The effects of galaxy formation on the matter power spectrum: A challenge for precision cosmology

TL;DR

Future weak lensing surveys demand 1%–level predictions of the non-linear matter power spectrum over 0.1–10 h/Mpc. Using the OWLS hydrodynamical simulations and a high-accuracy power-spectrum estimator, the paper shows that baryonic physics—particularly AGN feedback—profoundly reshapes P(k) and the distribution of power among CDM, gas, and stars, with back-reaction on dark matter. AGN-driven gas ejection can reduce power by up to tens of percent on k ~ 1–10 h/Mpc, challenging the common assumption that baryons mainly boost power on small scales. The findings imply that precise cosmology from weak lensing will require auxiliary observations to constrain galaxy-formation physics, and that simplistic dark-matter-only models are insufficient for upcoming surveys.

Abstract

Upcoming weak lensing surveys, such as LSST, EUCLID, and WFIRST, aim to measure the matter power spectrum with unprecedented accuracy. In order to fully exploit these observations, models are needed that, given a set of cosmological parameters, can predict the non-linear matter power spectrum at the level of 1% or better for scales corresponding to comoving wave numbers 0.1<k<10 h/Mpc. We have employed the large suite of simulations from the OWLS project to investigate the effects of various baryonic processes on the matter power spectrum. In addition, we have examined the distribution of power over different mass components, the back-reaction of the baryons on the CDM, and the evolution of the dominant effects on the matter power spectrum. We find that single baryonic processes are capable of changing the power spectrum by up to several tens of per cent. Our simulation that includes AGN feedback, which we consider to be our most realistic simulation as, unlike those used in previous studies, it has been shown to solve the overcooling problem and to reproduce optical and X-ray observations of groups of galaxies, predicts a decrease in power relative to a dark matter only simulation ranging, at z=0, from 1% at k~0.3 h/Mpc to 10% at k~1 h/Mpc and to 30% at k~10 h/Mpc. This contradicts the naive view that baryons raise the power through cooling, which is the dominant effect only for k>70 h/Mpc. Therefore, baryons, and particularly AGN feedback, cannot be ignored in theoretical power spectra for k>0.3 h/Mpc. It will thus be necessary to improve our understanding of feedback processes in galaxy formation, or at least to constrain them through auxiliary observations, before we can fulfil the goals of upcoming weak lensing surveys.

Figures (11)

• Figure 1: Comparison of the matter power spectrum of DMONLY_L100N512 with analytical fits by PeacockDodds1996 and SmithPeacock2003 at redshift zero. The small circle, drawn in this and all following plots showing $\Delta^2(k)$, indicates the scale below which the (subtracted) shot noise in the simulation becomes significant, and the dashed purple curve shows the linear input power spectrum of the simulations. The bottom panel shows the ratios of the power spectra from theoretical models and the simulation. There is good agreement down to scales of a few Mpc, especially for the more recent HALOFIT model, but on smaller scales DMONLY predicts up to twice as much power as HALOFIT. For $\lambda < 10^2\,h^{-1}\,\mathrm{kpc}$ the power in the DMONLY simulation drops due to a lack of resolution.
• Figure 2: A comparison of the total matter power spectra of DMONLY_L100N512 (black), REF_L100N512 (green) and AGN_L100N512 (red), at redshift $z=0$. The bottom panel shows the absolute value of the relative difference of the latter two with respect to DMONLY; solid (dashed) curves indicate that the power is higher (lower) than for DMONLY. The dotted, horizontal line shows the $1\%$ level. Note that the first wave mode has been omitted as it holds no information. While pressure forces smooth the baryonic density field on intermediate scales, cooling allows the baryons to increase the total power on small scales. The addition of AGN feedback, which is required to match observations of groups, has an enormous effect, reducing the power by $\ga 10\%$ for $k\ga 1\,h\,\mathrm{Mpc}^{-1}$.
• Figure 3: Comparisons of $z=0$ power spectra predicted by simulations incorporating different physical processes to that predicted by the reference simulation. The panels are similar to the bottom panel of Figure \ref{['DMONLYREFAGN']}, but now show differences relative to REF. The thin black curve that is repeated in all panels shows the relative difference with DMONLY. Colours indicate different simulations, while different line styles indicate whether the power is reduced or increased relative to the reference simulation. Top: A simulation without SN feedback (blue), one without metal-line cooling (green) and one that excludes both effects (red). SN feedback decreases the power on all scales. Metal-line cooling decreases the power for $\lambda > 0.4\,h^{-1}\,\mathrm{Mpc}$ but increases the power on smaller scales. The effects of removing both SN feedback and metal-line cooling are $> 10\%$ for $k>20\,h\,\mathrm{Mpc}^{-1}$ and $>1\%$ for $k>2\,h\,\mathrm{Mpc}^{-1}$. Middle: Different SN wind models which all use the same amount of SN energy per unit stellar mass (see text). The effects of varying the implementation of SN feedback, while keeping the SN energy that is injected per unit stellar mass the same, are $>10\%$ for $k>10\,h\,\mathrm{Mpc}^{-1}$ and $>1\%$ for $k>1\,h\,\mathrm{Mpc}^{-1}$. Bottom: Models with different feedback energies and processes, see text for details. Including a top-heavy IMF at high pressure (DBLIMFV1618) or AGN feedback (AGN) greatly reduces the power. The reduction caused by the latter is $>10\%$ for $k>2\,h\,\mathrm{Mpc}^{-1}$ and $>1\%$ for $k>0.4\,h\,\mathrm{Mpc}^{-1}$.
• Figure 4: Difference of the $z=0$ matter power spectrum in a simulation using a WMAP1 cosmology (MILL) relative to that of the REF model, which assumes the WMAP3 cosmology, after rescaling the former to match the latter on the scale of the simulation box ($\lambda=100\,h^{-1}\,\mathrm{Mpc}$, not shown). WML4 is shown for reference as this simulation uses the same baryonic physics as MILL. For $k \ga 3\,h\,\mathrm{Mpc}^{-1}$, the effect of AGN feedback is at least as strong as that of this unrealistically large change in cosmology.
• Figure 5: Decomposing the $z=0$ total power spectra (black) into the contributions from cold dark matter (blue), gas (green) and stars/black holes (red). The left and right columns show results for REF_L100N512 and AGN_L100N512. In the top row the density contrast of each component $i$ is defined relative to its own mean density, i.e. $\delta_i \equiv (\rho_i - \bar{\rho}_i)/\bar{\rho}_i$. This guarantees that all power spectra converge on large scales, thus enabling a straightforward comparison of their shapes. In the bottom row the density contrast of each component is defined relative to the total mean density, i.e. $\delta_i \equiv (\rho_i - \bar{\rho}_\mathrm{tot})/\bar{\rho}_\mathrm{tot}$, which allows one to compare their contributions to the total power. The power spectrum of the gas flattens or even decreases for $\lambda\la 1\,h^{-1}\,\mathrm{Mpc}$ as a result of pressure smoothing, but its ability to cool allows it to increase again on galaxy scales ($\lambda \la 10^2\,h^{-1}\,\mathrm{kpc}$). The power spectrum of the stellar component, which is a product of the collapse of cooling gas, increases most rapidly towards smaller scales. While stars dominate the total power for $\lambda \ll 10^2\,h^{-1}\,\mathrm{kpc}$ in REF, dark matter dominates on all scales when AGN feedback is included.