Checking the second law at cosmic scales

Banerjee, Narayan; Mukherjee, Purba; Pavón, Diego

doi:10.1088/1475-7516/2023/11/092

J. Cosmol. Astropart. Phys.

2023

DOI: 10.1088/1475-7516/2023/11/092

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Checking the second law at cosmic scales

Narayan Banerjee,

Purba Mukherjee,

Diego Pavón

Abstract: Based on recent data about the history of the Hubble factor, it is argued that the second law of thermodynamics holds at the largest scales accessible to observation. This is consistent with previous studies of the same question.

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2024

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Cited by 6 publications

References 44 publications

(47 reference statements)

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A possible late-time transition of M _B inferred via neural networks

Mukherjee,

Dialektopoulos,

Said

et al. 2024

J. Cosmol. Astropart. Phys.

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The strengthening of tensions in the cosmological parameters has led to reconsidering the fundamental aspects of standard cosmology. The tension in the Hubble constant can also be viewed as a tension between local and early Universe constraints on the absolute magnitude M B of Type Ia supernova. In this work, we reconsider the possibility of a variation of this parameter in a model-independent way. We employ neural networks to agnostically constrain the value of the absolute magnitude as well as assess the impact and statistical significance of a variation in M B with redshift from the Pantheon+ compilation, together with a thorough analysis of the neural network architecture. We find an indication for a possible transition redshift at the z ≈ 1 region.

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A possible late-time transition of M _B inferred via neural networks

Mukherjee,

Dialektopoulos,

Said

et al. 2024

J. Cosmol. Astropart. Phys.

View full text Add to dashboard Cite

show abstract

Model-independent cosmological inference post DESI DR1 BAO measurements

Mukherjee,

Sen

2024

Phys. Rev. D

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Analytical Gaussian process cosmography: unveiling insights into matter-energy density parameter at present

Dinda

2024

Eur. Phys. J. C

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In this study, we introduce a novel analytical Gaussian Process (GP) cosmography methodology, leveraging the differentiable properties of GPs to derive key cosmological quantities analytically. Our approach combines cosmic chronometer (CC) Hubble parameter data with growth rate (f) observations to constrain the $$\Omega _{\textrm{m0}}$$ Ω m0 parameter, offering insights into the underlying dynamics of the Universe. By formulating a consistency relation independent of specific cosmological models, we analyze under a flat FLRW metric and first-order Newtonian perturbation theory framework. Our analytical approach simplifies the process of Gaussian Process regression (GPR), providing a more efficient means of handling large datasets while offering deeper interpretability of results. We demonstrate the effectiveness of our methodology by deriving precise constraints on $$\Omega _{\textrm{m0}}h^2$$ Ω m0 h 2 , revealing $$\Omega _\textrm{m0}h^2=0.139\pm 0.017$$ Ω m0 h 2 = 0.139 ± 0.017 . Moreover, leveraging $$H_0$$ H 0 observations, we further constrain $$\Omega _{\textrm{m0}}$$ Ω m0 , uncovering an inverse correlation between mean $$H_0$$ H 0 and $$\Omega _{\textrm{m0}}$$ Ω m0 . Our investigation offers a proof of concept for analytical GP cosmography, highlighting the advantages of analytical methods in cosmological parameter estimation.

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Checking the second law at cosmic scales

Abstract: Based on recent data about the history of the Hubble factor, it is argued that the second law of thermodynamics holds at the largest scales accessible to observation. This is consistent with previous studies of the same question.

Cited by 6 publications

References 44 publications

A possible late-time transition of M _B inferred via neural networks

A possible late-time transition of M _B inferred via neural networks

Model-independent cosmological inference post DESI DR1 BAO measurements

Analytical Gaussian process cosmography: unveiling insights into matter-energy density parameter at present

Contact Info

Product

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About

Checking the second law at cosmic scales

Abstract: Based on recent data about the history of the Hubble factor, it is argued that the second law of thermodynamics holds at the largest scales accessible to observation. This is consistent with previous studies of the same question.

Cited by 6 publications

References 44 publications

A possible late-time transition of M B inferred via neural networks

A possible late-time transition of M B inferred via neural networks

Model-independent cosmological inference post DESI DR1 BAO measurements

Analytical Gaussian process cosmography: unveiling insights into matter-energy density parameter at present

Contact Info

Product

Resources

About

A possible late-time transition of M _B inferred via neural networks

A possible late-time transition of M _B inferred via neural networks