Friday 25 January 2008

Molecular hydrogen in DLAs

Figure 5 in Noterdame et al (2008, arXiv:0801.3682)
Caption:
The figure shows the fraction of molecular hydrogen found in z~2.5 DLAs as a function of metallicity. The filled symbols show actual detections and the open symbols upper limits. These results is from a large survey of existing UVES data on DLAs but the results do not appear to be strongly biased by the heterogeneous nature of the data. The dashed horizontal line shows their adopted completeness limit and the dashed vertical line where they split their sample into low and high metallicity systems.

What is intersting is a) that selecting high metallicity DLAs is an efficient way to find systems with molecular hydrogen and b) that molecular fractions appear to be very low in DLAs. Neither was unknown but this is the largest compilation thus far and allows other correlations to be studied.

Where do early-type void galaxies come from?

(Figures 1+2 of Croton & Farrar, arXiv:0801.2771)

Not from anywhere particularly inspiring, apparently. The authors
investigate red and blue galaxy populations in voids using the
Millennium simulation. On the left are the predicted Millennium
galaxy luminosity functions (solid lines) and observed 2dF LFs for
the global sample (solid points) and voids (open circles). The right-
hand plot shows the predicted and observed LFs of red and blue void
galaxies, with galaxies at the centers of their halos (i.e. non-
satellites) shown as a dotted red line.

A "radio-mode" feedback model, efficiently quenching star formation
above a threshold halo mass but independent of environment, was
employed and tuned to fit only the global 2dF luminosity function.
As the left panel shows, this more or less automatically matches the
void galaxy LF as well, and reproduces the relative red and blue void
populations reasonably well (right panel). The authors conclude
there is no unusual physics going on in void galaxy formation, and
further that the presence of "red and dead" void galaxies is not
actually a big problem for galaxy formation models. As in denser
environments, red galaxies are simply those that occupy the most
massive halos.

Thursday 24 January 2008

Predictability in Semi-Analytic Models of Galaxy Formation


Predictability in Semi-Analytic Models of Galaxy Formation
Authors: Jaime E. Forero-Romero

http://arxiv.org/abs/0801.1953

Basically, semi-analytic models go all crazy non-linear for high mass galaxies. On the left is a grid of SAM of 10^10 M_sun galaxies for different star formation and feedback efficiencies. The right shows the corresponding 10^12 M_sun models. From top to bottom is total mass, stellar mass, and SDSS U-band magnitude respectively.

Large Scale Structures at High Redshift in the GOODS Field

Castellano et al., http://arxiv.org/abs/0801.3557 (conference proc.)

These authors identify overdense regions up to z~2.5 in GOODS-S using photometric redshifts. The most interesting feature is a proto-cluster at z~1.6. This figure shows the distribution of rest-frame color, mass, and M_B for candidate members of this proto-cluster (open histograms) and for field galaxies at similar redshift (filled histograms).

The candidate cluster galaxies tend to be brighter and more massive. There is also a prominent red sequence (and I suspect that the effect of interlopers is to contribute to the blue cloud, so the red sequence is probably even more prominent than is immediately apparent). These characteristics have been seen before at high-z, but this is a nice illustration and it is neat that they are able to do this kind of thing using photometric redshifts.

Wednesday 23 January 2008

The Intrinsic Properties of SDSS Galaxies


This is Figure 11 from Maller et al. (arXiv:0801.3286), which looks at the impact of inclination corrections on SDSS galaxies.

One of the things they do is show that Sersic index is not a good enough discriminator between disks and ellipticals (see also Van der Wel from last week); the axis ratio provides an important second piece of information. They also argue that the axis ratio is good enough to derive (wavelength dependent) inclination corrections.

This plot shows how the color--magnitude diagram changes with these inclination corrections: the left panel is uncorrected, the right panel is inclination corrected. In each panel, the yellow points are edge on (b/a < 0.35) galaxies; the purple points are face on (b/a > 0.85) galaxies.

Lots of the edge on galaxies are disks, and so heavily extincted -- so they can be even redder than the red sequence. Correcting for inclination (effectively assigning them the (g-r) colors of b/a > 0.85 -- ie, face on -- galaxies with the same K magnitude and Sersic index), most of these galaxies fall back into the blue cloud.

Things i think are cool: 1. the correction is not so important for the brightest galaxies; 2. there are precious few edge on systems on the red sequence after inclination correction: if this is right, then the quenching mechanism really is associated with the morphological transformation from disk to spheroidal.

