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Spatial Curvature and Thermodynamics

Narayan Banerjee1 , Purba Mukherjee2 and Diego Pavón3

1Department of Physical Sciences, Indian Institute of Science Education and Research, Mohanpur, West Bengal - 741246 India
2Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata - 700108, India
3Departamento de Física, Facultad de Ciencias, Universidad Autónoma de Barcelona, 08193 Bellaterra (Barcelona), Spain
Contact e-mail: [email protected]Contact e-mail: [email protected]Contact e-mail: [email protected]
(Accepted 2023 March 22. Received 2023 March 18; in original form 2023 January 23)
Abstract

Reasonable parametrizations of the current Hubble data set of the expansion rate of our homogeneous and isotropic universe, after suitable smoothing of these data, strongly suggest that the area of the apparent horizon increases irrespective of whether the spatial curvature of the metric is open, flat or closed. Put in another way, any sign of the spatial curvature appears consistent with the second law of thermodynamics.

keywords:
methods: data analysis – cosmological parameters – cosmology: observations – cosmology: theory
pubyear: ????pagerange: Spatial Curvature and ThermodynamicsSpatial Curvature and Thermodynamics

1 Introduction

Homogeneous and isotropic cosmological models are most aptly described by the Friedmann-Lemaître-Robertson-Walker (FLRW) space-time metric,

ds2=dt2+a2(t)[dr21kr2+r2(dθ2+sin2θdϕ2)].ds^{2}=-dt^{2}\,+a^{2}(t)\,\left[\frac{dr^{2}}{1-kr^{2}}\,+\,r^{2}\left(d\theta^{2}\,+\,\sin^{2}\theta d\phi^{2}\right)\right]\,. (1)

The spatial curvature index, k{1,0,1}k\in\{-1,0,1\}, indicates whether the spatial part of the metric is open (negatively curved, i.e., hyperbolic), flat, or closed (positively curved).

This constant index, like the scale factor a(t)a(t), is not a directly observable quantity. In principle, however, it can be determined through the knowledge of the spatial curvature density parameter, Ωkk/(a2H2)\Omega_{k}\equiv-k/(a^{2}H^{2}), which is accessible to observation, albeit indirectly. Recent estimates of the latter, assuming the universe correctly described by the Λ\LambdaCDM model only suggests that its present absolute value is small (Ωk0102\mid\Omega_{k0}\mid\sim 10^{-2} or less (Komatsu et al., 2011; Ade et al., 2014; Aghanim et al., 2020; Vagnozzi et al., 2021a; Vagnozzi et al., 2021b; Dhawan et al., 2021; Park & Ratra, 2019; Handley, 2021; Mukherjee & Banerjee, 2022; Bel et al., 2022; Akarsu et al., 2023)). More recent measurements, not based in the aforesaid model, hint that the universe may not be flat (i.e., k0k\neq 0) (Park & Ratra, 2019; Handley, 2021; Mukherjee & Banerjee, 2022; Bel et al., 2022). So, the sign of kk is rather uncertain.

Based on the history of the Hubble factor H(z)H(z), (where H=a˙/aH=\dot{a}/a ) it has been recently argued (Gonzalez-Espinoza & Pavón, 2019) that the universe is a thermodynamic system in the sense that it satisfies the second law of thermodynamics (the first law is guaranteed by Einstein equations while the third law may not apply). As we shall see soon, the possibilities k=+1k=+1 and k=0k=0 are consistent with the second law while this is not so obvious for the third possibility; in principle k=1k=-1 may or may not be compatible with the second law. The aim of our study is to resolve this uncertainty. To this end we shall resort to the 60 H(z)H(z) data currently available alongside their 1σ1\sigma confidence intervals, the parametrized graph of this history after smoothing the data set by a Gaussian Process (Rasmussen & Williams, 2005), the FLRW metric and the expression of the area of the apparent horizon (Eq. (2) below). As it turns out, the k=1k=-1 possibility (open spatial sections) appears also compatible with the second law of thermodynamics. The paper is organized as follows: In section 2 we write the second law at cosmic scales in terms of the deceleration parameter and Ωk\Omega_{k}. In section 3 we present the H(z)H(z) data set and the smoothing process. In section 4 we introduce four parametrizations of the Hubble factor and study whether they are compatible with the second law. In section 5 we consider the impact of the Hubble constant priors on our results. Finally, in section 6 we summarize our findings.

As usual, a subindex zero attached at any given quantity indicates that the quantity is to be evaluated at the present epoch. Likewise, we recall, for future convenience, that after fixing a0=1a_{0}=1, the redshift, zz, of any given luminous source is related to the corresponding scale factor by  1+z=a1\,1+z=a^{-1}. In our units c=G==1\,c=G=\hbar=1.

