Machine Learning meets the redshift evolution of the CMB Temperature. (arXiv:2002.12700v2 [astro-ph.CO] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Arjona_R/0/1/0/all/0/1">Rubén Arjona</a>
We present a model independent and non-parametric reconstruction with a
Machine Learning algorithm of the redshift evolution of the Cosmic Microwave
Background (CMB) temperature from a wide redshift range $zin left[0,3right]$
without assuming any dark energy model, an adiabatic universe or photon number
conservation. In particular we use the genetic algorithms which avoid the
dependency on an initial prior or a cosmological fiducial model. Through our
reconstruction we constrain new physics at late times. We provide novel and
updated estimates on the $beta$ parameter from the parametrisation
$text{T}(z)=text{T}_0(1+z)^{1-beta}$, the duality relation $eta(z)$ and the
cosmic opacity parameter $tau(z)$. Furthermore we place constraints on a
temporal varying fine structure constant $alpha$, which would have signatures
in a broad spectrum of physical phenomena such as the CMB anisotropies. Overall
we find no evidence of deviations within the $1sigma$ region from the well
established $Lambdatext{CDM}$ model, thus confirming its predictive
potential.
We present a model independent and non-parametric reconstruction with a
Machine Learning algorithm of the redshift evolution of the Cosmic Microwave
Background (CMB) temperature from a wide redshift range $zin left[0,3right]$
without assuming any dark energy model, an adiabatic universe or photon number
conservation. In particular we use the genetic algorithms which avoid the
dependency on an initial prior or a cosmological fiducial model. Through our
reconstruction we constrain new physics at late times. We provide novel and
updated estimates on the $beta$ parameter from the parametrisation
$text{T}(z)=text{T}_0(1+z)^{1-beta}$, the duality relation $eta(z)$ and the
cosmic opacity parameter $tau(z)$. Furthermore we place constraints on a
temporal varying fine structure constant $alpha$, which would have signatures
in a broad spectrum of physical phenomena such as the CMB anisotropies. Overall
we find no evidence of deviations within the $1sigma$ region from the well
established $Lambdatext{CDM}$ model, thus confirming its predictive
potential.
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