
bits on the screen. Now it is clear why the equation (3.2) for ∆S was chosen to be of the
given form, including the factor of 2. It is picked precisely in such a way that one recovers
the second law of Newton
F = ma. (3.5)
as is easily verified by combining (3.4) together with (3.2) and (3.3).
– 7 –
JHEP04(2011)029
Equation (3.4) should be read as a formula for the temperature T that is required
to cause an acceleration equal to a. And not as usual, as the temperature caused by
an acceleration.
3.2 Newtonfs law of gravity
Now suppose our boundary is not infinitely extended, but forms a closed surface. More
specifically, let us assume it is a sphere with already emerged space on the outside. For
the following it is best to forget about the Unruh law (3.4), since we donft need it. It only
served as a further motivation for (3.2). The key statement is simply that we need to have
a temperature in order to have a force. Since we want to understand the origin of gravity,
we need to know where the temperature comes from.
One can think about the boundary as a storage device for information. Assuming
that the holographic principle holds, the maximal storage space, or total number of bits,
is proportional to the area A. In fact, in a theory of emergent space this how area may be
defined: each fundamental bit occupies by definition one unit cell.
Let us denote the number of used bits by N. It is natural to assume that this number
will be proportional to the area. So we write
N =
Ac3
G~
(3.6)
where we introduced a new constant G. Eventually this constant is going to be identified
with Newtonfs constant, of course. But since we have not assumed anything yet about the
existence a gravitational force, one can simply regard this equation as the definition of G.
So, the only assumption made here is that the number of bits is proportional to the area.
Nothing more.
Suppose there is a total energy E present in the system. Let us now just make the
simple assumption that the energy is divided evenly over the bits N. The temperature is
then determined by the equipartition rule
E =
1
2
N kBT (3.7)
as the average energy per bit. After this we need only one more equation. It is:
E = M c2
. (3.8)
Here M represents the mass that would emerge in the part of space enclosed by the screen,
see figure 3. Even though the mass is not directly visible in the emerged space, its presence
is noticed though the energy that is distributed of the the screen.
The rest is straightforward: one eliminates E and inserts the expression for the number
of bits to determine T in terms of M and A. Next one uses the postulate (3.2) for the
change of entropy to determine the force. Finally one inserts
A = 4R2
.
– 8 –
JHEP04(2011)029
Figure 3. A particle with mass m near a spherical holographic screen. The energy is evenly
distributed over the occupied bits, and is equivalent to the mass M that would emerge in the part
of space surrounded by the screen.
and one obtains the familiar law:
F = G
Mm
R2
. (3.9)
We have recovered Newtonfs law of gravitation, practically from first principles!
These equations do not just come out by accident. It had to work, partly for dimensional
reasons, and also because the laws of Newton have been ingredients in the steps
that lead to black hole thermodynamics and the holographic principle. In a sense we have
reversed these arguments. But the logic is clearly different, and sheds new light on the
origin of gravity: it is an entropic force! That is the main statement, which is new and has
not been made before. If true, this should have profound consequences.
3.3 Naturalness and robustness of the derivation
Our starting point was that space has one emergent holographic direction. The additional
ingredients were that (i) there is a change of entropy in the emergent direction (ii) the
number of degrees of freedom are proportional to the area of the screen, and (iii) the energy
is evenly distributed over these degrees of freedom. After that it is unavoidable that the
resulting force takes the form of Newtonfs law. In fact, this reasoning can be generalized
to arbitrary dimensions3 with the same conclusion. But how robust and natural are these
heuristic arguments?
Perhaps the least obvious assumption is equipartition, which in general holds only for
free systems. But how essential is it? Energy usually spreads over the microscopic degrees
of freedom according to some non trivial distribution function. When the lost bits are
randomly chosen among all bits, one expects the energy change associated with ∆S still
to be proportional to the energy per unit area E/A. This fact could therefore be true even
when equipartition is not strictly obeyed.
3
In d dimensions (3.6) includes a factor 1
2
d|2
d|3
to get the right identification with Newtonfs constant.
– 9 –
JHEP04(2011)029
Why do we need the speed of light c in this non relativistic context? It was necessary
to translate the mass M into an energy, which provides the heat bath required for the
entropic force. In the non-relativistic setting this heat bath is infinite, but in principle one
has to take into account that the heat bath loses or gains energy when the particle changes
its location under the influence of an external force. This will lead to relativistic redshifts,
as we will see.
Since the postulate (3.1) is the basic assumption from which everything else follows,
let us discuss its meaning in more detail. Why does the entropy precisely change like this
when one shifts by one Compton wave length? In fact, one may wonder why we needed to
introduce Planckfs constant in the first place, since the only aim was to derive the classical
laws of Newton. Indeed, ~ eventually drops out of the most important formulas. So, in
principle one could multiply it with any constant and still obtain the same result. Hence, ~
just serves as an auxiliary variable that is needed for dimensional reasons. It can therefore
be chosen at will, and defined so that (3.1) is exactly valid. The main content of this
equation is therefore simply that there is an entropy change perpendicular to the screen
proportional to the mass m and the displacement ∆x. That is all there is to it.
If we would move further away from the screen, the change in entropy will in general
no longer be given by the same rule. Suppose the particle stays at radius R while the screen
is moved to R0 < R. The number of bits on the screen is multiplied by a factor (R0/R)
2
,
while the temperature is divided by the same factor. Effectively, this means that only ~ is
multiplied by that factor, and since it drops out, the resulting force will stay the same. In
this situation the information associated with the particle is no longer concentrated in a
small area, but spreads over the screen. The next section contains a proposal for precisely
how it is distributed, even for general matter configurations.
3.4 Inertia and the Newton potential
To complete the derivation of the laws of Newton we have to understand why the symbol
a, that was basically introduced by hand in (3.4), is equal to the physical acceleration
xN. In fact, so far our discussion was quasi static, so we have not determined yet how to
connect space at different times. In fact, it may appear somewhat counter-intuitive that the
temperature T is related to the vector quantity a, while in our identifications the entropy
gradient ∆S/∆x is related to the scalar quantity m. In a certain way it seems more natural
to have it the other way around.
So let reconsider what happens to the particle with mass m when it approaches the
screen. Here it should merge with the microscopic degrees of freedom on the screen, and
hence it will be made up out of the same bits as those that live on the screen. Since each
bit carries an energy 1
2
kBT, the number of bits n follows from
mc2 =
1
2
n kBT. (3.10)
When we insert this into equation (3.2), and use (3.4), we can express the entropy change
in terms of the acceleration as ∆S
n
= kB
a ∆x
2c
2
. (3.11)
– 10 –
JHEP04(2011)029
By combining the above equations one of course again recovers F = ma as the entropic
force. But, by introducing the number of bits n associated with the particle, we succeeded
in making the identifications more natural in terms of their scalar versus vector character.
In fact, we have eliminated ~ from the equations, which in view of our earlier comment is
a good thing.
Thus we conclude that acceleration is related to an entropy gradient. This will be one
of our main principles: inertia is a consequence of the fact that a particle in rest will stay
in rest because there are no entropy gradients. Given this fact it is natural to introduce
the Newton potential and write the acceleration as a gradient
a = |ރ.
This allows us to express the change in entropy in the concise way
∆S
n
= | kB

