Non-linear matter power spectrum modeling in interacting dark energy cosmologies
Abstract Understanding the behavior of the matter power spectrum on non-linear scales beyond the $$\Lambda $$ Λ CDM model is crucial for accurately predicting the large-scale structure (LSS) of the Universe in non-standard cosmologies. In this work, we present an analysis of the non-linear matter po...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-10-01
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| Series: | European Physical Journal C: Particles and Fields |
| Online Access: | https://doi.org/10.1140/epjc/s10052-024-13487-x |
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| Summary: | Abstract Understanding the behavior of the matter power spectrum on non-linear scales beyond the $$\Lambda $$ Λ CDM model is crucial for accurately predicting the large-scale structure (LSS) of the Universe in non-standard cosmologies. In this work, we present an analysis of the non-linear matter power spectrum within the framework of interacting dark energy-dark matter cosmologies (IDE). We employ N-body simulations and theoretical models to investigate the impact of IDE on these non-linear scales. Beginning with N-body simulations characterized by a fixed parameter space delineated by prior observational research, we adeptly fit the simulated spectra with a simple parametric function, achieving accuracy within 5%. Subsequently, we refine a modified halo model tailored to the IDE cosmology, exhibiting exceptional precision in fitting the simulations down to scales of approximately 1 h/Mpc. To assess the model’s robustness, we conduct a forecast analysis for the Euclid survey, employing our refined model. We find that the coupling parameter $$\xi $$ ξ will be constrained to $$\sigma (\xi ) = 0.0110$$ σ ( ξ ) = 0.0110 . This marks a significant improvement by an order of magnitude compared to any other current observational tests documented in the literature. These primary findings pave the way for a novel preliminary approach, enabling the utilization of IDE models for observational constraints concerning LSS data on non-linear scales. |
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| ISSN: | 1434-6052 |