Testing f(R) gravity models with quasar X-ray and UV fluxes

Leizerovich, Matías; Kraiselburd, Lucila; Landau, Susana J.; Scóccola, Claudia G.

doi:10.48550/arxiv.2112.01492

Cited by 3 publications

(6 citation statements)

References 56 publications

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“…Let us now compare our results with similar ones published in the literature such as for example the ones performed in [51,62] where the same data sets of CC and SNeIa were considered. First, we note that the estimates in [62] for the b parameter are smaller than the ones obtained in this work, while an excellent agreement is found with the results of [51]. The reason for this is the following: due to the computational instabilities of Eqs.…”

Section: Resultsmentioning

confidence: 61%

“…In this work, we use the mean values estimated by the Pantheon compilation [24] (α = 0.0154 ± 0.06, β = 3.02 ± 0.06, γ = 0.053 ± 0.009) where a ΛCDM model is assumed. These values have been verified by two independent analyses with alternative cosmological models: the one in [51] where the f (R) Hu-Sawicky model is assumed and the one in [52] performed in the context of the MOdified Gravity theory (MOG). To perform the statistical analysis, we compare the value of µ obtained from the data using Eq.…”

Section: B Supernovae Iamentioning

confidence: 76%

“…no computational instabilities in the ANN method and a wider region can be explored. On the other hand, in [51], the series expansion is only used for b < 0.2 and a numerical integration is performed for other values of b allowing for a complete exploration of the parameter space. Besides, there is also excellent agreement between this work and the results of [51] when the BAO data are included in the statistical analysis.…”

Section: Resultsmentioning

confidence: 99%

“…On the other hand, in [51], the series expansion is only used for b < 0.2 and a numerical integration is performed for other values of b allowing for a complete exploration of the parameter space. Besides, there is also excellent agreement between this work and the results of [51] when the BAO data are included in the statistical analysis. Furthermore, we also note that our estimates for the b parameter are in agreement within 1σ with the ones of another analysis performed in [62], where data from six systems of strongly lensed quasars analyzed by the HOLICOW Collaboration [67] are added to the previous ones (CC+SNeIa).…”

Section: Resultsmentioning

confidence: 99%

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Cosmology-informed neural networks to solve the background dynamics of the Universe

Chantada¹,

Landau²,

Protopapas³

et al. 2022

Preprint

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The field of machine learning has drawn increasing interest from various other fields due to the success of its methods at solving a plethora of different problems. An application of these has been to train artificial neural networks to solve differential equations without the need of a numerical solver. This particular application offers an alternative to conventional numerical methods, with advantages such as lower memory required to store the solutions, parallelization, and in some cases less overall computational cost than its numerical counterparts. In this work, we train artificial neural networks to represent a bundle of solutions of the differential equations that govern the background dynamics of the Universe for four different models. The models we have chosen are ΛCDM, the Chevallier-Polarski-Linder parametric dark energy model, a quintessence model with an exponential potential, and the Hu-Sawicki f (R) model. We used the solutions that the networks provide to perform statistical analyses to estimate the values of each model's parameters with observational data; namely, estimates of the Hubble parameter from Cosmic Chronometers, the Supernovae type Ia data from the Pantheon compilation, and measurements from Baryon Acoustic Oscillations. The results we obtain for all models match similar estimations done in the literature using numerical solvers. In addition, we estimated the error of the solutions by comparing them to the analytical solution when there is one, or to a high-precision numerical solution when there is not. Through those estimations we found that the error of the solutions was at most ∼ 1% in the region of the parameter space that concerns the 95% confidence regions that we found using the data, for all models and all statistical analyses performed in this work.