2c
2
. (3.12)
We thus reach the important conclusion that the Newton potential keeps track of the
depletion of the entropy per bit. It is therefore natural to identify it with a coarse graining
variable, like the (renormalization group) scale in AdS/CFT. Indeed, in the next section
we propose a holographic scenario for the emergence of space in which the Newton potential
precisely plays that role. This allows us to generalize our discussion to other mass
distributions and arbitrary positions in a natural way, and give additional support for the
presented arguments.
4 Emergent gravity for general matter distributions
Space emerges at a macroscopic level only after coarse graining. One forgets or integrates
out a large number of microscopic degrees of freedom. A certain part of the microscopic
phase space is forgotten. Hence, there will be a finite entropy associated with each matter
configuration, which measures the amount of microscopic information that is made invisible
to the macroscopic observer. In general, this amount will depend on the distribution of the
matter. The microscopic dynamics by which this information is processed looks random
from a macroscopic point of view. Fortunately, to determine the force we donft need the
details of the information, nor the exact dynamics, only the amount of information given
by the entropy, and the energy that is associated with it. If the entropy changes as a
function of the location of the matter distribution, it will lead to an entropic force.
Therefore, space can not just emerge by itself. It has to be endowed by a book keeping
device that keeps track of the amount of information for a given energy distribution. It
turns out, that in a non relativistic situation this device is provided by Newtonfs potential
. And the resulting entropic force is called gravity.
We start from microscopic information. It is assumed to be stored on holographic
screens. Note that information has a natural inclusion property: by forgetting certain bits,
by coarse graining, one reduces the amount of information. This coarse graining can be
achieved through averaging, a block spin transformation, integrating out, or some other
– 11 –
JHEP04(2011)029
Figure 4. The holographic screens are located at equipotential surfaces. The information on the
screens is coarse grained in the direction of decreasing values of the Newton potential . The
maximum coarse graining happens at black hole horizons, when 2/c2 = |1.
renormalization group procedure. At each step one obtains a further coarse grained version
of the original microscopic data.
The coarse grained data live on smaller screens obtained by moving the first screen
further into the interior of the space. The information that is removed by coarse graining
is replaced by the emerged part of space between the two screens. In this way one gets a
nested or foliated description of space by having surfaces contained within surfaces. In other
words, just like in AdS/CFT, there is one emerging direction in space that corresponds to
a gcoarse grainingh variable, something like the cut-off scale of the system on the screens.
A priori there is no preferred holographic direction in flat space. However, this is where
we use our observation about the Newton potential. It is the natural variable that measures
the amount of coarse graining on the screens. Therefore, the holographic direction is given
by the gradient ރ of the Newton potential. In other words, the holographic screens
correspond to equipotential surfaces. This leads to a well defined foliation of space, except
that screens may break up into disconnected parts that each enclose different regions of
space. This is depicted in figure 4.
The amount of coarse graining is measured by the ratio /c2
, as can be seen from (3.12).
Note that |2/c2
is a dimensionless number that is always between zero and one, and
is only equal to one on the horizon of a black hole. We interpret this as the point
where all bits have been maximally coarse grained. Thus the foliation naturally stops
at black hole horizons.
4.1 The Poisson equation for general matter distributions
Consider a microscopic state, which after coarse graining corresponds to a given mass
distribution in space. All microscopic states that lead to the same mass distribution belong
to the same macroscopic state. The entropy for each of these state is defined as the number
of microscopic states that flow to the same macroscopic state.
We want to determine the gravitational force by using virtual displacements, and
calculating the associated change in energy. So, let us freeze time and keep all the matter
– 12 –
JHEP04(2011)029
at fixed locations. Hence, it is described by a static matter density (~r). Our aim is to
obtain the force that the matter distribution exerts on a collection of test particles with
masses mi and positions ~ri
.
We choose a holographic screen S corresponding to an equipotential surface with fixed
Newton potential 0. We assume that the entire mass distribution given by (x) is contained
inside the volume enclosed by the screen, and all test particles are outside this
volume. To explain the force on the particles, we again need to determine the work that
is performed by the force and show that it is naturally written as the change in entropy
multiplied by the temperature. The difference with the spherically symmetric case is that
the temperature on the screen is not necessarily constant. Indeed, the situation is in general
not in equilibrium. Nevertheless, one can locally define temperature and entropy per
unit area.
First let us identify the temperature. We do this by taking a test particle and moving
it close to the screen, and measuring the local acceleration. Thus, motivated by our earlier
discussion we define temperature analogous to (3.4), namely by
kBT =
1
2

