Improved late-time fits with wavelet extensions of ΛCDM

ABSTRACT We parametrize the Hubble function by adding Hermitian wavelets to the Hubble radius of $\Lambda$ cold dark matter ($\Lambda$CDM). This construction enables the Hubble function to oscillate around $\Lambda$CDM at late times while preserving the angular diameter distance to the last scattering. We perform parameter inference and model selection at the background level using a wide range of cosmological observations. We find that baryon acoustic oscillation (BAO) data play a central role in constraining the wavelet parameters. In particular, we focus on the differences between SDSS and DESI BAO data sets. Wavelet models consistently provide a better fit when either BAO data set is included. DESI-BAO prefers wavelets centred around $z \sim 0.7$, while SDSS-BAO prefers higher redshifts ($z > 1$), driven by discrepancies in their $D_H / r_{\rm d}$ measurements at $z = 0.51$ and $z \sim 2.3$. We also analyse the consequences for a dynamical dark energy component derived from the wavelet modifications. The dark energy density is found to oscillate by construction and can become negative at large redshifts ($z \gtrsim 2$) in response to the SDSS-BAO data. Notably, the early Universe constraints, including those on the matter density and Hubble constant, remain essentially unchanged. Our results indicate that wavelet-based deviations are favoured in the late Universe, with DESI-BAO leading to a significant improvement of more than $3\sigma$ in the fit. These findings suggest that localized oscillatory features in the expansion history may help reconcile tensions in low-redshift data without disrupting early-Universe consistency.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-10-09
DOI
https://doi.org/10.1093/mnras/staf1732
Citations
4
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
5.10

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article

Improved late-time fits with wavelet extensions of ΛCDM

Luis A. Escamilla, Emre Özülker, Özgür Akarsu, Eleonora Di Valentino et al.
4 citations
Monthly Notices of the Royal Astronomical Society
Image and Signal Denoising Methods
5.10
article

Improved late-time fits with wavelet extensions of ΛCDM

Luis A. Escamilla, Emre Özülker, Özgür Akarsu, Eleonora Di Valentino, J. Alberto Vázquez
article en
4 citations

Abstract

ABSTRACT We parametrize the Hubble function by adding Hermitian wavelets to the Hubble radius of $\Lambda$ cold dark matter ($\Lambda$CDM). This construction enables the Hubble function to oscillate around $\Lambda$CDM at late times while preserving the angular diameter distance to the last scattering. We perform parameter inference and model selection at the background level using a wide range of cosmological observations. We find that baryon acoustic oscillation (BAO) data play a central role in constraining the wavelet parameters. In particular, we focus on the differences between SDSS and DESI BAO data sets. Wavelet models consistently provide a better fit when either BAO data set is included. DESI-BAO prefers wavelets centred around $z \sim 0.7$, while SDSS-BAO prefers higher redshifts ($z > 1$), driven by discrepancies in their $D_H / r_{\rm d}$ measurements at $z = 0.51$ and $z \sim 2.3$. We also analyse the consequences for a dynamical dark energy component derived from the wavelet modifications. The dark energy density is found to oscillate by construction and can become negative at large redshifts ($z \gtrsim 2$) in response to the SDSS-BAO data. Notably, the early Universe constraints, including those on the matter density and Hubble constant, remain essentially unchanged. Our results indicate that wavelet-based deviations are favoured in the late Universe, with DESI-BAO leading to a significant improvement of more than $3\sigma$ in the fit. These findings suggest that localized oscillatory features in the expansion history may help reconcile tensions in low-redshift data without disrupting early-Universe consistency.

Monthly Notices of the Royal Astronomical SocietyVol. 544(1)
Istanbul Technical University (TR), Universidad Autónoma del Estado de Morelos (MX), Universidad Nacional Autónoma de México (MX), University of Sheffield (GB)
Consejo Nacional de Ciencia y Tecnología, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, Türkiye Bilimler Akademisi, Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México
Openalex Percentile: Top 4%
Image and Signal Denoising Methods
5.10
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