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Section: Resultsmentioning

confidence: 61%

Section: B Supernovae Iamentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Cosmology-informed neural networks to solve the background dynamics of the Universe

Chantada¹,

Landau²,

Protopapas³

et al. 2022

Preprint

Self Cite

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“…Farooq et al 2017;Scolnic et al 2018;Planck Collaboration 2020;eBOSS Collaboration 2021). The measurements, however, are not yet decisive enough (see, surements that reach to z ∼ 7.5 (Risaliti & Lusso 2015Khadka & Ratra 2020a,b, 2021Lusso et al 2020;Zhao & Xia 2021;Rezaei et al 2022;Luongo et al 2021;Leizerovich et al 2021;Colgáin et al 2022;Dainotti et al 2022a), 1 and -the main subject of our paper -gamma-ray burst (GRB) observations that reach to z ∼ 8.2 (Cardone et al 2009(Cardone et al , 2010Samushia & Ratra 2010;Dainotti et al 2013;Postnikov et al 2014;Wang et al 2015Wang et al , 2016Dainotti & Del Vecchio 2017;Dainotti & Amati 2018;Wang et al 2022;Fana Dirirsa et al 2019;Amati et al 2019;Khadka & Ratra 2020c;Hu et al 2021;Demianski et al 2021;Khadka et al 2021b;Luongo et al 2021;Luongo & Muccino 2021;Cao et al 2021a;Liu et al 2022). In this paper the highest redshift GRB we use is at z = 9.4 (Cucchiara et al 2011), but GRBs might be detectable to z = 20 (Lamb & Reichart 2000).…”

Section: Introductionmentioning

confidence: 85%

Gamma-ray burst data strongly favor the three-parameter fundamental plane (Dainotti) correlation relation over the two-parameter one

Cao¹,

Dainotti²,

Ratra³

2022

Preprint

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Gamma-ray bursts (GRBs), observed to redshift z = 9.4, are potential probes of the largely unexplored z ∼ 2.7 − 9.4 part of the early Universe. Thus, finding relevant relations among GRB physical properties is crucial. We find that the Platinum GRB data compilation, with 50 long GRBs (with relatively flat plateaus and no flares) in the redshift range 0.553 ≤ z ≤ 5.0, and the LGRB95 data compilation, with 95 long GRBs in 0.297 ≤ z ≤ 9.4, as well as the 145 GRB combination of the two, strongly favor the three-dimensional (3D) fundamental plane (Dainotti) correlation relation (between the peak prompt lumininosity, the luminosity at the end of the plateau emission, and its rest frame duration) over the two-dimensional one (between the luminosity at the end of the plateau emission and its duration). The 3D Dainotti correlations in the three data sets are standardizable. We find that while LGRB95 data have ∼ 50% larger intrinsic scatter parameter values than the better-quality Platinum data, they provide somewhat tighter constraints on cosmological-model and GRB-correlation parameters, perhaps solely due to the larger number of data points, 95 versus 50. This suggests that when compiling GRB data for the purpose of constraining cosmological parameters, given the quality of current GRB data, intrinsic scatter parameter reduction must be balanced against reduced sample size.

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Unveiling the Universe with emerging cosmological probes

et al. 2022

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The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave Background, Supernovae Type Ia, Baryon Acoustic Oscillations) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most importantly, to increase the accuracy and robustness of our results. This review is meant to provide a state-of-art benchmark of the latest advances in emerging “beyond-standard” cosmological probes. We present how several different methods can become a key resource for observational cosmology. In particular, we review cosmic chronometers, quasars, gamma-ray bursts, standard sirens, lensing time-delay with galaxies and clusters, cosmic voids, neutral hydrogen intensity mapping, surface brightness fluctuations, stellar ages of the oldest objects, secular redshift drift, and clustering of standard candles. The review describes the method, systematics, and results of each probe in a homogeneous way, giving the reader a clear picture of the available innovative methods that have been introduced in recent years and how to apply them. The review also discusses the potential synergies and complementarities between the various probes, exploring how they will contribute to the future of modern cosmology.

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Testing f(R) gravity models with quasar X-ray and UV fluxes

Abstract: 1 There is also no agreement within the scientific community of the amount of this tension. While some authors claim that there is a 4 − σ tension [9], others claim lower amounts or even no disagreements [10,11].

Cited by 3 publications

References 56 publications

Cosmology-informed neural networks to solve the background dynamics of the Universe

Cosmology-informed neural networks to solve the background dynamics of the Universe

Gamma-ray burst data strongly favor the three-parameter fundamental plane (Dainotti) correlation relation over the two-parameter one

Unveiling the Universe with emerging cosmological probes

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