The Last Eight-Billion Years of Intergalactic CIV and SiIV Evolution 

~~~~~~~~~
ABSTRACT

The low-redshift (z < 1) IGM probes the last eight-billion years of
metal enrichment from galactic feedback processes. Outflows and
mergers return to the IGM enriched material for future generations of
galaxies and stars. The signature of this process is etched in the
recycled gas: metallicity, abundances, density, distribution, etc. We
conducted the largest survey for C IV and/or SiIV systems at z < 1,
and we compare our results to those from high-redshift (1.5 < z < 6)
studies. For example, we present the frequency distribution f(N) and
mass density of C IV and SiIV absorbers in the HST archival spectra of
49 quasars. The changes in the properties of the low-redshift systems,
compared to the high-redshift ones, indicate that CIV and SiIV more
commonly trace circum-galactic gas at z < 1.


~~~~~~~~~
1. The Last Eight-Billion Years of Intergalactic CIV and SiIV Evolution 

Thank you for inviting me to speak and hosting me for a full day. I
will be discussing the chemical composition of the low-redshift (z <
1) IGM, specifically focusing on the CIV and SiIV absorption
lines. Please feel free to ask questions at any time.

My collaborators for this work are my thesis advisor, Xavier at UCSC; Chris
Thom, a postdoc at STSCI, and Hsiao-Wen Chen, a professor from the University of
Chicago.


~~~~~~~~~
2. What's to come...

I will be motivating why you should care about this research first
(obviously). Then I'll describe the technique briefly. The majority of
the talk will be about the observations, their analysis, and the results.

The Wordle tag cloud is a summary in its own right.  The size of the
words are proportional to the frequency with which they occur in the
two papers I'm discussing. I probably spent all together too much time
getting the LaTEX text to be like normal text (so things like \citet
don't show up.)  


~~~~~~~~~
3. Science Drivers

Let me frame the broad context. These are the fundamental questions I
have. They are important questions because they affect e.g., star
formation, galaxy colors and morphologies, etc.

How many metals are produced in the Universe? This is a question about
star formation and anything/everything that affects it.

Where are they? We, who are made of many metals, are not in stars,
where the metals are produced. Metals are observed in many places in
the Universe.

How did they get there? We observe metals not in stars. We also
observe metals being released from stars in a variety of ways.

For this project, we observed the metals that are not in galaxies
(though they may be close, hint, hint), and we leveraged cosmological
simulations to interpret some of the observations as well as our own
simple models.


~~~~~~~~~
4. Cosmic Chemical Enrichment Cycle

The whole time that stars are forming and dying you have chemical
enrichment, and it's a cycle. The stars produce the metals. Those
metals will end up in the ISM, halo, and/or canonical IGM. They get
there through some outflow mechanism. Wherever they may go, they could
end up in a star again. Even some of the "more escaped" material may rain
back into a galaxy.


~~~~~~~~~
5. "Feedback"

Let me give my working definition of feedback. Feedback is stars
and/or AGN moving material (gas, metals, etc) and energy. We observe
these processes as winds, jets, bubbles, etc in galaxies.

The movement of material and energy affects the e.g., star formation
rate (if there's less gas or it's higher temperature gas, star
formation will be suppressed). Also, feedback may change the physical
condition of the gas (temperature, density) which changes what ions
are observed in absorption. The distribution of the gas is also
affected by feedback. For example, here are 100 kpc/h boxes of the
same z=2 galaxy in a suite of simulations with different physics.

Feedback affects the immediate vicinity of the source of the feedback
as well as things farther away (and how far is "far" depends on many
factors). And feedback happens over all time. 


~~~~~~~~~
6. Quasar Absorption-Line Spectroscopy

We used quasar absorption-line spectroscopy to study the metals
in the IGM. Here is a classic diagram of how quasar absorption-line
spectroscopy works. Light from the background quasar is absorbed by
the intervening gas at wavelengths characteristic of the elements
in the gas. The light passes through the quasar's local environment
(intrinsic), the cosmic web (intergalactic), and our Galaxy's gas.

The most direct observables for quasar absorption lines are: the
number of lines of interest, their redshift (after you identify them);
their rest equivalent widths (the strength of the absorption); and the
column density (which we measure by the apparent optical depth method,
so it depends on the amount of absorbed flux).  Column density is a
physical property of the gas, whereas equivalent width is the observed
quantity. So this talk describes the results from analyses of the
column densities.


~~~~~~~~~
7. QAL Spectroscopy in Action

Here's a movie demonstrating how the light traveling from the
background quasar is absorbed by the intervening material in a fashion
characteristic of the material (elements, distribution, etc).  