There is also some discussion on how the inclination correction affects mass estimates, which comes up with some surprising (and i think fishy) results.

Friday 18 January 2008

The Dependence of Galaxy Morphology and Structure on Environment and Stellar Mass

Arjen van der Wel, http://arxiv.org/abs/0801.1995.

In this letter, the author distinguishes between morphology (i.e. early- vs. late-type) and structure (quantified using Sersic index). Although these two properties are correlated with each other, it turns out that it is meaningful to consider them separately.  In the scheme used in this letter, a galaxy is classified as early-type if it has a smooth light distribution, even
if the Sersic index is small. Conversely, a galaxy is classified as late-type if the light distribution is clumpy even if it has a high Sersic index.

The bottom panels show a strong relationship between galaxy structure (Sersic index) and stellar mass, with little residual dependence on environmental density. The top panels show a relationship between morphology (i.e. smoothness) and environmental density, with essentially no residual dependence on mass.

The key to interpreting these results is to realize that star formation tends to make the light distibution clumpy. So (specific) star formation rate depends on environmental density, while structure depends only on stellar mass.

I found this interesting because it seems to imply that whatever processes are responsible for reducing the star formation in dense regions are ~independent of the processes that determine galaxy structure.

Fwd: Galaxies Journal Club begins again


---------- Forwarded message ----------
From: Huub Rottgering <XXXX>
Date: Jan 11, 2008 10:30 AM
Subject: Re: Galaxies Journal Club begins again
To: "Edward Taylor (ned)" &lt;XXXX>

good that you start this again! attached my plot for next meeting. Huub

--
Huub Rottgering



From 0801.1170. The luminosity-halo mass relation for brightest cluster galaxies, Brough et al.
The authors measure the K-band luminosity and the halo mass (from X-ray emission) of 146 BGG and BCGs. They find that L_K is proportional to M^grad. They have plotted their data points (open circles) as well as other studies (squares) and models (stars) against redshift. They find no evolution in the luminosity-halo mass relation up to a redshift of 1. This suggests that the early-type BCGs grow steadily with the growth of their host cluster. A slope of 0.3 suggests that BCG growth is limited by the timescale on which dynamical friction causes satellite galaxies to fall into the centre. These observations are consistent with BCGs accreting 10-20% of their stellar mass as their host cluster doubles in size. Hence they can grow by less than 50% since z~1 i.e. most of the stellar mass in these massive red galaxies is already in place by z~1.

Nina

Tracking down a critical halo mass for killing galaxies through the growth of the red-sequence


Figure 1 from Gilbank & Balogh (astro-ph 0801.1930)
Catption: The evolution of the Dwarf-to-Giant ratio (DGR) for various samples, taken from literature and converted to a uniform system, as described in the text. Filled circles and open diamonds denote cluster and field samples respectively from observational data, and lines show (1+z)^\beta fits. Horizontal error bars indicate the redshift range covered by the data. Naked error bars are measurements from individual clusters. Only cluster ensembles are included in the fit. The filled square shows the highest density regions in the SDSS, which agrees well with the cluster data. Asterisks and triangles show predictions from the Bower et al. (2006) semi-analytical model, connected with lines to guide the eye. The dot-dashed lines show the predicted evolution of the field DGR if isolated galaxies have a constant DGR=0 and the observed trend is due to the increasing abundance of groups (having the same DGR as clusters) above the labeled threshold mass, Mth, with cosmic time.

This plot shows that the DGR evolves with redshift, consistent with the down-sizing picture, in which the termination of star-formation progresses from the most massive to the least massive galaxies as the universe ages. Although individual cluster measurements of the DGR show considerable scatter, the ensemble averages of clusters show a clear trend. The two main results are that the DGR of field-galaxies is always lower than that of cluster galaxies at the same redshift, and the DGR of both samples evolves with redshift.
The semi-analytical model fails to reproduces these two effects. One possible explanation for this is the inclusion of "strangulation" in galaxy formation models, where all the hot gas is removed from a galaxy as soon as it enters the dark matter halo of a more massive galaxy and becomes a satellite. This process may be too effecient.

The evolution of stellar mass and the implied star formation history

Figure 2 in arXiv:0801.1594, Wilkins et al.
Caption: The authors compile a number of measurements of the stellar mass density as a function of redshift and convert this to a star formation history. They then compare this to measurements of the instantaneous star formation history.