kc . (4.1)
Here the derivative is taken in the direction of the outward pointing normal to the screen.
Note at this point is just introduced as a device to describe the local acceleration, but
we donft know yet whether it satisfies an equation that relates it to the mass distribution.
The next ingredient is the density of bits on the screen. We again assume that these
bits are uniformly distributed, and so (3.6) is generalized to
dN =
c
3
G~
dA. (4.2)
Now let us impose the analogue of the equipartition relation (3.7). It is takes the form of
an integral expression for the energy
E =
1
2
kB
Z
S
T dN. (4.3)
It is an amusing exercise to work out the consequence of this relation. Of course, the
energy E is again expressed in terms of the total enclosed mass M. After inserting our
identifications for the left hand side one obtains a familiar relation: Gaussfs law!
M =
1
4G Z
S
ރ · dA. (4.4)
This should hold for arbitrary screens given by equipotential surfaces. When a bit of mass
is added to the region enclosed by the screen S, for example, by first putting it close to the
screen and then pushing it across, the mass M should change accordingly. This condition
can only hold in general if the potential satisfies the Poisson equation
2(~r) = 4G (~r). (4.5)
We conclude that by making natural identifications for the temperature and the information
density on the holographic screens, that the laws of gravity come out in a straightforward
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JHEP04(2011)029
m1
!
F 1

!
r 1
m2
!
F 2
m3
!
F = 0 3
Figure 5. A general mass distribution inside the not yet emerged part of space enclosed by the
screen. A collection of test particles with masses mi are located at arbitrary points ~ri
emerged space outside the screen. The forces F~
i due to gravity are determined by the virtual work
done after infinitesimal displacement ~ri of the particles.
fashion. Note that to obtain Newtonian gravity one has to assume that the bit density on
the screen is uniform, and that the energy follows from an equipartition. Changing either
of these assumption leads to another form of gravity.
4.2 The gravitational force for arbitrary particle locations
The next issue is to obtain the force acting on matter particles that are located at arbitrary
points outside the screen. For this we need a generalization of the first postulate (3.2) to
this situation. What is the entropy change due to arbitrary infinitesimal displacements ~ri
of the particles? There is only one natural choice here. We want to find the change s in
the entropy density locally on the screen S. We noted in (3.12) that the Newton potential
keeps track of the changes of information per unit bit. Hence, the right identification for
the change of entropy density is
s = kB

2c
2
dN (4.6)
where  is the response of the Newton potential due to the shifts ~ri of the positions
of the particles. To be specific,  is determined by solving the variation of the Poisson
equation
2
(~r) = 4GX
i
mi ~ri
·i (~r | ~ri) (4.7)
One can verify that with this identification one indeed reproduces the entropy shift (3.2)
when one of the particles approaches the screen.
Let us now determine the entropic forces on the particles. The combined work done
by all of the forces on the test particles is determined by the first law of thermodynamics.
However, we need to express in terms of the local temperature and entropy variation.
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JHEP04(2011)029
Hence,
X
i
F~
i
· ~ri =
Z
S
T s (4.8)
To see that this indeed gives the gravitational force in the most general case, one simply
has to use the electrostatic analogy. Namely, one can redistribute the entire mass M as
a mass surface density over the screen S without changing the forces on the particles.
The variation of the Newton potential can be obtained from the Greens function for the
Laplacian. The rest of the proof is a straightforward application of electrostatics, but then
applied to gravity. The basic identity one needs to prove is
X
i
F~
i
· ~ri =
1
4G Z
S

