Life as a Physicist

I was reading an internal note today and stumbled on this great quote:

The success of the standard model (SM) has been quite unexpected, given its shortcomings. The number of free parameters ranging many orders of magnitude, absence of Dark Matter candidates, the hierarchy problem, lack of gauge coupling unification, and no path to incorporate gravity naturally lead to the belief that the SM is but a low-energy approximation of some more general and aesthetically pleasing theory. