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Register a new userIdentifying the progenitors of present-day early-type galaxies in observational surveys: correcting `progenitor bias using the Horizon-AGN simulation
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G. Martin
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As endpoints of the hierarchical mass-assembly process, the stellar populations of local early-type galaxies encode the assembly history of galaxies over cosmic time. We use Horizon-AGN, a cosmological hydrodynamical simulation, to study the merger histories of local early-type galaxies and track how the morphological mix of their progenitors evolves over time. We provide a framework for alleviating `progenitor bias -- the bias that occurs if one uses only early-type galaxies to study the progenitor population. Early-types attain their final morphology at relatively early epochs -- by $zsim1$, around 60 per cent of todays early-types have had their last significant merger. At all redshifts, the majority of mergers have one late-type progenitor, with late-late mergers dominating at $z>1.5$ and early-early mergers becoming significant only at $z<0.5$. Progenitor bias is severe at all but the lowest redshifts -- e.g. at $zsim0.6$, less than 50 per cent of the stellar mass in todays early-types is actually in progenitors with early-type morphology, while, at $zsim2$, studying only early-types misses almost all (80 per cent) of the stellar mass that eventually ends up in local early-type systems. At high redshift, almost all massive late-type galaxies, regardless of their local environment or star-formation rate, are progenitors of local early-type galaxies, as are lower-mass (M$_star$ $<$ 10$^{10.5}$ M$_{odot}$) late-types as long as they reside in high density environments. In this new era of large observational surveys (e.g. LSST, JWST), this study provides a framework for studying how todays early-type galaxies have been built up over cosmic time.
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Elliptical galaxies today appear aligned with the large-scale structure of the Universe, but it is still an open question when they acquire this alignment. Observational data is currently insufficient to provide constraints on the time evolution of intrinsic alignments, and hence existing models range from assuming that galaxies gain some primordial alignment at formation, to suggesting that they react instantaneously to tidal interactions with the large-scale structure. Using the cosmological hydrodynamical simulation Horizon-AGN, we measure the relative alignments between the major axes of galaxies and eigenvectors of the tidal field as a function of redshift. We focus on constraining the time evolution of the alignment of the main progenitors of massive $z=0$ elliptical galaxies, the main weak lensing contaminant at low redshift. We show that this population, which at $z=0$ has a stellar mass above $10^{10.4}$ M$_odot$, transitions from having no alignment with the tidal field at $z=3$, to a significant alignment by $z=1$. From $z=0.5$ they preserve their alignment at an approximately constant level until $z=0$. We find a mass-dependence of the alignment signal of elliptical progenitors, whereby ellipticals that are less massive today ($10^{10.4}<M/{rm M}_odot<10^{10.7}$) do not become aligned till later redshifts ($z<2$), compared to more massive counterparts. We also present an extended study of progenitor alignments in the parameter space of stellar mass and galaxy dynamics, the impact of shape definition and tidal field smoothing.
Using the two large cosmological hydrodynamical simulations, Horizon-AGN (H-AGN) and Horizon-noAGN (H-noAGN, no AGN feedback), we investigate how a typical sub-grid model for AGN feedback affects the evolution of the total density profiles (dark matter + stars) at the effective radius of massive early-type galaxies (M*>10^11 Msun). We have studied the dependencies of the mass-weighted density slope gamma_tot with the effective radius, the galaxy mass and the host halo mass at z~0.3 and found that the inclusion of AGN feedbackalways leads to a much better agreement with observational values and trends. Our analysis suggests also that the inclusion of AGN feedback favours a strong correlation between gamma_tot and the density slope of the dark matter component while, in the absence of AGN activity, gamma_tot is rather strongly correlated with the density slope of the stellar component. Finally, we find that gamma_tot derived from our samples of galaxies increases from z=2 to z=0,in good agreement with the expected observational trend. The derived slopes are slightly lower than in the data when AGN is included because the simulated galaxies tend to be too extended, especially the least massive ones. However, the simulated compact galaxies without AGN feedback have gamma_tot values that are significantly too high compared to observations.
Using a suite of three large cosmological hydrodynamical simulations, Horizon-AGN, Horizon-noAGN (no AGN feedback) and Horizon-DM (no baryons), we investigate how a typical sub-grid model for AGN feedback affects the evolution of the inner density profiles of massive dark matter haloes and galaxies. Based on direct object-to-object comparisons, we find that the integrated inner mass and density slope differences between objects formed in these three simulations (hereafter, H_AGN, H_noAGN and H_DM) significantly evolve with time. More specifically, at high redshift (z~5), the mean central density profiles of H_AGN and H_noAGN dark matter haloes tend to be much steeper than their H_DM counterparts owing to the rapidly growing baryonic component and ensuing adiabatic contraction. By z~1.5, these mean halo density profiles in H_AGN have flattened, pummelled by powerful AGN activity (quasar mode): the integrated inner mass difference gaps with H_noAGN haloes have widened, and those with H_DM haloes have narrowed. Fast forward 9.5 billion years, down to z=0, and the trend reverses: H_AGN halo mean density profiles drift back to a more cusped shape as AGN feedback efficiency dwindles (radio mode), and the gaps in integrated central mass difference with H_noAGN and H_DM close and broaden respectively. On the galaxy side, the story differs noticeably. Averaged stellar profile central densities and inner slopes are monotonically reduced by AGN activity as a function of cosmic time, resulting in better agreement with local observations. As both dark matter and stellar inner density profiles respond quite sensitively to the presence of a central AGN, there is hope that future observational determinations of these quantities can be used constrain AGN feedback models.
Although there are many more stellar population studies of elliptical and lenticular galaxies, studies of spiral galaxies are catching up, due to higher signal to noise data on one hand, and better analysis methods on the other. Here I start by discussing some modern methods of analyzing integrated spectra of spiral galaxies, and comparing them with traditional methods. I then discuss some recent developments in our understanding of the stellar content of spiral galaxies, and their associated dust content. I discuss star formation histories, radial stellar population gradients, and stellar populations in sigma drops.
Timing decisions are common: when to file your taxes, finish a referee report, or complete a task at work. We ask whether time preferences can be inferred when textsl{only} task completion is observed. To answer this question, we analyze the following model: each period a decision maker faces the choice whether to complete the task today or to postpone it to later. Cost and benefits of task completion cannot be directly observed by the analyst, but the analyst knows that net benefits are drawn independently between periods from a time-invariant distribution and that the agent has time-separable utility. Furthermore, we suppose the analyst can observe the agents exact stopping probability. We establish that for any agent with quasi-hyperbolic $beta,delta$-preferences and given level of partial naivete $hat{beta}$, the probability of completing the task conditional on not having done it earlier increases towards the deadline. And conversely, for any given preference parameters $beta,delta$ and (weakly increasing) profile of task completion probability, there exists a stationary payoff distribution that rationalizes her behavior as long as the agent is either sophisticated or fully naive. An immediate corollary being that, without parametric assumptions, it is impossible to rule out time-consistency even when imposing an a priori assumption on the permissible long-run discount factor. We also provide an exact partial identification result when the analyst can, in addition to the stopping probability, observe the agents continuation value.
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