ރ | ރ

dA (4.9)
which holds for any location of the screen outside the mass distribution. This is easily
verified by using Stokes theorem and the Laplace equation. The second term vanishes
when the screen is chosen at a equipotential surface. To see this, simply replace by 0
and pull it out of the integral. Since  is sourced by only the particles outside the screen,
the remaining integral just gives zero.
The forces we obtained are independent of the choice of the location of the screen. We
could have chosen any equipotential surface, and we would obtain the same values for F~
i
,
the ones described by the laws of Newton. That all of this works is not just a matter of
dimensional analysis. The invariance under the choice of equipotential surface is very much
consistent with idea that a particular location corresponds to an arbitrary choice of the
scale that controls the coarse graining of the microscopic data. The macroscopic physics,
in particular the forces, should be independent of that choice.
5 The equivalence principle and the Einstein equations
Since we made use of the speed of light c in our arguments, it is a logical step to try
and generalize our discussion to a relativistic situation. So let us assume that the microscopic
theory knows about Lorentz symmetry, or even has the PoincarLe group as a global
symmetry. This means we have to combine time and space into one geometry. A scenario
with emergent space-time quite naturally leads to general coordinate invariance and curved
geometries, since a priori there are no preferred choices of coordinates, nor a reason why
curvatures would not be present. Specifically, we would like to see how Einsteinfs general
relativity emerges from similar reasonings as in the previous section. We will indeed show
that this is possible. But first we study the origin of inertia and the equivalence principle.
5.1 The law of inertia and the equivalence principle
Consider a static background with a global time like Killing vector
a
. To see the emergence
of inertia and the equivalence principle, one has to relate the choice of this Killing vector
field with the temperature and the entropy gradients. In particular, we like to see that the
usual geodesic motion of particles can be understood as being the result of an entropic force.
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JHEP04(2011)029
In general relativity4
the natural generalization of Newtonfs potential is [11],
=
1
2
log(|
a
a). (5.1)
Its exponent e

represents the redshift factor that relates the local time coordinate to that
at a reference point with = 0, which we will take to be at infinity.
Just like in the non relativistic case, we like to use to define a foliation of space,
and put our holographic screens at surfaces of constant redshift. This is a natural choice,
since in this case the entire screen uses the same time coordinate. So the processing of the
microscopic data on the screen can be done using signals that travel without time delay.
We want to show that the redshift perpendicular to the screen can be understood
microscopically as originating from the entropy gradients.5 To make this explicit, let us
consider the force that acts on a particle of mass m. In a general relativistic setting force
is less clearly defined, since it can be transformed away by a general coordinate transformation.
But by using the time-like Killing vector one can given an invariant meaning to
the concept of force [11].
The four velocity u
a of the particle and its acceleration a
b u
aau
b
can be expressed
in terms of the Killing vector
b as
u
b = e
|

b
, ab = e
|2

aa
b
.
We can further rewrite the last equation by making use of the Killing equation
ab + ba = 0
and the definition of . One finds that the acceleration can again be simply expressed the
a
b = |b. (5.2)
Note that just like in the non relativistic situation the acceleration is perpendicular to
screen S. So we can turn it into a scalar quantity by contracting it with a unit outward
pointing vector Nb normal to the screen S and to
b
.
The local temperature T on the screen is now in analogy with the non relativistic
situation defined by
T =
~
2
e
N
bb. (5.3)
Here we inserted a redshift factor e

, because the temperature T is measured with respect
to the reference point at infinity.
To find the force on a particle that is located very close to the screen, we first use
again the same postulate as in section two. Namely, we assume that the change of entropy
4
In this subsection and the next we essentially follow Waldfs book on general relativity (pg. 288–290).
We use a notation in which c and kB are put equal to one, but we will keep G and ~ explicit.
5
In this entire section it will be very useful to keep the polymer example of section 2 in mind, since that
will make the logic of our reasoning very clear.
– 16 –
JHEP04(2011)029
at the screen is 2 for a displacement by one Compton wavelength normal to the screen.
Hence,
aS = |2
m
~
Na, (5.4)
where the minus sign comes from the fact that the entropy increases when we cross from the
outside to the inside. The comments made on the validity of this postulate in section 3.3
apply here as well. The entropic force now follows from (5.3)
Fa = T aS = |meӁa (5.5)
This is indeed the correct gravitational force that is required to keep a particle at fixed
position near the screen, as measured from the reference point at infinity. It is the relativistic
analogue of Newtonfs law of inertia F = ma. The additional factor e

is due to the
redshift. Note that ~ has again dropped out.
It is instructive to rewrite the force equation (5.5) in a microcanonical form. Let
S(E, xa
) be the total entropy associated with a system with total energy E that contains a
particle with mass m at position x
a
. Here E also includes the energy of the particle. The
entropy will in general also dependent on many other parameters, but we suppress these
in this discussion.
As we explained in the section 2, an entropic force can be determined micro-canonically
by adding by hand an external force term, and impose that the entropy is extremal. For
this situation this condition looks like
d
dxa
S