2 The second law

Table 1: Recent Hubble parameter compilation from cosmic chronometers.
zz H(z)H(z) [km Mpc-1 s-1] Ref.
0.09  69 ±\pm 12 Stern et al. (2010)
0.17  83 ±\pm 8
0.27  77 ±\pm 14
0.4  95 ±\pm 17
0.48  97 ±\pm 62
0.88  90 ±\pm 40
0.9 117 ±\pm 23
1.3 168 ±\pm 17
1.43 177 ±\pm 18
1.53 140 ±\pm 14
1.75 202 ±\pm 40
0.1797  75 ±\pm 4 Moresco et al. (2012)
0.1993  75 ±\pm 5
0.3519  83 ±\pm 14
0.5929 104 ±\pm 13
0.6797  92 ±\pm 8
0.7812 105 ±\pm 12
0.8754 125 ±\pm 17
1.037 154 ±\pm 20
0.07 69.0 ±\pm 19.6 Zhang et al. (2014)
0.12 68.6 ±\pm 26.2
0.2 72.9 ±\pm 29.6
0.28 88.8 ±\pm 36.6
1.363 160.0 ±\pm 33.6 Moresco (2015)
1.965 186.5 ±\pm 50.4
0.3802  83.0 ±\pm 13.5 Moresco et al. (2016)
0.4004  77.0 ±\pm 10.2
0.4247  87.1 ±\pm 11.2
0.4497  92.8 ±\pm 12.9
0.4783  80.9 ±\pm 9
0.47   89 ±\pm 49.6 Ratsimbazafy et al. (2017)
0.75   98.8 ±\pm 33.6 Borghi et al. (2022)

Given the strong connection between gravity and thermodynamics (Bekenstein, 1974, 1975; Hawking, 1974; Jacobson, 1995; Padmanabhan, 2005), it is natural to expect that the universe behaves as a normal thermodynamic system (Gonzalez-Espinoza & Pavón, 2019) whereby it must tend to a state of maximum entropy in the long run (Radicella & Pavon, 2012; Pavon & Radicella, 2013).

A basic standpoint is that the entropy of the universe is dominated by entropy of the cosmic horizon. In fact its entropy (10132kB\sim 10^{132}\rm{k_{B}}) exceeds by far the combined entropies of super-massive black holes, the cosmic microwave background radiation, the neutrino sea, etc (Egan & Lineweaver, 2010). As cosmic horizon, we take the apparent horizon rather than other possible choices, since the laws of thermodynamics are fulfilled on it (Wang et al., 2006). Its entropy (proportional to its area) is given by S𝒜=kBπr~𝒜2/p2\,S_{\cal A}=\rm{k_{B}}\pi\,\tilde{r}^{2}_{\cal A}/{\ell_{p}}^{2}\; (Bak & Rey, 2000; Cai, 2008), with r~𝒜=(H2+ka2)1/2\tilde{r}_{\cal A}=(H^{2}+ka^{-2})^{-1/2}\, as the radius of the horizon.

Obviously, the area of the apparent horizon,

𝒜=4πH2+ka2,{\cal A}=\frac{4\pi}{H^{2}\,+\,\frac{k}{a^{2}}}\,, (2)

depends on the Hubble factor and spatial curvature.

By the second law of thermodynamics S𝒜0S_{\cal A}^{\prime}\geq 0, thus

𝒜=𝒜28π2(HHka3)0HHka3,{\cal A}^{\prime}=-\frac{{\cal A}^{2}}{8\pi^{2}}\,\left(HH^{\prime}\,-\,\frac{k}{a^{3}}\right)\geq 0\quad\Rightarrow\quad HH^{\prime}\leq\frac{k}{a^{3}}\,, (3)

where the prime indicates d/dad/da.

The above inequality tells us: (i)(i) if HH^{\prime} is or has been positive at any stage of cosmic expansion (excluding, possibly, the pre-Planckian era), then k=+1k=+1, (ii)(ii) H<0H^{\prime}<0 may, in principle, be compatible with any sign of kk, and (iii)(iii) the possibilities k=+1k=+1 and k=0k=0 are consistent with the second law. In particular the data analysis carried out by the 2018 Planck mission produced the 99%\% probability region 0.095<Ωk0<0.007-0.095<\Omega_{k0}<-0.007 on the spatial curvature parameter (Aghanim et al., 2020). Note that this bound on Ωk0\Omega_{k0} is fully compatible with the second law because it corresponds to the possibility k=+1k=+1. However, the third possibility, k=1k=-1, may or may not be compatible.

