Brookhaven job

I have accepted a position at Brookhaven National Lab. I posted about it in my other blog

M/L modeling; papers accepted

M/L Modeling

I'm creating some new measurements that make it simpler for Jeremy Tinker to model our mass-to-light ratio (M/L) results. To create his models he uses Zehavi's correlation functions for r-band selected samples. In my M/L paper I used i-band selected galaxies. It turns out the only way this modeling was going to get done is if I repeat my measurements for r-band limited galaxies. It took a week of running on a cluster of computers here at NYU and I now have the basic light measurements done. This was much faster than the previous measurements because I only measured the light correlation functions to 2Mpc. Now I need to do the analysis, which I hope to get to after my trip to Brookhaven this week.

Papers Accepted

Paper I, the cluster lensing measurement paper, and Paper III, the M/L paper were both accepted to ApJ this week. I've spent the last few days working with ApJ to create downloadable data tables that will accompany the papers, and accompanying "preview" tables to go in the papers. I also plan to make the data available online with links placed with the arXiv abstract.

Cluster Centers and Mass Scatter

Centers

One of the uncertainties in understanding the lensing results for the MaxBCG cluster sample is the center of mass. We know that some of the time our chosen center, the location of the brightest cluster galaxy, is not at the mass peak or the center of mass. On the other hand, the theoretical predictions for dark matter mass profiles are predicted around the mass peak.

We have put together two alternative centers, both based on finding a peak in smoothed density maps. One is in the number density and the other is in the luminosity weighted number density. It looks like we can flag bad centers when neither of these new centers agrees with the BCG location. Evidence comes from the X--ray concentration and also from lensing. I compared the mass profiles for "good" and "bad" centers at fixed cluster luminosity and found significant differences in the profiles. We still haven't figured out what is the best center, but we can now flag bad ones with some level of confidence.

Mass Scatter

The variance in the mass measurements we get from lensing are the convolution of many different sources of scatter. There is the scatter in mass at fixed richness, which is what we are interested in. But on top of this is the scatter from measurement noise sigma_err and the intrinsic variance among galaxy shapes for the background sources sigma_SN. These two sources of scatter are well known. But even on top of that is the variance from unknown sources of systematic error. We can guess at what these are, such as variance in the signal calibration as a function of observing conditions.

I looked at the inferred scatter sigma_tot^2 - sigma_err^2 - sigma_SN^2. I found that the residual scatter is much larger than the expected sigma_m^2 based on other measurements, such as X--ray properties and velocity measurements.

Next I want to figure out how to estimate other sources of variance. The goal is to design a measurement that does not also include the variance in mass of the lenses.

Lensing papers submitted to ApJ

All three lensing papers have been submitted to ApJ. We now have eight papers out based on the MaxBCG cluster catalogs: the catalog papers (I,II), a cosmology analysis based on the number counts and selection function (III), a velocity dispersion paper (IV), a stacked X-ray luminosity paper (V) and three lensing papers (VI, VII, VIII). Soon, a ninth paper by Sarah Hansen on galaxy populations in the MaxBCG clusters will appear.

Lensing papers on astro-ph

The lensing papers were posted on astro-ph last week. Here are the links:

  Paper I:   Measurements        astro-ph 0709.1153
  Paper II:  Modeling/Inversions astro-ph 0709.1159
  Paper III: M/L                 astro-ph 0709.1162

There are still questions about calibration at the 10% level. We did the best we could with the data we had, I know that. But over the year since the initial measurements were made there have undoubtedly been improvements in our understanding of the photozs. But this is part of science; we have to publish sometime and we will incrementally improve our understanding as we go. Because this uncertainty comes in as a calibration, an overall amplitude, we can always re-calibrate the results in the future.

Erin

Collaborations

I've learned something extremely important about collaborations. It is something that people have often tried to tell me but I didn't have the experience to understand fully. Please note this is not a knock on any of my collaborators but simply a general observation:

You must set hard deadlines for the completion of papers.

I think at first this statement can seem either obvious or irrelevant to many people, but I'll explain why it is certainly not irrelevant.

First of all, it doesn't matter how good your work is if you don't communicate that work to the outside world efficiently. You won't be able to continue your good work because you won't be supported. And if you are in a collaboration your work depends on others, and you must consider others in order to produce efficiently.

This has been really hard for me to accept, because internally my motivation is to follow my interests, and that is it. This is true for most scientists I think, especially after they finish graduate school.

But when you join a collaboration most people are interested in lots projects but they themselves are the lead on at most one or two of those projects. But they have excellent ideas concerning all of the projects. This is where the fundamental problem arises: how do you get people to contribute work to your project on your timescale?

What usually happens is you think of a project and start working on it. You tell your collaborators about it. You think of all the most important issues right away and deal with them. Then you start thinking of not so obvious issues and work on them. Then the work starts to feel like it's ready to share with the larger community. You must do this in order to be supported. You write it up and send it off to collaborators. For the first time, your collaborators start to really think about the project, and they have many good ideas. Most of them you already thought of but there are some ideas you have yet to address. Addressing these new issues often requires work from you, but it often requires a fair amount of work from the individual collaborator because only they fully understand it. So you end up delaying publication for a while, sometimes a long while.

If only everyone involved knew from the beginning that the paper would be released on an exact day, with no possible delay, they would have been forced to think about the project from it's inception in order to contribute. They would have realized that some input was needed from them up front. They would have done this work while you were working. Most of these issues would have been dealt with by the time the first draft was written.

Collaborating is worth while because I learn so much by seeing other people's perspectives. And everyone has such varied skills that the work is always better for it. The theory is that a deadline is an impersonal rule that once established should help to keep the ideas and work flowing more naturally and efficiently.

Erin

M/L paper really close

I know I said it was close before, but unless something comes up it should be out in a couple of weeks. If things move fast it could come out with papers I and II, which should come out this week.

For those who want a preview: the M/L goes as M^0.33 within r200, the M/L reaches an asymptotic value on large scales (20Mpc) and when you multiply that number by the luminosity density you get 0.20 +/- 0.02. There is a factor of bias on that too, but we don't know what it is exactly other than it should be of order unity.

Erin