Blogging Update

I've been a very bad blogger recently. Basically this is because I've been spending all my time working on a project with people at Berkeley, and so there isn't as much need to post, as I was mainly using this blog to communicate to Alexia on our project. Alexia, if you are reading this I haven't given up on our project, and in fact much of the work I am doing now will be useful for us. However, considering I want to graduate this year, I've been pushing forward on this new project that is working, and close to being publishable.

My collaborators at Berkeley have wanted me to keep quiet about my new project's results (until we publish), and so I've not been able to post plots etc. for this project. However, I do find it helpful for organization and motivation to write on this blog, so I think I'll start writing on it again, if nothing else that to say what I did that day.

I've been working a lot of error analysis for my correlation functions. I have bootstrap/jackknife analysis in place and have been doing various fits to the correlation function to try to figure out the errors. It's strange because depending on what fitting methods I use, I get wildly different errors... and sometimes it seems like I am getting a statistically significant result (3+ sigma) and other times not.

I've also been much better at writing self-contained code that is easily re-runnable. I used to drive Alexia crazy will all the "cutting and pasting" I was doing. Well no more. I know am doing object-oriented programs with lots of functions etc. It's actually really nice.

I've been learning a lot more about python. Using cool fitting tools and statistics tools. Python is such a powerful language.

On the Market

Hello readers!

I'm officially on the job market this year. Aiming to graduate in June, and hoping to start working the following fall. If you like what you've been reading, please consider hiring me.

Due to a "two-body" problem, I am mainly looking at jobs on the west coast of North America (Los Angeles, San Francisco, Seattle, Vancouver) and New York City.

Please visit my web site for more information.

I hate IDL

I've been working a little bit in IDL for this new project because all the data is in fits files, Alexie has a lot of code that is in IDL which we are using to handle the CFHT data.

Anyway, I spent all morning struggling trying to do very simple input and output from this stupid stupid language.

I learned a few things, and since I hardly ever code in IDL, I am sure I'll forget unless I write them down right now. So here we go:

1) Tag names

You can get the tag names from a structure like this:

tname = tag_names(struct)

2) Merging structures

You can merge two structures as follows:

str3 = create_struct(str1,str2,NAME='str3')

3) writecol bug

For some reason when I try to use writecol to write out data, if there are more that 6 columns, and I don't specify the format, it puts a return carriage in the middle of the data. This goes away if you specify the format:

thisfile = './qsosMergedInfo.dat'
writecol,thisfile, qsos.ra, qsos.dec, qsos.z, qsos.zwarning, $
qsos.flux_clip_mean[0],qsos.flux_clip_mean[1], qsos.flux_clip_mean[2], $
qsos.flux_clip_mean[3], qsos.flux_clip_mean[4], fmt='(f,f,f,f,f,f,f,f,f)'

More streamlining

Martin White keeps telling me I should streamline my code/runs so that it is really easy to re-run with new data/subsets.

I've been working on doing that for running the correlation functions, and running the error analysis. I've written code:

../Jessica/qsobias/Correlate/runCrossCorrelationJackknifeMulti.py

That takes the run directories, and qso-file names as inputs (along with other constants for the correlation) and runs the correlation on all those different files at once.

Then there is code that compares the correlation functions and makes a bunch of pretty plots. I'm running it for the first time now. Hope it all works!

Oh, and I need to talk to Martin White about what to do when certain realizations of the bootstrap/jackknife are negative. This causes problems with fitting the power-law, and also isn't physical. Currently I re-run the realization if it has a negative value for the correlation function, but I don't think this the right thing to do, as it is biasing the bootstrap to have higher clustering values.

Black Hole Masses

I had a nice chat with Benny Trakhtenbrot this morning about calculating black hole masses and his research. He had some useful suggestions. First he suggested that I look at the McLure and Dunlop 2004 paper instead of the Vestergaard and Peterson 2006 for calculating the black hole masses. I should ask Martin if he agrees.

He also suggested that I talk to Yue Shen about his catalogs of black hole masses (or maybe it was line widths). I don't know how different this is to the catalog that Ian McGreer has given us.

He also thought that perhaps we might want to do a separation by Eddington ratio and see if there is a clustering dependence there.

He was very helpful, and overall a productive meeting.

I've been working on trying to get a stronger clustering signal separation. So far divided the QSO sample into even brighter/dimmer sets. As well as applying a uniform redshift selection to my two samples to see if what I am measuring is actually a redshift separation, not luminosity. Fun fun fun!

Cambridge Fan?

So apparently I have a very regular reader in Cambridge, England. I was checking out my Google Analytics statistics for this blog and my personal web page yesterday (I was wondering how many people had looked at my likelihood post/paper). To my surprise, I discovered that between last March and today, and single individual in Cambridge has looked at my blog 238 times, and my personal web page 267 times. That is an average of 2.8 visits per day!

Who are you Cambridge, England? And why do you find my blog/web page so interesting?

Perhaps it is Stephen Hawking looking for inspiration? The strange thing is that I don't actually know anyone in Cambridge.

The only other city with anywhere near this many visits is Berkeley (44 on my web page, and 181 on my blog). However these visits are from 31/64 different people in Berkeley, whereas the Cambridge visitor is ONE person.

Thank you Google for providing me with such detailed information about my followers. Who else is out there reading this? Roll Call people.

My Blog

My Web Page

Likelihood Accepted!

It's been a long process, but the likelihood paper was accepted by the Astrophysical Journal this week. I submitted my final draft to them today, as well as resubmitting the accepted version to the arXiv! So happy to be done with that chapter of my research and able to focus on new work!

Here is a link to the paper!

Likelihood Paper (Final version)