E+e
(x)m, xa

= 0. (5.6)
One easily verifies that this leads to the same equation (5.5). This fixes the equilibrium
point where the external force, parametrized by (x) and the entropic force statistically
balance each other. Again we stress the point that there is no microscopic force acting
here! The analogy with equation (2.4) for the polymer, discussed in section 2, should be
obvious now.
Equation (5.6) tells us that the entropy remains constant if we move the particle and
simultaneously reduce its energy by the redshift factor. This is true only when the particle
is very light, and does not disturb the other energy distributions. It simply serves as a
probe of the emergent geometry. This also means that redshift function (x) is entirely
fixed by the other matter in the system.
We have arrived at equation (5.6) by making use of the identifications of the temperature
and entropy variations in space time. But actually we should have gone the other way.
We should have started from the microscopics and defined the space dependent concepts
in terms of them. We chose not to follow such a presentation, since it might have appeared
somewhat contrived.
But it is important to realize that the redshift must be seen as a consequence of the
entropy gradient and not the other way around. The equivalence principle tells us that
redshifts can be interpreted in the emergent space time as either due to a gravitational
field or due to the fact that one considers an accelerated frame. Both views are equivalent
in the relativistic setting, but neither view is microscopic. Acceleration and gravity are
both emergent phenomena.
– 17 –
JHEP04(2011)029
5.2 Towards a derivation of the Einstein equations
We would like to extend our derivation of the laws of gravity to the relativistic case, and
obtain the Einstein equations. We will present a sketch of how this can be done in a very
analogous fashion. Let us again consider a holographic screen on closed surface of constant
redshift . We assume that it is enclosing a certain static mass configuration with total
mass M. The bit density on the screen is again given by
dN =
dA
G~
(5.7)
as in (4.2). Following the same logic as before, let us assume that the energy associated
with the mass M is distributed over all the bits. Again by equipartition each bit carries a
mass unit equal to 1
2
T. Hence
M =
1
2
Z
S
T dN (5.8)
After inserting the identifications for T and dN we obtain
M =
1
4G Z
S
e
Ӂރ · dA (5.9)
Note that again ~ drops out, as expected. The equation (5.9) is indeed known to be the
natural generalization of Gaussfs law to General Relativity. Namely, the right hand side is
precisely Komarfs definition of the mass contained inside an arbitrary volume inside any
static curved space time. It can be derived by assuming the Einstein equations. In our
reasoning, however, we are coming from the other side. We made identifications for the
temperature and the number of bits on the screen. But we donft know yet whether it
satisfies any field equations. The key question at this point is whether the equation (5.9)
is sufficient to derive the full Einstein equations.
An analogous question was addressed by Jacobson for the case of null screens. By
adapting his reasoning to this situation, and combining it with Waldfs exposition of the
Komar mass, it is straightforward to construct an argument that naturally leads to the
Einstein equations. We will present a sketch of this.
First we make use of the fact that the Komar mass (5.9) can alternatively be reexpressed
in terms of the Killing vector
a as
M =
1
8G Z
S
abcdc

d
(5.10)
Next one uses Stokes theorem and subsequently the relation aa
b = |Rb
a
a which is
implied by the Killing equation for
a
. This leads to an expression for the mass in terms
of the Ricci tensor.
M =
1
4G Z

Rabn
a

b
dV (5.11)
From this identity one can get to an integrated form of the Einstein equations, by noting
that the left hand side can be expressed as an integral over the enclosed volume of certain
components of stress energy tensor Tab. The particular combination of the stress energy
– 18 –
JHEP04(2011)029
tensor can be fixed by comparing properties on both sides, such as for instance the conservation
laws of the tensors that occur in the integrals. This leads finally to the integral
relation
2
Z


Tab |
1
2
T gab
n
a

b
dV =
1
4G Z

Rabn
a

b
dV (5.12)
where is the three dimensional volume bounded by the holographic screen S and n
a
is
its normal.
We arrived at the equation (5.12) directly from (5.9) by performing independent steps
on both the left and the right hand side. It is derived for a general static background with
a time like Killing vector
a
. By requiring that it holds for arbitrary screens implies that
also the integrands on both sides are equal. This gives us only a certain component of
the Einstein equation. In fact, we can choose the surface in many ways, as long as its
boundary is given by S. This means that we can vary the normal n
a
. But that still leaves
a contraction with the Killing vector
a
.
To try and get to the Einstein equations we now use a similar reasoning as Jacobson [7],
except now applied to time-like screens. Let us consider a very small region of space time
and look also at very short time scales. Since locally every geometry looks approximately
like Minkowski space, we can choose approximate time like Killing vectors. Now consider
a small local part of the screen, and impose that when matter crosses it, the value of the
Komar integral will jump precisely by the corresponding mass m. By following the steps
described above then leads to (5.12) for all these Killing vectors, and for arbitrary screens.
This kind of reasoning should be sufficient to obtain the full Einstein equations. It is worth
making this sketchy derivation into a complete proof of the Einstein equations.
5.3 The force on a collection of particles at arbitrary locations
We close this section with explaining the way the entropic force acts on a collection of
particles at arbitrary locations xi away from the screen and the mass distribution. The
Komar definition of the mass will again be useful for this purpose. The definition of the
Komar mass depends on the choice of Killing vector a. In particular also in its norm, the
redshift factor e