High-redshift spectra have a lot of lines. At z < 1, we don't have to
suffer that much. But notice that red-ward of the quasar Lya emission
line, the density of lines is less. There are only metal lines
there. 


~~~~~~~~~
8. Metal Absorption Lines Affected by...

(And I'm mostly referring to the number of lines observed and their
column density here.)

More metals and more of the particular metal of interest can increase
the number and/or strength of the transitions observed.

The ionizing background changes the favored transition of any given
element.

The physical distribution will change the number of lines and their
strengths.


~~~~~~~~~
9. Ultraviolet Background and Ionization Balance

Here's a quick plot of how the UV ionizing background affects the
strength of transitions in an optically thin, plane-parallel slab of
gas with solar relative abundances and metallicity one-tenth solar.
As the background intensity increases, the carbon becomes more highly
ionized. 

I ignore shape of the UVB in this plot, though the shape becomes
important when considering absorption systems with both SiIV and CIV
doublets.


~~~~~~~~~
10. Physical Distribution

The number of lines observed changes from high redshift to low. But
that doesn't mean that the number of lines per redshift changes. Even
more important is to look at the absorber line density dN/dX, which is
the product of the co-moving number density of the lines and their
physical cross section (also co-moving).  Evolution (or no evolution)
in dN/dX has physical implications about the distribution of the gas
through time.


~~~~~~~~~
11. Observations

Here are the two papers summarized in this talk (and their word cloud
summaries).  The latter is oh-so nearly ready for submission...


~~~~~~~~~
12. Archival Spectra

We culled the HST archive for targets with STIS and/or GHRS (UV)
spectra. Of the almost 70 targets that had such data, only 49 had
spectra with the right wavelength coverage (CIV is at 1548, 1550 Ang
and SiIV at 1393, 1402 Ang), resolution, and signal-to-noise.

We incorporated any FUSE observations of the same targets for coverage
of shorter wavelength transitions. 

The STIS spectra made up the bulk of the coverage. The echelle
gratings were really the movers and shakers of the surveys. The E140M
grating covers CIV up to z ~ 0.1 and SiIV < 0.2, and there's a lot of
E140M observations. The E230M grating covers CIV from z ~ 0.4 to 1
(SiIV 0.6 to 1.2) depending on the tilt (it can cover down to z =
0). The other STIS gratings and the GHRS spectra make up the rest.

Across the top is marked the redshifts of the final CIV and SiIV
samples.


~~~~~~~~~
13. Automatic, Blind CIV and SiIV Surveys

We conducted a (mostly) automated, blind survey. First we
automatically detected absorption lines. Then we had the computer pair
up all lines that had roughly the characteristic separation of the CIV
(or SiIV) doublet.  In a similar fashion, the computer tacked on other
common transitions (such as HI Lyman lines).

CIV and SiIV are resonant doublet lines, which are very
observationally useful. First they have characteristic separation and
EW ratios. Second, their rest wavelengths are red-ward of the Lya 1215
line, so that CIV and SiIV can be detected outside the Lya forest
(i.e.,  less blending). Also, the doublet lines have very similar
profiles when not blended.

In a velocity plot, the various transitions associated with one
system are stacked in velocity space, determined by the rest
wavelength of the transition and the redshift of the system, in this
case, the redshift of the CIV 1548 line. They show how well aligned the
transitions are and how the profiles compare. 

We assigned flags to the candidate CIV (SiIV) systems based on ideal
characteristics of actual CIV (SiIV) systems, such as how similar their line
profiles are or if they have other lines associated with them. 

Then we visually evaluated the candidates, voting for the ones we were
confident were actual CIV and/or SiIV systems, and adjusting a few
details (e.g., boundaries).


~~~~~~~~~
14. Final CIV and SiIV Samples

In the end, we had two groups. G = 1 is the group of definite CIV (or
SiiV) absorbers, and the G = 2 group is the likely CIV (SiIV) systems.
We'll only analyze systems with both doublet lines detected at greater
than 3-sigma in equivalent width. (Other studies make other cuts.)
This leaves us with 38 G = 1 CIV doublets and 20 G = 1 SiIV
doublets. And I will only talk about the G = 1 sample; adding the G =
2 sample does not change the results.

For some analyses, we divided the G = 1 CIV group at roughly the median
redshift to see what we could with regards to evolution. There was no
evolution of statistical significance within either of our samples.

There's a slew of other checks we made that of course took a lot of
time but do not merit more than a mention. HI Lyman lines are the
biggest contaminate to our survey, which we did _not_ restrict to
outside the Lya forest, so we had to characterize how that affects our
results. (Not much.) We used what published results there were as
checks to our methods. We made our own line lists. We did a special
check that the CIV doublets weren't actually OI 1302, SiII 1304 at
another redshift; this pair has about the same wavelength separation
as the CIV doublets. Since our automatic blind search depends relies
solely on the separation, this was a smart check (thanks to Edward
Jenkins for telling us to do it). Unfortunately, there was a mix-up
with one G = 1 CIV doublet, that was realized when we analyzed the
data for SiIV.


