Extracting information from the total matter power spectrum with the precision needed for upcoming cosmological surveys requires unraveling the complex effects of galaxy formation processes on the distribution of matter. We investigate the impact of baryonic physics on matter clustering at z = 0 using a library of power spectra from the Cosmology and Astrophysics with MachinE Learning Simulations project, containing thousands of $(25\, h^{-1}\, {\rm Mpc})^3$ volume realizations with varying cosmology, initial random field, stellar and active galactic nucleus (AGN) feedback strength and subgrid model implementation methods. We show that baryonic physics affects matter clustering on scales $k \gtrsim 0.4\, h\, \mathrm{Mpc}^{-1}$ and the magnitude of this effect is dependent on the details of the galaxy formation implementation and variations of cosmological and astrophysical parameters. Increasing AGN feedback strength decreases halo baryon fractions and yields stronger suppression of power relative to N-body simulations, while stronger stellar feedback often results in weaker effects by suppressing black hole growth and therefore the impact of AGN feedback. We find a broad correlation between mean baryon fraction of massive haloes (M200c > 1013.5 M⊙) and suppression of matter clustering but with significant scatter compared to previous work owing to wider exploration of feedback parameters and cosmic variance effects. We show that a random forest regressor trained on the baryon content and abundance of haloes across the full mass range 1010 ≤ Mhalo/M⊙<1015 can predict the effect of galaxy formation on the matter power spectrum on scales k = 1.0–20.0 $h\, \mathrm{Mpc}^{-1}$.
Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraints on cosmology. We investigate how the observable properties of group-scale haloes can constrain feedback’s impact on the matter distribution using Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). Extending the results of previous work to smaller halo masses and higher wavenumber, k, we find that the baryon fraction in haloes contains significant information about the impact of feedback on the matter power spectrum. We explore how the thermal Sunyaev Zel’dovich (tSZ) signal from group-scale haloes contains similar information. Using recent Dark Energy Survey weak lensing and Atacama Cosmology Telescope tSZ cross-correlation measurements and models trained on CAMELS, we obtain 10 per cent constraints on feedback effects on the power spectrum at $k \sim 5\, h\, {\rm Mpc}^{-1}$. We show that with future surveys, it will be possible to constrain baryonic effects on the power spectrum to $\mathcal {O}(\lt 1~{{\ \rm per\ cent}})$ at $k = 1\, h\, {\rm Mpc}^{-1}$ and $\mathcal {O}(3~{{\ \rm per\ cent}})$ at $k = 5\, h\, {\rm Mpc}^{-1}$ using the methods that we introduce here. Finally, we investigate the impact of feedback on the matter bispectrum, finding that tSZ observables are highly informative in this case.
more » « less- NSF-PAR ID:
- 10444618
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 525
- Issue:
- 2
- ISSN:
- 0035-8711
- Page Range / eLocation ID:
- p. 1779-1794
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
ABSTRACT -
more » « less
ABSTRACT We use the small scales of the Dark Energy Survey (DES) Year-3 cosmic shear measurements, which are excluded from the DES Year-3 cosmological analysis, to constrain the baryonic feedback. To model the baryonic feedback, we adopt a baryonic correction model and use the numerical package baccoemu to accelerate the evaluation of the baryonic non-linear matter power spectrum. We design our analysis pipeline to focus on the constraints of the baryonic suppression effects, utilizing the implication given by a principal component analysis on the Fisher forecasts. Our constraint on the baryonic effects can then be used to better model and ameliorate the effects of baryons in producing cosmological constraints from the next-generation large-scale structure surveys. We detect the baryonic suppression on the cosmic shear measurements with a ∼2σ significance. The characteristic halo mass for which half of the gas is ejected by baryonic feedback is constrained to be $M_c \gt 10^{13.2} \, h^{-1} \, \mathrm{M}_{\odot }$ (95 per cent C.L.). The best-fitting baryonic suppression is $\sim 5{{\ \rm per\ cent}}$ at $k=1.0 \, {\rm Mpc}\ h^{-1}$ and $\sim 15{{\ \rm per\ cent}}$ at $k=5.0 \, {\rm Mpc} \ h^{-1}$. Our findings are robust with respect to the assumptions about the cosmological parameters, specifics of the baryonic model, and intrinsic alignments.
-
more » « less
ABSTRACT We quantify the cosmological spread of baryons relative to their initial neighbouring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighbouring distribution owing to chaotic gravitational dynamics on spatial scales comparable to their host dark matter halo. In contrast, gas in hydrodynamic simulations spreads much further from the initial neighbouring dark matter owing to feedback from supernovae (SNe) and active galactic nuclei (AGN). We show that large-scale baryon spread is very sensitive to model implementation details, with the fiducial simba model spreading ∼40 per cent of baryons >1 Mpc away compared to ∼10 per cent for the IllustrisTNG and astrid models. Increasing the efficiency of AGN-driven outflows greatly increases baryon spread while increasing the strength of SNe-driven winds can decrease spreading due to non-linear coupling of stellar and AGN feedback. We compare total matter power spectra between hydrodynamic and paired N-body simulations and demonstrate that the baryonic spread metric broadly captures the global impact of feedback on matter clustering over variations of cosmological and astrophysical parameters, initial conditions, and (to a lesser extent) galaxy formation models. Using symbolic regression, we find a function that reproduces the suppression of power by feedback as a function of wave number (k) and baryonic spread up to $k \sim 10\, h$ Mpc−1 in SIMBA while highlighting the challenge of developing models robust to variations in galaxy formation physics implementation.
-
null (Ed.)ABSTRACT Galaxy intrinsic alignments (IAs) have long been recognized as a significant contaminant to weak lensing-based cosmological inference. In this paper we seek to quantify the impact of a common modelling assumption in analytic descriptions of IAs: that of spherically symmetric dark matter haloes. Understanding such effects is important as the current generation of IA models are known to be limited, particularly on small scales, and building an accurate theoretical description will be essential for fully exploiting the information in future lensing data. Our analysis is based on a catalogue of 113 560 galaxies between z = 0.06 and 1.00 from massiveblack-ii, a hydrodynamical simulation of box length $100 \, h^{-1}$ Mpc. We find satellite anisotropy contributes at the level of $\ge 30\!-\!40{{\ \rm per\ cent}}$ to the small-scale alignment correlation functions. At separations larger than $1 \, h^{-1}$ Mpc the impact is roughly scale independent, inducing a shift in the amplitude of the IA power spectra of $\sim 20{{\ \rm per\ cent}}$. These conclusions are consistent across the redshift range and between the massiveblack-ii and the illustris simulations. The cosmological implications of these results are tested using a simulated likelihood analysis. Synthetic cosmic shear data are constructed with the expected characteristics (depth, area, and number density) of a future LSST-like survey. Our results suggest that modelling alignments using a halo model based upon spherical symmetry could potentially induce cosmological parameter biases at the ∼1.5σ level for S8 and w.more » « less
-
null (Ed.)ABSTRACT Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q1) generally reflects the strength of baryon feedback. With the upper limit of Q1 prior being bound by the Illustris feedback scenarios, we reach $\sim 20{{\ \rm per\ cent}}$ improvement in the constraint of $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q1 prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.more » « less