. If one moves the particles by a virtual displacement xi
, this will effect
the definition of the Komar mass of the matter configuration inside the screen. In fact, the
temperature on the screen will be directly affected by a change in the redshift factor.
The virtual displacements can be performed quasi-statically, which means that the
Killing vector itself is still present. Its norm, or the redshift factor, may change, however.
In fact, also the spatial metric may be affected by this displacement. We are not going to
try to solve these dependences, since that would be impossible due to the non linearity of
the Einstein equations. But we can simply use the fact that the Komar mass is going to
be a function of the positions xi of the particles.
Next let us assume that in addition to this xi dependence of the Komar mass that the
entropy of the entire system has also explicit xi dependences, simply due to changes in the
amount of information. These are de difference that will lead to the entropic force that we
wish to determine. We will now give a natural prescription for the entropy dependence that
is based on a maximal entropy principle and indeed gives the right forces. Namely, assume
– 19 –
JHEP04(2011)029
that the entropy may be written as a function of the Komar mass M and in addition on
the xi
. But since the Komar mass should be regarded as a function M(xi) of the positions
xi
, there will be an explicit and an implicit xi dependence in the entropy. The maximal
entropy principle implies that these two dependences should cancel. So we impose
S

M(xi+xi), xi+xi

= S

M(xi), xi

(5.13)
By working out this condition and singling out the equations implied by each variation xi
one finds
iM + T iS = 0 (5.14)
The point is that the first term represents the force that acts on the i-th particle due to
the mass distribution inside the screen. This force is indeed equal to minus the derivative
of the Komar mass, simply because of energy conservation. But again, this is not the
microscopic reason for the force. In analogy with the polymer, the Komar mass represents
the energy of the heat bath. Its dependence on the position of the other particles is caused
by redshifts whose microscopic origin lies in the depletion of the energy in the heat bath
due to entropic effects.
Since the Komar integral is defined on the holographic screen, it is clear that like in the
non relativistic case the force is expressed as an integral over this screen as well. We have
not tried to make this representation more concrete. Finally, we note that this argument
was very general, and did not really use the precise form of the Komar integral, or the
Einstein equations. So it should be straightforward to generalize this reasoning to higher
derivative gravity theories by making use of Waldfs Noether charge formalism [12], which
is perfectly suitable for this purpose.
6 Conclusion and discussion
The ideas and results presented in this paper lead to many questions. In this section we
discuss and attempt to answer some of these. First we present our main conclusion.
6.1 The end of gravity as a fundamental force
Gravity has given many hints of being an emergent phenomenon, yet up to this day it is
still seen as a fundamental force. The similarities with other known emergent phenomena,
such as thermodynamics and hydrodynamics, have been mostly regarded as just suggestive
analogies. It is time we not only notice the analogy, and talk about the similarity, but
finally do away with gravity as a fundamental force.
Of course, Einsteinfs geometric description of gravity is beautiful, and in a certain way
compelling. Geometry appeals to the visual part of our minds, and is amazingly powerful
in summarizing many aspects of a physical problem. Presumably this explains why we, as
a community, have been so reluctant to give up the geometric formulation of gravity as
being fundamental. But it is inevitable we do so. If gravity is emergent, so is space time
geometry. Einstein tied these two concepts together, and both have to be given up if we
want to understand one or the other at a more fundamental level.
– 20 –
JHEP04(2011)029
Our description was clearly motivated by the AdS/CFT correspondence. The gravitational
side of this duality is usually seen as independently defined. But in our view it is
a macroscopic emergent description, which by chance we happened to know about before
we understood it as being the dual of a microscopic theory without gravity. We canft
resist making the analogy with a situation in which we would have developed a theory for
elasticity using stress tensors in a continuous medium half a century before knowing about
atoms. We probably would have been equally resistant in accepting the obvious. Gravity
and closed strings are not much different, but we just have not yet got used to the idea.
The results of this paper suggest gravity arises as an entropic force, once space and
time themselves have emerged. If the gravity and space time can indeed be explained as
emergent phenomena, this should have important implications for many areas in which
gravity plays a central role. It would be especially interesting to investigate the consequences
for cosmology. For instance, the way redshifts arise from entropy gradients could
The derivation of the Einstein equations presented in this paper is analogous to previous
works, in particular [7]. Also other authors have proposed that gravity has an entropic
or thermodynamic origin, see for instance [14]. But we have added an important element
that is new. Instead of only focussing on the equations that govern the gravitational field,
we uncovered what is the origin of force and inertia in a context in which space is emerging.
We identified a cause, a mechanism, for gravity. It is driven by differences in entropy, in
whatever way defined, and a consequence of the statistical averaged random dynamics at
the microscopic level. The reason why gravity has to keep track of energies as well as
entropy differences is now clear. It has to, because this is what causes motion!
The presented arguments have admittedly been rather heuristic. One can not expect
otherwise, given the fact that we are entering an unknown territory in which space does
not exist to begin with. The profound nature of these questions in our view justifies the
heuristic level of reasoning. The assumptions we made have been natural: they fit with
existing ideas and are supported by several pieces of evidence. In the following we gather
more supporting evidence from string theory, the AdS/CFT correspondence, and black
hole physics.
6.2 Implications for string theory and relation with AdS/CFT
If gravity is just an entropic force, then what does this say about string theory? Gravity
is seen as an integral part of string theory, that can not be taken out just like that. But
we do know about dualities between closed string theories that contain gravity and decoupled