~~~~~~~~~
15. Luminosity Function Analogy

The fundamental result of our surveys were the column density
frequency distributions of whatever ion was of interest (CIV or SiIV
actually). The frequency distribution is similar to the luminosity
function of galaxy surveys. Likely, people are familiar with the
galaxy luminosity function, so I just wanted to run through the
similarities between these two quantities. The luminosity function is
the number of galaxies per luminosity bin per unit volume surveyed
where such galaxies can be observed. I'm using magnitude and
luminosity interchangeably here.

Once you have the luminosity function, you can integrate it to measure
the e.g., total number of galaxies per unit volume or the total
luminosity density.

Measuring the volume surveyed is crucial. It's what dictates the
faint-end slope. The same is true for the frequency distribution. A
lot of time was spent on estimating the co-moving pathlength dX
sensitive to the observed absorbers (their column densities).


~~~~~~~~~
16. N(C+3) Frequency Distribution

Here is the CIV column density frequency distribution f(N). It
looks like a power-law, so we fit that through a maximum likelihood
method that included the number of saturated doublets as a constraint,
because we only had lower limits on their column densities. 

For the full G = 1 sample, the exponent is -1.5+/-0.2, that includes 36
CIV doublets. 

I'm setting up a pattern where I introduce a quantity (like f(N)) for
just the CIV survey. Then, in the next slide, I compare and contrast
the CIV and SiIV samples.


~~~~~~~~~
17. Frequency Distributions 

Laying the two column density frequency distributions side-by-side, we
can see, from the normalization of the two distributions, that CIV
absorbers are more common (which will be born out in the next pair of
slides).  This is reflected by the normalization of the power-law fit
being greater (though the caveat here is that the normalizations are
actually normalized differently, CIV is set to 10^14 cm^-2 and SiIV is
set to 10^13.5 cm^-2). The second thing you can read off, is that
there is a greater incidence of high-column density CIV doublets than
there are of high-column density SiIV. This is reflected in the slope
of the CIV sample being shallower. HOWEVER, within the error bars,
these two numbers are in agreement.


~~~~~~~~~
18. CIV Absorber Line Density

I mentioned the absorber line density earlier.  We actually measure it
by weighting the absorbers above the limit of interest with dX. The
0th moment of the frequency distribution (or the integral over column
density) is the fit.

Just a reminder, because it becomes important later, this quantity
dN/dX is the result of the distribution of the absorbers... the
product of their co-moving number density and cross section.


~~~~~~~~~
19. Absorber Line Densities

As I read off for you on the frequency distribution plots, the
incidence (dN/dX) of CIV absorbers is greater than for SiIV doublets.

Neither of my rather large redshift bins (considering the time period
covered), show any sigh of evolution within them. 

~~~~~~~~~
20. Absorber Line Densities: Evolution?

We looked at the (redshift) evolution of the absorber line density by
comparing to the integrated value from Songaila (2001) for CIV and the
integrated values from Scannapieco et al (2006) for SiIV (also from
Boksenberg et al (2003)).  People have not published the information
for us to do better than this.  The background points are the summed
values for absorbers with log N(C+3) >~ 12 (actually not properly
corrected).

The increase in dN/dX from z = 3.2 to z = 0.6 is detected with
statistical significance. But in light of the fact that 12 Gyr separate
these measurements, it's intriguing that the physical distribution
(co-moving number density and cross section) have conspired to change
by less than a factor of 2.   Any change in SiIV is less dramatic (and
the error bars here for the high-redshift studies are
underestimated). 

Since dN/dX changes little to not at all, for the last 12-billion
years, the co-mooving number density and cross section must both not
have changed or both changed in opposite ways to preserve dN/dX. 


~~~~~~~~~
21. C+3 Mass Density

I mentioned that measuring the C+3 mass density at z < 1 was a
motivator for this project. Here is the definition of Om(C+3), the C+3
mass density relative to the critical density of the Universe.  Again,
integrating the frequency distribution to get the mass density is very
similar to taking the first moment of the luminosity function to
measure the luminosity density of the Universe.

All the other studies to which we compare use the sum of the column
densities to measure the mass density. They typically include all
absorbers they detect, which is log N(C+3) = 13 to about 15 and log
N(Si+3) = 12 to 15.

We can't use the sum because of saturated absorbers and how we measure
the column. We would only have a lower limit to the 13 <= log N(C+3)
<= 15 Om(C+3).  So we use the integral of our best-fit power law.