The plot shows the results. The dark solid line is a best fit to the star formation history inferred from the mass density history and the grey shaded areas denote the 1 and 3 sigma uncertainty regions. The various symbols are the measurements of the instantaneous star formation with different symbols denoting different methods of measuring the instantaneous SFR.

For redshifts lower than 0.7 the two methods of determining the star formation history agree quite well, but for larger redshifts there is a clear discrepancy between both methods. Suggested causes for this discrepancy include overestimation of the extinction correction and evolution of the IMF with time.

Post by Ernst Kuiper

Evolving mass-metallicity relation (Liu et al., arXiv:0801.1670)

(Figure 6)
Hi, this is Rik. The actual caption is too long and cryptic to quote verbatim, but this figure shows the (oxygen) mass-metallicity relation for z~1-2 DEEP2 galaxies (colored points) and z=0 star-forming galaxies from SDSS (contours). Oxygen abundances are determined by emission line ratios; in the left panel a diagnostic based on the [NII]/Halpha ratio is used, while the abundances in the right panel are effectively found through ([OIII]/Hbeta)/([NII]/Halpha).

Regardless of the measure, there's a strong shift in the normalization: at a given mass, galaxies at lower redshift are more metal-rich than at high redshift. This is reassuring. The effect is stronger for the abundance measure on the right (i.e. the one incorporating both [OIII] and [NII]) than the one on the left. Later on, through other line ratios the authors find that gas in z~2 galaxies is more highly excited, and thus has stronger emission lines, than at z=0. Some of this may be due to shocks and AGN, but for the most part the high-z galaxies simply appear to have higher interstellar pressures. This makes z~2 galaxies appear more metal-rich than they actually are (this is stronger with the [NII] indicator than the [OIII]/[NII]); thus, characterizing these ionization effects is crucial to accurately measure the evolution of the M-Z relation.

arXiv:0801.1193 - Halliday et al

Figure 6 in arXiv:0801.1193
Caption:
The authors create a composite UV spectrum from 75 (MIR selected) GMASS galaxies. Using this and the set of population synthesis models from Rix et al (2004; the 1978 index for the connoisseurs) they derive a stellar metal abundance of log (Z/Z_sun) = -0.574 +/- 0.159 [read this as an iron abundance]. This value is compared to models by Finlator & Davé (2007) in the figure above (red circles correspond to stellar abundance estimates at z~2 and black filled circles to gas-phase abundances at z~2). The triangles are gas-phase metallicities (oxygen) derived by Erb et al (2006) also at z~2.

The most immediate explanation for the difference between the stellar & gas-phase abundance is that we are seeing the effect of alpha-enhancement here.

Poster: Jarle Brinchmann

Wednesday 9 January 2008

Testing Cold Dark Matter with the Hierarchical Buildup of Stellar Light

Balough et al., astro-ph/0801.0990, Figure 2

caption: The stellar mass fraction f∗= M∗,500/M500, including intracluster light, is shown as a function of total mass M500. The LM data (red squares) include a correction for ICL estimated from the GZZ data (circles). The two open circles represent clusters A2405 and APMC020, which are systems strongly affected by line-of-sight structure. The 1 error bars are
derived from the published uncertainties on M500, and the tilt reflects the correlated uncertainty in M500 and M∗,500/M500 as described in § 2.2. The horizontal, dotted line shows the global baryon fraction measured by WMAP3 (Spergel et al. 2007). The two solid lines show constant slopes of −0.35 and −0.05, for comparison with our most conservative theoretical lower limit, and the Bower et al. (2006) model prediction, respectively.

Based on LCDM simulations, the authors argue that the steepest slope you can get for the plotted relation is about -0.35; the observations suggest something more like -0.65.

The basic method is to assume a relation for M*/M500 as a function of M500, feed it into a collection of LCDM merger trees, and then look at the z~0 M*/M500--M500 relation that comes out : if you get too many groups/clusters with values of M*/M500 which are too high, then this model is inconsistent and can be ruled out; groups/clusters with values of M*/M500 which are too low need some in situ star formation to preserve the relation. Essentially, the 'mixing' that comes with merging halos of different masses leads to M*/M500 being more or less independent of M500 -- lots of merging leads to a flat slope. The steepest slope for which the authors find consistency is around -0.35, even allowing the relation to evolve. This appears to be consistent with one shallower data set, but not a deeper one.