open string theories that donft. A particularly important example is the AdS/CFT
correspondence.
The open/closed string and AdS/CFT correspondences are manifestations of the
UV/IR connection that is deeply engrained within string theory. This connection implies
that short and long distance physics can not be seen as totally decoupled. Gravity is a long
distance phenomenon that clearly knows about short distance physics, since it is evident
that Newtonfs constant is a measure for the number of microscopic degrees of freedom.
String theory invalidates the hgeneral wisdomh underlying the Wilsonian effective field
– 21 –
JHEP04(2011)029
Figure 6. The microscopic theory in a) is effectively described by a string theory consisting of
open and closed strings as shown in b). Both types of strings are cut off in the UV.
theory, namely that integrating out short distance degrees of freedom only generate local
terms in the effective action, most of which become irrelevant at low energies. If that were
completely true, the macroscopic physics would be insensitive to the short distance physics.
The reason why the Wilsonian argument fails, is that it makes a too conservative
assumption about the asymptotic growth of the number of states at high energies. In
string theory the number of high energy open string states is such that integrating them
out indeed leads to long range effects. Their one loop amplitudes are equivalent to the
tree level contributions due to the exchange of close string states, which among other are
responsible for gravity. This interaction is, however, equivalently represented by the sum
over all quantum contributions of the open string. In this sense the emergent nature of
gravity is also supported by string theory.
The AdS/CFT correspondence has an increasing number of applications to areas of
physics in which gravity is not present at a fundamental level. Gravitational techniques are
used as tools to calculate physical quantities in a regime where the microscopic description
fails. The latest of these developments is the application to condensed matter theory. No
one doubts that in these situations gravity emerges only as an effective description. It arises
not in the same space as the microscopic theory, but in a holographic scenario with one
extra dimension. No clear explanation exists of where this gravitational force comes from.
The entropic mechanism described in this paper should be applicable to these physical
systems, and explain the emergence of gravity.
The holographic scenario discussed in this paper has certainly be inspired by the way
holography works in AdS/CFT and open closed string correspondences. In string language,
the holographic screens can be identified with D-branes, and the microscopic degrees of
freedom on these screens represented as open strings defined with a cut off in the UV.
The emerged part of space is occupied by closed strings, which are also defined with a
UV cut off, as shown in figure 6. The open and closed string cut offs are related by the
UV/IR correspondence: pushing the open string cut off to the UV forces the closed string
cut off towards the IR, and vice versa. The value of the cut offs is determined by the
– 22 –
JHEP04(2011)029
location of the screen. Integrating out the open strings produces the closed strings, and
leads to the emergence of space and gravity. Note, however, that from our point of view
the existence of gravity or closed strings is not assumed microscopically: they are emergent
as an effective description.
In this way, the open/closed string correspondence supports the interpretation of gravity
as an entropic force. Yet, many still see the closed string side of these dualities is a well
defined fundamental theory. But in our view gravity and closed strings are emergent and
only present as macroscopic concept. It just happened that we already knew about gravity
before we understood it could be obtained from a microscopic theory without it. We canft
resist making the analogy with a situation in which we would have developed a theory for
elasticity using stress tensors in a continuous medium half a century before knowing about
atoms. We probably would have been equally resistant in accepting the obvious. Gravity
and closed strings are not much different, but we just have to get used to the idea.
6.3 Black hole horizons revisited
We saved perhaps the clearest argument for the fact that gravity is an entropic force to the
very last. The first cracks in the fundamental nature of gravity appeared when Bekenstein,
Hawking and others discovered the laws of black hole thermodynamics. In fact, the thought
experiment mentioned in section 3 that led Bekenstein to his entropy law is surprisingly
similar to the polymer problem. The black hole serves as the heat bath, while the particle
can be thought of as the end point of the polymer that is gradually allowed to go back to
its equilibrium situation.
Of course, there is no polymer in the gravity system, and there appears to be no direct
contact between the particle and the black hole. But here we are ignoring the fact that
one of the dimensions is emergent. In the holographic description of this same process,
the particle can be thought of as being immersed in the heat bath representing the black
hole. This fact is particularly obvious in the context of AdS/CFT, in which a black hole is
dual to a thermal state on the boundary, while the particle is represented as a delocalized
operator that is gradually being thermalized. By the time that the particle reaches the
horizon it has become part of the thermal state, just like the polymer. This phenomenon
is clearly entropic in nature, and is the consequence of a statistical process that drives the
system to its state of maximal entropy.
Upon closer inspection Bekensteinfs reasoning can be used to show that gravity becomes
an entropic force near the horizon, and that the equations presented in section 3 are
exactly valid. He argued that one has to choose a location slightly away from the black hole
horizon at a distance of about the order of the Compton wave length, where we declare
that the particle and the black hole have become one system. Let us say this location
corresponds to choosing a holographic screen. The precise location of this screen can not
be important, however, since there is not a natural preferred distance that one can choose.
The equations should therefore not depend on small variations of this distance.
By pulling out the particle a bit further, one changes its energy by a small amount
equal to the work done by the gravitational force. If one then drops the particle into the
black hole, the mass M increases by this same additional amount. Consistency of the
– 23 –
JHEP04(2011)029
laws of black hole thermodynamics implies that the additional change in the Bekenstein
Hawking entropy, when multiplied with the Hawking temperature TH, must be precisely
