The Effects of Active Galactic Nuclei Feedback on the Lyα Forest Flux Power Spectrum
We study the effects of active galactic nuclei (AGN) feedback on the Ly α forest 1D flux power spectrum (P1D). Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba , the impact of AGN f...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
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Series: | The Astrophysical Journal |
Subjects: | |
Online Access: | https://doi.org/10.3847/1538-4357/ada5f7 |
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Summary: | We study the effects of active galactic nuclei (AGN) feedback on the Ly α forest 1D flux power spectrum (P1D). Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba , the impact of AGN feedback is most dramatic at lower redshifts ( z < 1) and that AGN jet feedback plays the most significant role in altering the P1D. The effects of AGN feedback can be seen across a large range of wavenumbers (1.5 × 10 ^−3 < k < 10 ^−1 s km ^−1 ) changing the ionization state of hydrogen in the IGM through heating. AGN feedback can also alter the thermal evolution of the IGM and thermally broaden individual Ly α absorbers. For the Simba model, these effects become observable at z ≲ 1.0. At higher redshifts ( z > 2.0), AGN feedback has a 2% effect on the P1D for k < 5 × 10 ^−2 s km ^−1 and an 8% effect for k > 5 × 10 ^−2 s km ^−1 . We show that the small-scale effect is reduced when normalizing the simulation to the observed mean flux. On large scales, the effect of AGN feedback appears via a change in the IGM temperature and is thus unlikely to bias cosmological parameters. The strong AGN jets in the Simba simulation can reproduce the z > 2 Ly α forest. We stress that analyses comparing different AGN feedback models to future higher precision data will be necessary to determine the full extent of this effect. |
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ISSN: | 1538-4357 |