Table 2: Recent Hubble parameter compilation from the radial BAO & galaxy clustering.
zz H(z)H(z) [km Mpc-1 s-1] rdfid{r_{d}}^{\text{fid}} [Mpc] Ref.
0.24 79.69 ±\pm 2.99 153.3 Gaztanaga et al. (2009)
0.34 83.8 ±\pm 3.66
0.43 86.45 ±\pm 3.97
0.44 82.6 ±\pm 7.8 - Blake et al. (2012)
0.6 87.9 ±\pm 6.1
0.73 97.3 ±\pm 7
0.3 81.7 ±\pm 6.22 152.76 Oka et al. (2014)
0.35 82.7 ±\pm 9.1 152.76 Chuang & Wang (2013)
0.57 96.8 ±\pm 3.4 147.28 Anderson et al. (2014)
0.31 78.17 ±\pm 4.74 147.74 Wang et al. (2017)
0.36 79.93 ±\pm 3.39
0.40 82.04 ±\pm 2.03
0.44 84.81 ±\pm 1.83
0.48 87.79 ±\pm 2.03
0.52 94.35 ±\pm 2.65
0.56 93.33 ±\pm 2.32
0.59 98.48 ±\pm 3.19
0.64 98.82 ±\pm 2.99
0.38 81.5 ±\pm 1.9 147.78 Alam et al. (2017)
0.51 90.4 ±\pm 1.9
0.61 97.3 ±\pm 2.1
0.978 113.72 ±\pm 14.63 147.78 Zhao et al. (2019)
1.23 131.44 ±\pm 12.42
1.526 148.11 ±\pm 12.71
1.944 172.63 ±\pm 14.79
2.33 224 ±\pm 8 147.33 Bautista et al. (2017)
2.34 222 ±\pm 7 147.7 Delubac et al. (2015)
2.36 226 ±\pm 8 147.49 Font-Ribera et al. (2014)

The inequality HHka3HH^{\prime}\leq\frac{k}{a^{3}} can be recast as

1+qΩk,1+q\geq\Omega_{k}\,, (4)

where q=a¨/(aH2)=(1+H˙H2)q=-\ddot{a}/(aH^{2})=-(1+\dot{H}H^{-2}) is the deceleration parameter.

Equation (4) expresses the second law of thermodynamics at cosmic scales (Gonzalez-Espinoza & Pavón, 2019).

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Figure 1: Contour plots for GP hyperparameter space and the comoving sound horizon at drag epoch whose radius, rdr_{d}, is measured in megaparsecs.

To see that it is perfectly reasonable, let us assume the universe dominated by a perfect fluid of energy density ρ\rho and hydrostatic pressure PP. The corresponding Einstein equations can be written as,

H2+ka2=8π3ρanda¨a=4π3(ρ+3P).H^{2}+\frac{k}{a^{2}}=\frac{8\pi}{3}\rho\qquad{\rm and}\qquad\frac{\ddot{a}}{a}=-\frac{4\pi}{3}(\rho+3P). (5)

If the fluid is dust (P=0P=0), one has q>0\,q>0, and these equations lead to Ωk=12q\,\Omega_{k}=1-2q.

If the second law holds, i.e., 1+qΩk1+q\geq\Omega_{k}, it follows that q0\,q\geq 0 which is consistent with the fact that a pressureless matter dominated universe decelerates (q>0q>0).

By contrast, should the second law not hold, 1+q<Ωk1+q<\Omega_{k}, the absurd result 0<q0<-q (namely, zero less than a negative quantity), would follow.

Likewise, if the equation of state of the fluid filling the universe were P=wρP=w\rho with w1\,w\geq-1 the expression 1+qΩk1+q\geq\Omega_{k} also proves to be consistent with the corresponding sign of the deceleration parameter and not so, if 1+q<Ωk1+q<\Omega_{k}. Values of ww lower that 1-1 correspond to phantom fields. As is well known these fields are unstable both classically (Dabrowski, 2015) and quantum mechanically111Should HH^{\prime} be positive, the FLRW universe could neither be flat nor open, just closed (k=+1k=+1) which would be puzzling in view of the current data that clearly allow for k=0k=0.(Cline et al., 2004).

Further, by combining the Friedmann equation in the case of a universe dominated by pressureless matter, the cosmological constant and spatial curvature with the acceleration equation (5.b), we obtain

a¨a(a˙a)2ka2=4πρm.\frac{\ddot{a}}{a}\,-\,\left(\frac{\dot{a}}{a}\right)^{2}\,-\frac{k}{a^{2}}=-4\pi\rho_{m}\,. (6)

The latter can be rewritten as

1+q=Ωk+32Ωm(Ωm=8πρm/(3H2)),1+q=\Omega_{k}+\textstyle{3\over{2}}\Omega_{m}\,\qquad\qquad(\Omega_{m}=8\pi\rho_{m}/(3H^{2})), (7)

which makes apparent the reasonableness of the expression  1+qΩk\,1+q\geq\Omega_{k}. Moreover, the above shows the compatibility of the said expression with general relativity.

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(a) M1

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(c) M3

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(b) M2

Figure 2: Contour plots for (a) first H(a)H(a) model parameters, (b) second H(a)H(a) model parameters, and (c) third H(a)H(a) model parameters, using different choices of the GP kernel, where HH_{\star} is in units of km Mpc-1 s-1.