equal to the work done by gravity. Hence,
Fgravity = TH
SBH
x . (6.1)
The derivative of the entropy is defined as the response of SBH due to a change in the
distance x of the particle to the horizon. This fact is surely known, and probably just
regarded as a consistency check. But let us take it one or two steps further.
Suppose we take the screen even further away from the horizon. The same argument
applies, but we can also choose to ignore the fact that the screen has moved, and lower
the particle to the location of the previous screen, the one closer to the horizon. This
process would happen in the part of space behind the new screen location, and hence it
should have a holographic representation on the screen. In this system there is force in
the perpendicular direction has no microscopic meaning, nor acceleration. The coordinate
x perpendicular to the screen is just some scale variable associated with the holographic
image of the particle. Its interpretation as an coordinate is a derived concept: this is what
it means have an emergent space.
The mass is defined in terms the energy associated with the particlefs holographic
image, which presumably is a near thermal state. It is not exactly thermal, however,
because it is still slightly away from the black hole horizon. We have pulled it out of
equilibrium, just like the polymer. One may then ask: what is the cause of the change
in energy that is holographically dual to the work done when in the emergent space we
gradually lower the particle towards the location of the old screen behind the new one
. Of course, this can be nothing else then an entropic effect, the force is simply due to
the thermalization process. We must conclude that the only microscopic explanation is
that there is an emergent entropic force acting. In fact, the correspondence rules between
the scale variable and energy on the one side, and the emergent coordinate x the mass m
on the other, must be such that F = T S translates into the gravitational force. It is
straightforward to see that this indeed works and that the equations for the temperature
and the entropy change are exactly as given in section 3.
The horizon is only a special location for observers that stay outside the black hole.
The black hole can be arbitrarily large and the gravitational force at its horizon arbitrarily
weak. Therefore, this thought experiment is not just teaching us about black holes. It
teaches us about the nature of space time, and the origin of gravity. Or more precisely, it
tells us about the cause of inertia. We can do the same thought experiment for a Rindler
horizon, and reach exactly the same conclusion. In this case the correspondence rules must
be such that F = T S translates into the inertial force F = ma. Again the formulas work
out as in section 3.
This brings us to a somewhat subtle and not yet fully understood aspect. Namely, the role
of ~. The previous arguments make clear that near the horizon the equations are valid with
~ identified with the actual Planck constant. However, we have no direct confirmation or
– 24 –
JHEP04(2011)029
proof that the same is true when we go away from the horizon, or eespecially when there
is no horizon present at all. In fact, there are reasons to believe that the equations work
slightly different there. The first is that one is not exactly at thermal equilibrium. Horizons
have well defined temperatures, and clearly are in thermal equilibrium. If one assumes that
the screen at an equipotential surface with = 0 is in equilibrium, the entropy needed
to get the Unruh temperature (3.4) is given by the Bekenstein-Hawking formula, including
the factor 1/4,
S =
c
3
4G~
Z
S
dA. (6.2)
This value for this entropy appears to be very high, and violates the Bekenstein bound [15]
that states that a system contained in region with radius R and total energy E can not
have an entropy larger than ER. The reason for this discrepancy may be that Bekensteinfs
argument does not hold for the holographic degrees of freedom on the screen, or because
of the fact that we are far from equilibrium.
But there may also be other ways to reconcile these statements, for example by making
use of the freedom to rescale the value of ~. This would not effect the final outcome for
the force, nor the fact that it is entropic. In fact, one can even multiply ~ by a function
f(0) of the Newton potential on the screen. This rescaling would affect the values of the
entropy and the temperature in opposite directions: T gets multiplied by a factor, while S
will be divided by the same factor. Since a priori we can not exclude this possibility, there
is something to be understood. In fact, there are even other modifications possible, like
a description that uses weighted average over many screens with different temperatures.
Even then the essence of our conclusions would not change, which is the fact that gravity
and inertia are entropic forces.
Does this view of gravity lead to predictions? The statistical average should give the
usual laws, hence one has to study the fluctuations in the gravitational force. Their size
depends on the effective temperature, which may not be universal and depends on the
effective value of ~. An interesting thought is that fluctuations may turn out to be more
pronounced for weak gravitational fields between small bodies of matter. But clearly, we
need a better understanding of the theory to turn this into a prediction.
It is well known that Newton was criticized by his contemporaries, especially by Hooke,
that his law of gravity acts at a distance and has no direct mechanical cause like the elastic
force. Ironically, this is precisely the reason why Hookefs elastic force is nowadays not seen
as fundamental, while Newtonfs gravitational force has maintained that status for more
than three centuries. What Newton did not know, and certainly Hooke didnft, is that the
universe is holographic. Holography is also an hypothesis, of course, and may appear just
as absurd as an action at a distance.
One of the main points of this paper is that the holographic hypothesis provides a
natural mechanism for gravity to emerge. It allows direct gcontacth interactions between
degrees of freedom associated with one material body and another, since all bodies inside a
volume can be mapped on the same holographic screen. Once this is done, the mechanisms
for Newtonfs gravity and Hookefs elasticity are surprisingly similar. We suspect that neither
of these rivals would have been happy with this conclusion.
– 25 –
JHEP04(2011)029
Acknowledgments
This work is partly supported by Stichting FOM. I like to thank J. de Boer, B. Chowdhuri,
R. Dijkgraaf, P. McFadden, G. ft Hooft, B. Nienhuis, J.-P. van der Schaar, and especially
and reproduction in any medium, provided the original author(s) and source are credited.
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