The Dark Side of the Halo Occupation Distribution

Kravtsov, Andrey V.; Berlind, Andreas A.; Wechsler, Risa H.; Klypin, Anatoly; Gottlöber, Stefan; Allgood, Brandon; Primack, Joel R.

doi:10.1086/420959

Cited by 894 publications

(1,290 citation statements)

References 79 publications

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“…For a galaxy sample defined by a threshold L min in optical or near-IR luminosity (or stellar mass), theoretical models and empirical studies (too numerous to list comprehensively, but our summary here is especially influenced by Kravtsov et al 2004;Conroy et al 2006;Zehavi et al 2011) suggest the following approximate model. The minimum host halo mass is the one for which the comoving space density n(M min ) of halos above M min matches the space density n(L min ) of galaxies above the luminosity threshold.…”

Section: Cmb Anisotropies and Large Scale Structurementioning

confidence: 99%

Observational probes of cosmic acceleration

et al. 2013

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The accelerating expansion of the universe is the most surprising cosmological discovery in many decades, implying that the universe is dominated by some form of "dark energy" with exotic physical properties, or that Einstein's theory of gravity breaks down on cosmological scales. The profound implications of cosmic acceleration have inspired ambitious efforts to understand its origin, with experiments that aim to measure the history of expansion and growth of structure with percent-level precision or higher. We review in detail the four most well established methods for making such measurements: Type Ia supernovae, baryon acoustic oscillations (BAO), weak gravitational lensing, and the abundance of galaxy clusters. We pay particular attention to the systematic uncertainties in these techniques and to strategies for controlling them at the level needed to exploit "Stage IV" dark energy facilities such as BigBOSS, LSST, Euclid, and WFIRST. We briefly review a number of other approaches including redshift-space distortions, the Alcock-Paczynski effect, and direct measurements of the Hubble constant H 0 . We present extensive forecasts for constraints on the dark energy equation of state and parameterized deviations from General Relativity, achievable with Stage III and Stage IV experimental programs that incorporate supernovae, BAO, weak lensing, and cosmic microwave background data. We also show the level of precision required for clusters or other methods to provide constraints competitive with those of these fiducial programs. We emphasize the value of a balanced program that employs several of the most powerful methods in combination, both to cross-check systematic uncertainties and to take advantage of complementary information. Surveys to probe cosmic acceleration produce data sets that support a wide range of scientific investigations, and they continue the longstanding astronomical tradition of mapping the universe in ever greater detail over ever larger scales.

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Section: Cmb Anisotropies and Large Scale Structurementioning

confidence: 99%

Observational probes of cosmic acceleration

et al. 2013

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“…The HOD gives mean number of galaxies of a given type in a dark matter halo of mass M and is usually presented in a parameterized form (Seljak 2000;Bullock et al 2002;Kravtsov et al 2004;Hamana et al 2004;Zehavi et al 2005;Hamana et al 2006;Conroy et al 2006). Galaxy clustering can be calculated by combining the HOD with dark matter clustering, dark matter halo abundance, halo bias and the halo density profile.…”

Section: The Halo Occupation Distributionmentioning

confidence: 99%

Understanding the non-linear clustering of high-redshift galaxies

Jose

Baugh

Lacey

et al. 2017

Monthly Notices of the Royal Astronomical Society

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We incorporate the non-linear clustering of dark matter halos, as modelled by Jose et al. (2016) into the halo model to better understand the clustering of Lyman break galaxies (LBGs) in the redshift range z = 3 − 5. We find that, with this change, the predicted LBG clustering increases significantly on quasi-linear scales (0.1 ≤ r / h −1 Mpc ≤ 10) compared to that in the linear halo bias model. This in turn results in an increase in the clustering of LBGs by an order of magnitude on angular scales 5 ≤ θ ≤ 100 . Remarkably, the predictions of our new model on the whole remove the systematic discrepancy between the linear halo bias predictions and the observations. The correlation length and large scale galaxy bias of LBGs are found to be significantly higher in the non-linear halo bias model than in the linear halo bias model. The resulting two-point correlation function retains an approximate power-law form in contrast with that computed using the linear halo bias theory. We also find that the non-linear clustering of LBGs increases with increasing luminosity and redshift. Our work emphasizes the importance of using non-linear halo bias in order to model the clustering of high-z galaxies to probe the physics of galaxy formation and extract cosmological parameters reliably.

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“…Following Wang12, we can overcome this limitation by appealing to the approximate invariance of the scaled subhalo velocity function, N (>ν), with host halo mass, that is, to the fact that, to good approximation, the subhalo number PDF is independent of halo mass when expressed as a function of ν (Moore et al 1999;Kravtsov et al 2004;Zheng et al 2005;Springel et al 2008;Weinberg et al 2008;Wang12;C14). This is clearly seen in Fig.…”

Section: T H E M a S S D I S T R I B U T I O N O F T H E M Wmentioning

confidence: 99%

“…Using the approximate invariance of the scaled subhalo maximum velocity function with host halo mass (see e.g. Moore et al 1999;Kravtsov et al 2004;Zheng et al 2005;Springel et al 2008;Weinberg et al 2008), Wang12 derived statistics for galactic subhaloes and estimated the probability that an MW halo contains three or fewer satellites with V max ≥ 30 km s −1 , as a function of the host halo mass. These results were further refined by Cautun et al (2014, hereafter C14), who developed a better method for estimating the abundance of galactic subhaloes in cosmological simulations.…”

Section: Introductionmentioning

confidence: 99%

Milky Way mass constraints from the Galactic satellite gap

Cautun

Frenk

Weygaert

et al. 2014

Monthly Notices of the Royal Astronomical Society

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We use the distribution of maximum circular velocities, V max , of satellites in the Milky Way (MW) to constrain the virial mass, M 200 , of the Galactic halo under an assumed prior of a ΛCDM universe. This is done by analysing the subhalo populations of a large sample of halos found in the Millennium II cosmological simulation. The observation that the MW has at most three subhalos with V max 30 km/s requires a halo mass M 200 1.4 × 10 12 M , while the existence of the Magellanic Clouds (assumed to have V max 60 km/s) requires M 200 1.0 × 10 12 M . The first of these conditions is necessary to avoid the "too-big-to-fail" problem highlighted by Boylan-Kolchin et al., while the second stems from the observation that massive satellites like the Magellanic Clouds are rare. When combining both requirements, we find that the MW halo mass must lie in the range 0.25 M 200 /(10 12 M ) 1.4 at 90% confidence. The gap in the abundance of Galactic satellites between 30 km/s V max 60 km/s places our galaxy in the tail of the expected satellite distribution.

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The Dark Side of the Halo Occupation Distribution

Cited by 894 publications

References 79 publications

Observational probes of cosmic acceleration

Observational probes of cosmic acceleration

Understanding the non-linear clustering of high-redshift galaxies

Milky Way mass constraints from the Galactic satellite gap

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