3 Hubble data set and smoothing process

Our data set consists of: (i)(i) recent 32 cosmic chronometer (CC) H(z)H(z) measurements, presented in Table 1, which do not assume any particular cosmological model, and (ii)(ii) the 28 H(z)H(z) measurements from baryon acoustic oscillations (BAO) from different galaxy surveys, listed in Table 2. In both cases, the datasets are given with their 1σ1\sigma confidence interval. Because the BAO measurements are not entirely model-independent, particularly due to the assumption of a fiducial radius of the comoving sound horizon, rdfid{r_{d}}^{\text{fid}}, we adopted a full marginalization over the GP hyperparameter space (see below) with the comoving sound horizon at drag epoch rdr_{d} for the BAO data set as free parameter. This results in a model-independent Hubble data set from CC and the calibrated BAO.

Table 3: Parameter values for the first (M1) parametrization corresponding to each kernel, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
      k(a,a~)k(a,\tilde{a})       HH_{\star}       λ\lambda       H0H_{0}       q0q_{0}       ata_{t}
      Sq.Exp       41.9261.292+1.33241.926^{+1.332}_{-1.292}       0.5090.015+0.0150.509^{+0.015}_{-0.015}       69.7511.211+1.22969.751^{+1.229}_{-1.211}       0.4880.013+0.014-0.488^{+0.014}_{-0.013}       0.5090.509
      Mat.7/2       41.8181.311+1.34541.818^{+1.345}_{-1.311}       0.5100.016+0.0150.510^{+0.015}_{-0.016}       69.6221.267+1.27469.622^{+1.274}_{-1.267}       0.4870.014+0.014-0.487^{+0.014}_{-0.014}       0.5100.510
      Cauchy       41.8791.304+1.33941.879^{+1.339}_{-1.304}       0.5100.015+0.0150.510^{+0.015}_{-0.015}       69.7121.258+1.27369.712^{+1.273}_{-1.258}       0.4870.014+0.014-0.487^{+0.014}_{-0.014}       0.5100.510
      R.Quad       41.8931.303+1.34041.893^{+1.340}_{-1.303}       0.5090.015+0.0150.509^{+0.015}_{-0.015}       69.7221.260+1.28969.722^{+1.289}_{-1.260}       0.4880.014+0.014-0.488^{+0.014}_{-0.014}       0.5090.509
Table 4: Parameter values for the second (M2) parametrization, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
k(a,a~)k(a,\tilde{a}) HH_{\star} λ\lambda nn H0H_{0} q0q_{0} ata_{t}
Sq.Exp 49.1074.247+3.83549.107^{+3.835}_{-4.247} 0.3970.077+0.1040.397^{+0.104}_{-0.077} 1.8490.113+0.1131.849^{+0.113}_{-0.113} 68.6641.563+1.47768.664^{+1.477}_{-1.563} 0.4690.047+0.044-0.469^{+0.044}_{-0.047} 0.5560.556
Mat.7/2 48.9734.361+3.92748.973^{+3.927}_{-4.361} 0.4010.079+0.1080.401^{+0.108}_{-0.079} 1.8450.114+0.1151.845^{+0.115}_{-0.114} 68.6261.543+1.53868.626^{+1.538}_{-1.543} 0.4680.047+0.045-0.468^{+0.045}_{-0.047} 0.5550.555
Cauchy 44.4866.967+5.93444.486^{+5.934}_{-6.967} 0.5130.142+0.2320.513^{+0.232}_{-0.142} 1.7310.151+0.1521.731^{+0.152}_{-0.151} 67.3172.084+2.06367.317^{+2.063}_{-2.084} 0.4470.073+0.068-0.447^{+0.068}_{-0.073} 0.5670.567
R.Quad 49.3424.121+3.76249.342^{+3.762}_{-4.121} 0.3920.075+0.1000.392^{+0.100}_{-0.075} 1.8550.111+0.1121.855^{+0.112}_{-0.111} 68.6921.520+1.49468.692^{+1.494}_{-1.520} 0.4720.045+0.044-0.472^{+0.044}_{-0.045} 0.5540.554
Table 5: Parameter values for the third (M3) parametrization corresponding to each kernel, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
      k(a,a~)k(a,\tilde{a})       HH_{\star}       λ\lambda       H0H_{0}       q0q_{0}       ata_{t}
      Sq.Exp       74.6351.970+1.93874.635^{+1.938}_{-1.970}       4.2150.210+0.2164.215^{+0.216}_{-0.210}       74.7501.770+1.77274.750^{+1.772}_{-1.770}       0.8420.019+0.020-0.842^{+0.020}_{-0.019}       0.5460.546
      Mat.7/2       74.7981.964+1.92874.798^{+1.928}_{-1.964}       4.2370.212+0.2204.237^{+0.220}_{-0.212}       74.9171.721+1.79174.917^{+1.791}_{-1.721}       0.8470.018+0.020-0.847^{+0.020}_{-0.018}       0.5440.544
      Cauchy       74.7511.975+1.93174.751^{+1.931}_{-1.975}       4.2240.210+0.2214.224^{+0.221}_{-0.210}       74.8781.779+1.80674.878^{+1.806}_{-1.779}       0.8460.019+0.020-0.846^{+0.020}_{-0.019}       0.5450.545
      R.Quad       74.7351.978+1.92274.735^{+1.922}_{-1.978}       4.2250.210+0.2184.225^{+0.218}_{-0.210}       74.8621.752+1.76374.862^{+1.763}_{-1.752}       0.8460.019+0.020-0.846^{+0.020}_{-0.019}       0.5450.545
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Figure 3: Plots for H(a)H(a), in units of km Mpc-1 s-1, with their 1σ1\sigma, 2σ2\sigma and 3σ3\sigma confidence intervals vs aa for different choices of the GP kernel, where M1, M2 and M3 denote the first, second and third H(a)H(a) parametrizations, respectively.

