Machine learning meets the redshift evolution of the CMB temperature

Arjona, Rubén

doi:10.1088/1475-7516/2020/08/009

Cited by 38 publications

(21 citation statements)

References 88 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, we can say that the Van-der-Waals equation of state provides the similar results as obtained from dark energy models. Experimental evidences of accelerated universe support our obtained results [56][57][58][59][60]62].…”

Section: In Appendix Equation (A10)]supporting

confidence: 87%

Thermodynamic analysis for Non-linear system (Van-der-Waals EOS) with viscous cosmology

2021

View full text Add to dashboard Cite

The following paper is motivated by the recent works of Kremer [Gen Relativ Gravit 36(6):1423–1432, 2004; Phys Rev D 68(12):123507, 2003], Vardiashvili (Inflationary constraints on the van Der Waals equation of state, arXiv:1701.00748, 2017), Jantsch (Int J Mod Phys D 25(03):1650031, 2016), Capozziello (Phys Lett A 299(5–6):494–498, 2002) on Van-Der-Waals EOS cosmology. The main aim of this paper is to analyze the thermodynamics of a Non-linear system which in this case is Van-Der-Waals fluid EOS (Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003). We have investigated the Van-Der-Waals fluid system with the generalized EOS as $$p=w\left( \rho ,t \right) \rho +f\left( \rho \right) -3\eta \left( H,t \right) H$$ p = w ρ , t ρ + f ρ - 3 η H , t H (Brevik et al., Int J Geom Methods Mod Phys 15(09):1850150, 2018). The third term signifies viscosity which has been considered as an external parameter that only modifies pressure but not the density of the liquid. The $$w(\rho ,t)$$ w ( ρ , t ) and $$f(\rho )$$ f ( ρ ) are the two functions of energy density and time that are different for the 3 types of Vander Waal models namely one parameter model, two parameters model and three parameters model (Ivanov and Prodanov, Eur Phys J C 79(2):118, 2019; Elizalde and Khurshudyan, Int J Mod Phys D 27(04):1850037, 2018). The value of EOS parameter ($$w_{EOS})$$ w EOS ) (Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003; Obukhov and Timoshkin, Russ Phys J 60(10):1705–1711, 2018) will showdifferent values for different models. We have studied the changes in the parameters for different cosmic phases [Kremer, Phys Rev D 68(12):123507, 2003; Capozziello et al., Phys Lett A 299(5–6):494–498, 2002; Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003]. We have also studied the thermodynamics and the stability conditions for the three models in viscous condition [Obukhov and Timoshkin, Russ Phys J 60(10):1705–1711, 2018; Panigrahi and Chatterjee, Gen Relativ Gravit 49(3):35, 2017; Panigrahi and Chatterjee, J Cosmol Astropart Phys 2016(05):052, 2016; Chakraborty et al., Evolution of FRW Universe in Variable Modified Chaplygin Gas Model, arXiv:1906.12185, 2019]. We have discussed the importance of viscosity (Brevik and Grøn, Astrophys Space Sci 347(2):399–404, 2013) in explaining accelerating universe with negative pressure (Panigrahi and Chatterjee, Gen Relativ Gravit 49(3):35, 2017).Finally, we have resolved the finite time future singularity problems [Brevik et al., The effect of thermal radiation on singularities in the Dark Universe, arXiv:2103.08430, 2021; Odintsov and Oikonomou, Phys Rev D 98(2):024013, 2018; Odintsov and Oikonomou, Int J Mod Phys D 26(08):1750085, 2017; Frampton et al., Phys Rev D 85(8):083001, 2012; Frampton et al., Phys Lett B 708(1–2):204–211, 2012; Frampton et al., Phys Rev D 84(6):063003, 2011] and discussed the thermodynamics energy conditions [Visser and Barcelo, Energy conditions and their cosmological implications. In: Cosmo-99, pp 98–112, 2000; Chattopadhyay et al., Eur Phys J C 74(9):1–13, 2014; Arora et al., Phys. Dark Universe 31:100790, 2021; Sharma and Pradhan, Int J Geom Methods Mod Phys 15(01):1850014, 2018; Sahoo et al., AstronomischeNachrichten 342(1–2):89–95, 2021; Yadav et al., Mod Phys Lett A 34(19):1950145, 2019; Sharma et al., Int J Geom Methods Mod Phys 17(07):2050111, 2020, Moraes and Sahoo, Eur Phys J C 77(7):1–8, 2017; Hulke et al., New Astron 77:101357, 2020; Singla et al., Gravit Cosmol 26(2):144–152, 2020; Sharif et al., Eur Phys J Plus 128(10):1–11, 2013] with those models.