See here, for our alpha > -2 power law slopes, the mass density is
infinite and dominated by the stronger absorbers. 


~~~~~~~~~
22. Mass Densities over Age of Universe

For both CIV and SiIV, the mass density appears to have
increased. However, for CIV, this is a statistically provable increase
(having larger number of low-z doublets and high-z studies). 

For SiIV, it's less statistically secure (< 2 sigma).  I purposefully
made these plots different because we had to treat the high-redshift
studies differently, largely due to statistical size.

The variance-weighted average of the 1.5 < z < 5 CIV studies is
(2.2+/-0.18)x10^-8.  The unweighted mean of the SiIV studies is
(0.85+0.34/-0.3)x10^-8. 

We also fit a line to the data as a function
of time. This is no more than a toy model. The slope is unconstrained
for the 1.5 < z < 5 data, so it wasn't known whether they were
evolving or not because the data allowed for anything. 

But including our data points, we have a 2-sigma detection of the
slope for CIV and >3-sigma for SiIV. The low-redshift data adds the
evidence to show that Om(C+3) and Om(Si+3) are evolving, even from z =
5 to 1.5.


~~~~~~~~~
23. Ionic Ratio N(Si+3)/N(C+3)

Now that we have two experimentally uniform samples of CIV and SiIV
absorbers at low-redshift (our samples) and at high-redshift
(Boksenberg et al 2003), we can explore what the ratio is doing for
the last 12-billion years. As it turns out, not much of anything.
Since we have limits in both samples, we used survival statistics to
test whether the two groups are drawn from the same parent populations
(which they were) and if there is any correlation with redshift (which
there isn't).


~~~~~~~~~
24. Physics Affecting N(Si+3)/N(C+3) (I)

What physics are folded into the simple ratio of SiIV to CIV column
densities? Three factors: 

1) The spatial distribution of the enriched gas that is doing the
absorbing.  Since the the profiles of the SiIV and CIV doublets trace
each other quite well, there are no obvious systems where the ratio
varies significantly between components. Therefore, the first term is
effectively one. 

2) We know the metallicity of the Universe increases with age, but the
relative abundance of silicon to carbon does not, necessarily, follow
suit. Hence, the evolution in the second term is unclear, and we're
not in a position to discuss it. (Cosmological simulations would be
useful here.)

3) We took a stab at understanding the effect of the third term by
running a suite of CLOUDY models that varied some basic physics,
namely the shape and strength of the ionizing background. The
ionization balance for any given ion depends on how "well" lower
transitions are being ionized into the one of interest and how many
photons are ionizing the one of interest up to a higher transition.


~~~~~~~~~
25. Physics Affecting N(Si+3)/N(C+3) (II)

The most surprising result is that we do not necessarily need a "soft"
UVB (i.e., 'G') to find a lack of evolution in the ionic ratio over
redshift. I want to emphasize that we did NO FITTING with CLOUDY. The
plot is just representative of what we can do. The overall
normalization of these curves are nearly freely scalable with other
assumed parameters in CLOUDY.

Cosmological hydrodynamic simulations would be the best way to study
the randomly drawn sample that is the observations. In other words,
the observed SiIV and CIV samples are not probing just one type of
cloud, as modeled in this CLOUDY plot.


~~~~~~~~~
26. Summary

We have shown that the co-moving number density and the cross section
of absorbers have conspired to make dN/dX change by less than a factor
of two in 8 Gyr.

The 13 <= log N(C+3) <= 15 C+3 mass density has increased almost
threefold in the same time. 

Therefore, the typical column density of the absorbers at z < 1 is
higher than at z = 1.5 to 5. 

This suggests that CIV absorbers are tracing higher density gas at z <
1. We can even go so far to say that they're tracing circum-galactic
gas whereas before they were arising more in intergalactic gas. This
is supported by Hsiao-Wen's earlier work that most galaxies at z < 1,
no matter their luminosity or morphology, have CIV envelopes extending
to ~100 kpc.

There's a lot of conspiring going on in the Universe because the ionic
ratio N(Si+3)/N(C+3) also does not change, and that depends on
relative abundances and the ionizing background. 


~~~~~~~~~
27. This slide intentionally left blank

~~~~~~~~~
28. Evolution of the Cosmic Web
~~~~~~~~~
29. Survey Sensitivity
~~~~~~~~~
30. Survey Sensitivity
~~~~~~~~~
31. Lya Contamination
~~~~~~~~~
32. Example CIV: GHRS Detections
~~~~~~~~~
33. f(N(C+3)) by Redshift
~~~~~~~~~
34. C+3 Mass Density: Evolution?
~~~~~~~~~
35. C+3 and Si+3 Mass Densities: "Modeling" Temporal Evolution
~~~~~~~~~
36. Effect of log U on CLOUDY models
~~~~~~~~~