As is apparent, a handful of H(z)H(z) data are afflicted by a rather large 1σ1\sigma confidence intervals whence some statistically founded smoothing process must be applied to the full data set to arrive to sensible results. This is why we resort to the machine-learning model Gaussian Process (GP) which infers a function from labelled training data (Rasmussen & Williams, 2005; Seikel et al., 2012), and reconstruct the Hubble diagram as a function of the scale factor. The said process is able to reproduce an ample range of behaviors with just a few parameters and allows a Bayesian interpretation (Zhao et al., 2008). Then, after smoothing the Hubble data set, we constrain the free parameters that enter the proposed parametric expressions (Eqs. (10), (13) and (15), below) of the history of the Hubble factor and check whether the corresponding curves, H(a)H(a), are consistent with the second law. That is to say, whether they comply with the inequality  1+qΩk\,1+q\geq\Omega_{k}.

To undertake the GP, we consider the squared exponential (SqExp hereafter), Matérn 7/2 (Mat72 hereafter), Cauchy and rational quadratic (R.Quad hereafter) covariance functions,

k(a,a~)={σf2exp((aa~)22l2) Sq.Exp,σf2exp(7|aa~|l)[1+7|aa~|l+14(aa~)25l2+77|aa~|315l3] Mat.72,σf2[l(aa~)2+l2] Cauchy,σf2[1+(aa~)22αl2]α R.Quad,\displaystyle k(a,\tilde{a})=\begin{cases}~{}~{}\sigma_{f}^{2}\exp\left(-\frac{(a-\tilde{a})^{2}}{2l^{2}}\right)&\text{$\cdots$ Sq.Exp},\\ ~{}~{}\sigma_{f}^{2}\exp\left(-\frac{7|a-\tilde{a}|}{l}\right)\left[1+\frac{7|a-\tilde{a}|}{l}+\frac{14\left(a-\tilde{a}\right)^{2}}{5l^{2}}+\frac{7\sqrt{7}|a-\tilde{a}|^{3}}{15l^{3}}\right]&\text{$\cdots$ Mat.72},\\ ~{}~{}\sigma_{f}^{2}\left[\frac{l}{(a-\tilde{a})^{2}+l^{2}}\right]&\text{$\cdots$ Cauchy},\\ ~{}~{}\sigma_{f}^{2}\left[1+\frac{(a-\tilde{a})^{2}}{2\alpha l^{2}}\right]^{-\alpha}&\text{$\cdots$ R.Quad},\end{cases} (8)

(also called “kernels") where σf\sigma_{f}, ll and α\alpha are the hyperparameters. Throughout this work, we assume a zero mean function to characterize the GP. We investigate if the different covariance functions lead to significant differences in the results222For details on GP, visit http://www.gaussianprocess.org.

We adopt a python implementation of the ensemble sampler for MCMC, the emcee333https://github.com/dfm/emcee, introduced by Foreman-Mackey et al. (2013). The two dimensional confidence contours showing the uncertainties along with the one dimensional marginalized posterior probability distributions, are shown in Fig. 1 with the help of the GetDist444https://github.com/cmbant/getdist module of python, developed by Lewis (2019).

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Figure 4: Plots for ζ\zeta with their 1σ1\sigma confidence interval vs aa for different choices of the GP kernel, where M1, M2 and M3 denotes the first, second and third H(a)H(a) parametrizations, respectively. Every single curve stays above of the observational upper bound of Ωk0\Omega_{k0}, 102\sim 10^{-2}, in the whole scale factor interval.