show abstract

Section: In Appendix Equation (A10)]supporting

confidence: 87%

Thermodynamic analysis for Non-linear system (Van-der-Waals EOS) with viscous cosmology

2021

View full text Add to dashboard Cite

show abstract

“…The GA have been used extensively to test for extensions of the standard model (Akrami et al 2010), deviations from the cosmological constant model, both at the background and the perturbations level (Nesseris & Garcia-Bellido 2012;Arjona & Nesseris 2020a,b), to reconstruct a plethora of cosmological data, such as type Ia supernovae or CMB Bogdanos & Nesseris (2009), Arjona (2020) or to reconstruct various null tests such as the so called Om statistic or the curvature test (Nesseris & Shafieloo 2010;Nesseris & Garcia-Bellido 2013a;Sapone et al 2014).…”

Section: Genetic Algorithm Analysismentioning

confidence: 99%

Euclid: Constraining dark energy coupled to electromagnetism using astrophysical and laboratory data

Martinelli

Martins

Nesseris

et al. 2021

A&A

View full text Add to dashboard Cite

In physically realistic, scalar-field-based dynamical dark energy models (including, e.g., quintessence), one naturally expects the scalar field to couple to the rest of the model’s degrees of freedom. In particular, a coupling to the electromagnetic sector leads to a time (redshift) dependence in the fine-structure constant and a violation of the weak equivalence principle. Here we extend the previous Euclid forecast constraints on dark energy models to this enlarged (but physically more realistic) parameter space, and forecast how well Euclid, together with high-resolution spectroscopic data and local experiments, can constrain these models. Our analysis combines simulated Euclid data products with astrophysical measurements of the fine-structure constant, α, and local experimental constraints, and it includes both parametric and non-parametric methods. For the astrophysical measurements of α, we consider both the currently available data and a simulated dataset representative of Extremely Large Telescope measurements that are expected to be available in the 2030s. Our parametric analysis shows that in the latter case, the inclusion of astrophysical and local data improves the Euclid dark energy figure of merit by between 8% and 26%, depending on the correct fiducial model, with the improvements being larger in the null case where the fiducial coupling to the electromagnetic sector is vanishing. These improvements would be smaller with the current astrophysical data. Moreover, we illustrate how a genetic algorithms based reconstruction provides a null test for the presence of the coupling. Our results highlight the importance of complementing surveys like Euclid with external data products, in order to accurately test the wider parameter spaces of physically motivated paradigms.

show abstract

“…It is worth mentioning that the GA have been applied in the field of cosmology for several reconstructions on a wide range of data, see for example Refs. [17,30,40,[50][51][52][53][54][55][56][57][58][59]. Other applications of the GA have been used for particle physics [60][61][62], astronomy and astrophysics [63][64][65].…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Testing the $Λ$CDM paradigm with growth rate data and machine learning

Arjona,

Melchiorri,

Nesseris

2021

Preprint

Self Cite

View full text Add to dashboard Cite

The cosmological constant Λ and cold dark matter (CDM) model (ΛCDM) is one of the pillars of modern cosmology and is widely used as the de facto theoretical model by current and forthcoming surveys. As the nature of dark energy is very elusive, in order to avoid the problem of model bias, here we present a novel null test at the perturbation level that uses the growth of matter perturbation data in order to assess the concordance model. We analyze how accurate this null test can be reconstructed by using data from forthcoming surveys creating mock catalogs based on ΛCDM and three models that display a different evolution of the matter perturbations, namely a dark energy model with constant equation of state w (wCDM), the Hu & Sawicki and designer f (R) models, and we reconstruct them with a machine learning technique known as the Genetic Algorithms. We show that with future LSST-like mock data our consistency test will be able to rule out these viable cosmological models at more than 5σ, help to check for tensions in the data and alleviate the existing tension of the amplitude of matter fluctuations S8 = σ8 (Ωm/0.3) 0.5 .

show abstract

Machine learning meets the redshift evolution of the CMB temperature

Cited by 38 publications

References 88 publications

Thermodynamic analysis for Non-linear system (Van-der-Waals EOS) with viscous cosmology

Thermodynamic analysis for Non-linear system (Van-der-Waals EOS) with viscous cosmology

Euclid: Constraining dark energy coupled to electromagnetism using astrophysical and laboratory data

Testing the $Λ$CDM paradigm with growth rate data and machine learning

Contact Info

Product

Resources

About