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This site contains tabulated power spectra of OWLS simulations, and videos showing the evolution of these power spectra, presented in the following paper:

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.

Tabulated power spectra

Below, links are provided to plain text files containing power spectrum values for our simulations on a range of scales (0.06 ≤ k ≤ 500 h/Mpc) and redshifts (z ≤ 6). The format corresponds to that shown in Table B1 of Van Daalen et al. (2011). All simulations were run for a WMAP3 cosmology unless noted otherwise. For more information about the simulations and power spectra, we refer to Van Daalen et al. (2011).

Power spectra for AGN_L100N512

Power spectra for AGN_WMAP7_L100N512

Power spectra for DBLIMFV1618_L100N512

Power spectra for DMONLY_L100N512

Power spectra for DMONLY_WMAP7_L100N512

Power spectra for NOSN_L100N512

Power spectra for NOSN_NOZCOOL_L100N512

Power spectra for NOZCOOL_L100N512

Power spectra for REF_L100N512

Power spectra for WDENS_L100N512

Power spectra for WML1V848_L100N512

Power spectra for WML4_L100N512

Evolution of power spectra

Below we present videos showing the evolution of different power spectra. Additional videos may be added at a later time.

We first present several videos showing the joint evolution of power spectra of different models, from redshift 10 to zero. Two videos are shown for each set of models: one where we use the dimensionless power spectrum definition Δ2(k), and one where we use P(k). Note that this does not affect the relative differences between power spectra. Shot noise, which is shown as a dotted line for each model, has been subtracted. The linear input power spectrum, evolved with redshift, is shown as a dashed purple line. All simulations were run with a box size of L=100 Mpc/h and 5123 particles per species (i.e. CDM and baryons).

Δ2(k) for DMONLY_WMAP7 and AGN_WMAP7
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P(k) for DMONLY_WMAP7 and AGN_WMAP7
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Next, we show the evolution of different components, for both REF and AGN. The removal of gas and suppression of star formation in model AGN have a clear effect on the evolution of these components, relative to a simulation without AGN feedback.

Δ2(k) for different components of REF
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P(k) for different components of REF
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Δ2(k) for different components of AGN
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P(k) for different components of AGN
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Finally, we show how a dark matter-only simulation with 1283 particles evolves differently when either glass or grid initial conditions are applied. Here we do not correct for shot noise.

Δ2(k) for glass and grid initial conditions
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P(k) for glass and grid initial conditions
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