4 Parametrizations

In this section we study whether hyperbolic, i.e., open, spatial sections (which correspond to k=1k=-1) are compatible with the second law of thermodynamics as expressed by Eq, (4). To this end we consider three parametrizations (equations (10), (13) and (15), below) of the history of the Hubble factor and use the corresponding parameter values obtained after the smoothing of the Hubble data (tables 3, 4 and 5 for the first, second and third parametrizations, respectively555In these tables ata_{t} is the scale factor at which the transition from deceleration to acceleration occurs.). Figure 2 shows the contour plots of the different parameters occurring the three parametrizations. Then we check whether the corresponding curves, H(a)H(a), comply with the inequality (4). These curves are shown in Fig. 3.

We express Ωk\Omega_{k} as

Ωk=Ωk0(a0H0aH)2,\Omega_{k}=\Omega_{k0}\left(\frac{a_{0}\,H_{0}}{a\,H}\right)^{2}, (9)

with Ωk0102\Omega_{k0}\lesssim 10^{-2} the upper bound on the likely present value of the spatial curvature parameter assuming k=1k=-1, see Komatsu et al. (2011); Ade et al. (2014); Park & Ratra (2019); Handley (2021); Mukherjee & Banerjee (2022); Bel et al. (2022).

In the cases considered below HH(a)H_{\star}\equiv H(a\rightarrow\infty). The analysis of the fourth parametrization does not call for a numerical study.

Before going any further, it is worthwhile to note that since 0<Ωk=1<10<\Omega_{k=-1}<1 and that q>0q>0 (<0<0) when the universe is decelerating (accelerating), the said inequality cannot be violated when the universe is decelerating.

4.1 First parametrization

A reasonable and simple parametrization of the Hubble factor in an ever-expanding FLRW universe, regardless of the spatial curvature (M1 hereafter), is

H=Hexp(λ/a),H=H_{\star}\exp{(\lambda/a)}, (10)

where HH_{\star} and λ\lambda are free parameters to be fitted to the data by means of the GP method.

Since 1+q=λ/a1+q=\lambda/a there is deceleration when a<λa<\lambda and acceleration when a>λa>\lambda. On the other hand, recalling that Ωk\Omega_{k} is given by (9), and after setting a0=1a_{0}=1, Eq. (4) boils down to

λaΩk0exp[2λ(a1a)]a2,\frac{\lambda}{a}\geq\Omega_{k0}\,\frac{\exp{[2\lambda(\frac{a-1}{a}})]}{a^{2}}\,, (11)

which can be rewritten as

ζ M1=λaexp[2λ(1a1)]Ωk0.\zeta_{\text{ M1}}=\lambda\,a\exp\left[2\lambda\left(\frac{1}{a}-1\right)\right]\geq\Omega_{k0}. (12)

Using the best fit values of HH_{\star} and λ\lambda, shown in Table 3 corresponding to each kernel, we find that ζM1\zeta_{\text{M1}} stays above Ωk0\Omega_{k0} in the full range, (0.3,1)\,(0.3,1), of the scale factor covered by the data as shown in Fig. 4. Thus Eq. (12) is satisfied, i.e., the curve H(a)H(a) of the first parametrization respects, by a comfortable margin, the second law of thermodynamics also if k=1k=-1.

4.2 Second parametrization

A somewhat less simple parametrization (M2 hereafter) is

H=H(1+λan).H=H_{\star}(1+\lambda a^{-n})\,. (13)

This one contains three free parameters, namely, HH_{\star}, λ\lambda and nn, to be fitted to the data. Proceeding as before we can write,

ζ M2=λ(λ+an)[(1+λ)an1]2Ωk0.\zeta_{\text{ M2}}=\lambda\frac{\left(\lambda+a^{n}\right)}{\left[\left(1+\lambda\right)a^{n-1}\right]^{2}}\geq\Omega_{k0}. (14)

Using the best fit values of λ\lambda and nn displayed in table 4 we see, as Fig. 4 shows, that last equation is fulfilled (and therefore Eq. (4)) by an ample margin in the whole interval of the scale factor currently observationally accessible. Again, the second law is respected even if k=1k=-1.

4.3 Third parametrization

Similarly, consider the expression (M3 hereafter) for the Hubble rate

H(a)=H1exp(λa2),H(a)=\frac{H_{\star}}{1-\exp(-\lambda a^{2})}, (15)

where HH_{\star} and λ\lambda are free parameter to be fit to the data.

Proceeding as in the previous cases from equations (4) and (9) we obtain

ζM3=2λ(1exp(λ))2a4(1exp(λa2))3Ωk0.\zeta_{\text{M3}}=2\,\frac{\lambda(1-\exp(-\lambda))^{2}a^{4}}{(1-\exp(-\lambda a^{2}))^{3}}\geq\Omega_{k0}. (16)

As before, resorting to the best fit values of the free parameters as given in table 5 it is seen, that the above equation is satisfied (and consequently Eq. (4) as well) by a generous margin in the whole interval of the scale factor observationally accessible, as shown in Fig. 4. Once again, the second law is respected even if k=1k=-1.

