One-loop kernels in scale-dependent Horndeski theory
We investigate the nonlinear evolution of cosmological perturbations in theories with scale-dependent perturbation growth, first in general and then focusing on Horndeski gravity. Within the framework of standard perturbation theory, we derive the second- and third-order kernels and show that they a...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
November 12, 2025
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| In: |
Journal of cosmology and astroparticle physics
Year: 2025, Issue: 11, Pages: 1-41 |
| ISSN: | 1475-7516 |
| DOI: | 10.1088/1475-7516/2025/11/035 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1088/1475-7516/2025/11/035 |
| Author Notes: | Ziyang Zheng, Hanqiong Jia, Bilal Tüdes, Anton Chudaykin, Martin Kunz and Luca Amendola |
| Summary: | We investigate the nonlinear evolution of cosmological perturbations in theories with scale-dependent perturbation growth, first in general and then focusing on Horndeski gravity. Within the framework of standard perturbation theory, we derive the second- and third-order kernels and show that they are fully determined by two effective functions, h 1 and hc , which parametrize deviations from general relativity. Using the Wronskian method, we obtain solutions for the nonlinear growth functions and present explicit expressions for the resulting kernels, including bias and redshift space distortions, valid in the limit in which the k-dependent part is subdominant. We show that the kernels are entirely dependent on the linear growing mode: once this is calculated, the kernels are analytic up to a time integral. We also include redshift-space distortions (RSD) and scale-dependent bias. Our approach provides a physically motivated framework for evaluating the one-loop galaxy power spectrum in scale-dependent theories, suitable for the forecasts and actual data analysis. |
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| Item Description: | Veröffentlicht: 12. November 2025 Gesehen am 27.01.2026 |
| Physical Description: | Online Resource |
| ISSN: | 1475-7516 |
| DOI: | 10.1088/1475-7516/2025/11/035 |