OK, now for something a little different. In this post I'm not going to talk about stuff we already know or get right, but the stuff we think we may be getting wrong. That may seem a little negative, but is in fact what astronomers spend much of their time doing. We constantly check, question, argue, ponder … it's only when we've run out of ways to challenge an idea or result that we then tend to think we may have just learnt something.
We've heard before about galaxy environment, and more specifically, the relative importance of galactic nature vs. nurture. Measuring environment (or nurture) has become increasingly popular in recent years, mainly because it's become increasingly possible to do.
In particular, large space-bound telescopes, like Hubble, and the galaxy surveys they produce, like CANDELS, have been especially important in the search for, and classification of, rare yet impressive cosmic structures called galaxy clusters. This has sparked a kind of friendly competition within the community to find increasingly distant clusters in the early Universe. For astronomers, it's a bit like searching for the earliest fossilised pre-humans: a trophy when you can beat the previous record, and (more importantly) juicy new clues to early galaxy life within the cosmos.
|An early forming galaxy cluster, but is this a real over-density or |
artificial? Credit: Papovich et al. 2010
A perfect example is the 2008 discovery of a early forming cluster at redshift 1.6 (about 9 billion light years distant) by CANDELS team member Casey Papovich and collaborators. This cluster was first identified using the Spitzer Space Telescope in the infrared, and the galaxies within were recently studied using CANDELS data to measure their structural properties, types, masses and colours. However, to date, only 13 galaxies in the cluster have been confirmed to be at the distance of the cluster centre to any precision.
This highlights a problem: when clusters become distant and hard to find, how do we know if we've actually found one? Let me propose that you have to answer three challenges before you get to pop the champagne cork on a new cluster distance record:
- Demonstrate that the galaxies making up the cluster aren't just a chance alignment of unassociated galaxies along the line-of-sight. When you only have very rough distances, which is often the case (called photometric redshifts in astronomy-speak), such alignments can be a very common occurrence, and tricky to recognise.
- Show that the "reality" of the cluster doesn't depend on the method used to find it. There are many environment "metrics" employed by astronomers, typically based on counting galaxies projected on the sky within a fixed radius, or by an association of nearest neighbours. But the measurement techniques are varied, the uncertainties large, and the agreement between them approximate at best.
- Even when you've found a genuine cluster, how do you actually know what it will evolve in to? Simulations have shown that some structures grow fast and some slow, and there's no way to know in advance. It may be that the future for this particular object is rather boring and not the "Australopithecus" you were expecting.
At Swinburne, my graduate student Genevieve Shattow and I have been looking into these issues using CANDELS-based simulations of galaxy and cluster formation. These simulations are useful because we have "perfect" information for every modelled galaxy, unlike the real observations. By perfect I mean that every property of each dark matter halo and galaxy are precisely described (because we made them!), and the history of each is fully identified. We can use this information to our advantage.
With this simulation we looked at the most massive cluster at redshift 2 (i.e. when the Universe was 1/3 its present age, and where the current distance record is) and asked:
- How accurately can we identify the cluster if we degrade our information to be comparable to that of real observations?
- When we apply different environment measurement techniques, do they paint a consistent picture? Or do they return different answers?
- What will this object evolve into? Is it actually interesting? Is there a way to separate the interesting objects in the distant Universe from the more mundane ones without knowing in advance?
We're still working on these problems, but let me show you a few early, yet slightly disturbing results.
The above figure shows how galaxies in the larger environment around this simulated cluster appear on the sky if observed at four different times, ranging from the present day (far left) to redshift 2 (far right). We've coloured the galaxies: purple shows the actual gravitationally bound cluster members, while black are the non-cluster galaxies. The circle represents the typical radius astronomers would count within to look for over-densities, signalling the presence of a cluster.
As you can see, finding a cluster in the present-day Universe is fairly easy as there are many galaxies around to characterise it. In the early Universe though it's not so clear. Even worse, the ratio of cluster to non-cluster galaxies tips in an uncomfortable direction, making it hard to distinguish the actual cluster members from the background of field galaxies.
|Different viewing angles of the same|
cluster return different cluster
membership due to projection effects
We can play an even more illuminating game with the simulation. Let's again look at this single cluster and its surroundings at redshift 2, again projected onto the sky, but now from many different angles. Since galaxies in three dimensions will project differently on to the two dimensional sky depending on the viewing angle, the measured environmental over-density within the circle will vary. But by how much?
The distribution of counted galaxies based solely on changing the viewing angle is shown in the figure on the right. As can be seen, the environment measure may find 60 cluster members, or it may find 80 cluster members. That's a big difference for what is in essence exactly the same object! Given that we can't correct for such projection effects in real observations, this highlights a substantial uncertainty in any such measurement.
This is just the beginning of our work, but important to quantify if we're to have an honest accounting of the issues around measuring galaxy environment in real data. In doing this we'll be looking for ways to correct such biases, hopefully making the job of cluster identification easier and more accurate. This will enhance the value of data from galaxy surveys such as CANDELS and the science that follows from them.