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(a) M1

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(c) M3

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(b) M2

Figure 5: Contour plots for (a) first H(a)H(a) model parameters, (b) second H(a)H(a) model parameters, and (c) third H(a)H(a) model parameters, using P20, F21 and R22 H0H_{0} values as priors, where HH_{\star} is in units of km Mpc-1 s-1.
Table 6: Parameter values for the first (M1) parametrization corresponding to the three H0H_{0} values as priors, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
      Prior       HH_{\star}       λ\lambda       H0H_{0}       q0q_{0}       ata_{t}
      P       39.9270.566+0.57939.927^{+0.579}_{-0.566}       0.5290.010+0.0100.529^{+0.010}_{-0.010}       67.7780.458+0.46667.778^{+0.466}_{-0.458}       0.4680.010+0.010-0.468^{+0.010}_{-0.010}       0.5290.529
      F       42.1111.058+1.07842.111^{+1.078}_{-1.058}       0.5080.013+0.0130.508^{+0.013}_{-0.013}       69.9651.001+1.01369.965^{+1.013}_{-1.001}       0.4890.012+0.012-0.489^{+0.012}_{-0.012}       0.5080.508
      R       44.1440.910+0.92844.144^{+0.928}_{-0.910}       0.4880.012+0.0120.488^{+0.012}_{-0.012}       71.9370.795+0.79771.937^{+0.797}_{-0.795}       0.5090.012+0.011-0.509^{+0.011}_{-0.012}       0.4890.489
Table 7: Parameter values for the second (M2) parametrization corresponding to the three H0H_{0} values as priors, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
Prior HH_{\star} λ\lambda nn H0H_{0} q0q_{0} ata_{t}
P 47.1052.408+2.21647.105^{+2.216}_{-2.408} 0.4260.058+0.0700.426^{+0.070}_{-0.058} 1.7760.083+0.0831.776^{+0.083}_{-0.083} 67.1940.500+0.47767.194^{+0.477}_{-0.500} 0.4650.030+0.031-0.465^{+0.031}_{-0.030} 0.5360.536
F 46.9484.774+4.25646.948^{+4.256}_{-4.774} 0.4280.095+0.1330.428^{+0.133}_{-0.095} 1.7740.121+0.1231.774^{+0.123}_{-0.121} 67.0811.379+1.32167.081^{+1.321}_{-1.379} 0.4640.051+0.054-0.464^{+0.054}_{-0.051} 0.5350.535
R 58.3302.607+2.41758.330^{+2.417}_{-2.607} 0.2190.036+0.0430.219^{+0.043}_{-0.036} 2.0900.108+0.1112.090^{+0.111}_{-0.108} 71.1260.917+0.90471.126^{+0.904}_{-0.917} 0.6190.033+0.034-0.619^{+0.034}_{-0.033} 0.5040.504
Table 8: Parameter values for the third (M3) parametrization corresponding to the three H0H_{0} values as priors, where HH_{\star} and H0H_{0} are in units of km Mpc-1 s-1.
      Prior       HH_{\star}       λ\lambda       H0H_{0}       q0q_{0}       ata_{t}
      P       65.8240.590+0.58965.824^{+0.589}_{-0.590}       3.4270.091+0.0943.427^{+0.094}_{-0.091}       68.0320.483+0.47768.032^{+0.477}_{-0.483}       0.7580.016+0.015-0.758^{+0.015}_{-0.016}       0.6050.605
      F       71.4441.402+1.39371.444^{+1.393}_{-1.402}       3.9090.152+0.1583.909^{+0.158}_{-0.152}       72.9251.245+1.23072.925^{+1.230}_{-1.245}       0.8300.019+0.017-0.830^{+0.017}_{-0.019}       0.5670.567
      R       72.7221.009+1.01472.722^{+1.014}_{-1.009}       4.0370.130+0.1364.037^{+0.136}_{-0.130}       74.0250.901+0.91474.025^{+0.914}_{-0.901}       0.8450.014+0.014-0.845^{+0.014}_{-0.014}       0.5580.558
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Figure 6: Plots for H(a)H(a), in units of km Mpc-1 s-1, with their 1σ1\sigma, 2σ2\sigma and 3σ3\sigma confidence intervals vs aa using P20, F21 and R22 H0H_{0} values as priors (from left to right), where M1, M2 and M3 denotes the first, second and third H(a)H(a) parametrizations, repectively.
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Figure 7: Plots for ζ\zeta with their 1σ1\sigma confidence interval vs aa using P20, F21 and R22 H0H_{0} values as priors (from left to right), where M1, M2 and M3 denote the first, second and third H(a)H(a) parametrizations, respectively.

