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The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f_NL, offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ~23% and ~48% for galaxies at z=1 selected by stellar mass and star formation rate, respectively.
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The two-point clustering of dark matter halos is influenced by halo properties besides mass, a phenomenon referred to as halo assembly bias. Using the depth of the gravitational potential well, $V_{rm max}$, as our secondary halo property, in this paper we present the first study of the scale-dependence assembly bias. In the large-scale linear regime, $rgeq10h^{-1}{rm Mpc},$ our findings are in keeping with previous results. In particular, at the low-mass end ($M_{rm vir}<M_{rm coll}approx10^{12.5}{rm M}_{odot}$), halos with high-$V_{rm max}$ show stronger large-scale clustering relative to halos with low-$V_{rm max}$ of the same mass, this trend weakens and reverses for $M_{rm vir}geq M_{rm coll}.$ In the nonlinear regime, assembly bias in low-mass halos exhibits a pronounced scale-dependent bump at $500h^{-1}{rm kpc}-5h^{-1}{rm Mpc},$ a new result. This feature weakens and eventually vanishes for halos of higher mass. We show that this scale-dependent signature can primarily be attributed to a special subpopulation of ejected halos, defined as present-day host halos that were previously members of a higher-mass halo at some point in their past history. A corollary of our results is that galaxy clustering on scales of $rsim1-2h^{-1}{rm Mpc}$ can be impacted by up to $sim15%$ by the choice of the halo property used in the halo model, even for stellar mass-limited samples.
Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by spherical overdensity parameter, $Delta$. We summarize the strength of concentration-, shape-, and spin-dependent halo clustering as a function of halo mass and halo definition. Concentration-dependent clustering depends strongly on mass at all $Delta$. For conventional halo definitions ($Delta sim 200mathrm{m}-600mathrm{m}$), concentration-dependent clustering at low mass is driven by a population of haloes that is altered through interactions with neighbouring haloes. Concentration-dependent clustering can be greatly reduced through a mass-dependent halo definition with $Delta sim 20mathrm{m}-40mathrm{m}$ for haloes with $M_{200mathrm{m}} lesssim 10^{12}, h^{-1}mathrm{M}_{odot}$. Smaller $Delta$ implies larger radii and mitigates assembly bias at low mass by subsuming altered, so-called backsplash haloes into now larger host haloes. At higher masses ($M_{200mathrm{m}} gtrsim 10^{13}, h^{-1}mathrm{M}_{odot}$) larger overdensities, $Delta gtrsim 600mathrm{m}$, are necessary. Shape- and spin-dependent clustering are significant for all halo definitions that we explore and exhibit a relatively weaker mass dependence. Generally, both the strength and the sense of assembly bias depend on halo definition, varying significantly even among common definitions. We identify no halo definition that mitigates all manifestations of assembly bias. A halo definition that mitigates assembly bias based on one halo property (e.g., concentration) must be mass dependent. The halo definitions that best mitigate concentration-dependent halo clustering do not coincide with the expected average splashback radii at fixed halo mass.
We study the effect of large-scale tidal fields on internal halo properties using a set of N-body simulations. We measure significant cross-correlations between large-scale tidal fields and several non-scalar halo properties: shapes, velocity dispersion, and angular momentum. Selection effects that couple to these non-scalar halo properties can produce anisotropic clustering even in real-space. We investigate the size of this effect and show that it can produce a non-zero quadrupole similar in size to the one generated by linear redshift-space distortions (RSD). Finally, we investigate the clustering properties of halos identified in redshift-space and find enormous deviations from the standard linear RSD model, again caused by anisotropic assembly bias. These effects could contaminate the values of cosmological parameters inferred from the observed redshift-space clustering of galaxies, groups, or 21cm emission from atomic hydrogen, if their selection depends on properties affected by halo assembly bias. We briefly discuss ways in which this effect can be measured in existing and future large-scale structure surveys.
We present significant evidence of halo assembly bias for SDSS redMaPPer galaxy clusters in the redshift range $[0.1, 0.33]$. By dividing the 8,648 clusters into two subsamples based on the average member galaxy separation from the cluster center, we first show that the two subsamples have very similar halo mass of $M_{rm 200m}simeq 1.9times 10^{14}~h^{-1}M_odot$ based on the weak lensing signals at small radii $R<sim 10~h^{-1}{rm Mpc}$. However, their halo bias inferred from both the large-scale weak lensing and the projected auto-correlation functions differs by a factor of $sim$1.5, which is a signature of assembly bias. The same bias hypothesis for the two subsamples is excluded at 2.5$sigma$ in the weak lensing and 4.4$sigma$ in the auto-correlation data, respectively. This result could bring a significant impact on both galaxy evolution and precision cosmology.
We present evidence for halo assembly bias as a function of geometric environment. By classifying GAMA galaxy groups as residing in voids, sheets, filaments or knots using a tidal tensor method, we find that low-mass haloes that reside in knots are older than haloes of the same mass that reside in voids. This result provides direct support to theories that link strong halo tidal interactions with halo assembly times. The trend with geometric environment is reversed at large halo mass, with haloes in knots being younger than haloes of the same mass in voids. We find a clear signal of halo downsizing - more massive haloes host galaxies that assembled their stars earlier. This overall trend holds independently of geometric environment. We support our analysis with an in-depth exploration of the L-Galaxies semi-analytic model, used here to correlate several galaxy properties with three different definitions of halo formation time. We find a complex relationship between halo formation time and galaxy properties, with significant scatter. We confirm that stellar mass to halo mass ratio, specific star-formation rate and mass-weighed age are reasonable proxies of halo formation time, especially at low halo masses. Instantaneous star-formation rate is a poor indicator at all halo masses. Using the same semi-analytic model, we create mock spectral observations using complex star-formation and chemical enrichment histories, that approximately mimic GAMAs typical signal-to-noise and wavelength range. We use these mocks to assert how well potential proxies of halo formation time may be recovered from GAMA-like spectroscopic data.
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