4.4 Fourth parametrization

Consider the expression for the Hubble factor inspired in the Λ\LambdaCDM model

H(a)=H0Ωm0a3+Ωk0a2+ΩΛ,H(a)=H_{0}\sqrt{\Omega_{m0}\,a^{-3}\,+\,\Omega_{k0}\,a^{-2}\,+\,\Omega_{\Lambda}}, (17)

where H0H_{0}, Ωm0\Omega_{m0} and ΩΛ\Omega_{\Lambda} are free parameters. Following parallel steps to the previous cases, we write ζ M4=12(3Ωm0a1+ 2Ωk0)Ωk0\,\zeta_{\text{ M4}}=\textstyle{1\over{2}}\,(3\Omega_{m0}\,a^{-1}\,+\,2\Omega_{k0})\geq\Omega_{k0}, that is to say

ζ M4=32Ωm0a10.\zeta_{\text{ M4}}=\textstyle{3\over{2}}\Omega_{m0}\,a^{-1}\geq 0. (18)

It is immediately seen that Eq. (4) is satisfied for whatever value of the scale factor and consequently the second law as well.

5 Effect of H0H_{0} priors

We further examine to what extent (if at all) the rising tension between the local measurements of the Hubble constant (Riess et al., 2022; Freedman, 2021), and its inferred values via an extrapolation of data on the early universe (Aghanim et al., 2020) affects our results.

To this end we consider (i)(i) the local measurements by the SH0ES team [H0R22H_{0}^{\text{R22}} = 73.3±1.0473.3\pm 1.04 km Mpc-1 s-1 (R hereafter)], (ii)(ii) the updated TRGB calibration from the Carnegie Supernova Project [H0F21H_{0}^{\text{F21}} = 69.8±1.769.8\pm 1.7 km Mpc-1 s-1 (F hereafter)], and (iii)(iii) the inferred value via an extrapolation of data on the early universe by the Planck survey [H0P20H_{0}^{\text{P20}} = 67.4±0.567.4\pm 0.5 km Mpc-1 s-1 (P hereafter)], respectively. We assume Gaussian prior distributions with the mean and variances corresponding to the best-fit and 1σ1\sigma confidence interval reported about H0H_{0} values.

Fig. 5 shows the contour plots of the different parameters occurring in the three parametrizations, on assuming these H0H_{0} values. The constraints on the parameter values are given in Tables 6, 7, and 8, for the first, second and third parametrizations. The corresponding H(a)H(a) and ζ\zeta curves are shown in Figs. 6 and 7, respectively.

We can conclude this section by saying that our overall result, that the constrain 1+qΩk1+q\geq\Omega_{k} is satisfied even if k=1k=-1, is not affected whether we take the H0H_{0} value from the local measurements or the one obtained from extrapolating the precise data drawn from the cosmic microwave background radiation.

6 Concluding remarks

The second law of thermodynamics applied to our expanding FLRW universe implies that the area of its apparent horizon cannot decrease, i.e., 𝒜0{\cal A}^{\prime}\geq 0. This, in its turn, dictates HHk/a3HH^{\prime}\leq k/a^{3}. Since in absence of phantom fields, which are unstable, H<0H^{\prime}<0 leads to two possibilities, namely, k=0k=0 and k=+1k=+1, result immediately compatible with the second law. The third possibility, k=1k=-1, may or may not be compatible with it. Here we resorted to the set of observational data regarding the evolution of the Hubble factor to discern whether the said law is satisfied when k=1k=-1. So, with the help of the non-parametric Gaussian Process we smoothed the set of 6060 currently available data of the Hubble factor and introduced four different parametrizations of the ensuing curve, H(a)H(a). After using the latter to constrain the free parameters entering the first three parametrizations (the fourth one was not in need of a numerical study), we examined whether the resulting expressions, with the curvature index kk fixed to 1-1, satisfy Eq. (4). As it turned out, all of them did (Fig. 4 and Eq. (18)). Further, a quick inspection of the said expressions shows that they also comply with Eq. (4) in the limit aa\rightarrow\infty. Therefore, we are led to conclude that the evolution of FLRW universes with open spatial sections does not appear to conflict with the second law of thermodynamics. Regrettably, a final verdict cannot be attained at this stage since currently we have no cosmological model that deserves our unreserved confidence. In fact, the most reliable model, the so-called “concordance model", is afflicted by some drawbacks whose relevance may not be small (Perivolaropoulos & Skara, 2022; Di Valentino, 2022). This is why we did resort to parametrize the Hubble factor rather than taking it from any given model.

One may argue that this conclusion could be reached from Eq.(7) straightaway. However this is not so because that equation only concerns the adiabatic evolution of the fluid that sources the gravitational field. Further, the second law does not enter its derivation whereby it cannot be ascertained whether it is respected or violated.

Acknowledgments

PM thanks ISI Kolkata for financial support through Research Associateship.

Data Availability

Authors can confirm that all relevant source data are included in the article. The data sets generated during and/or analysed during this study are available from the corresponding author on reasonable request.

References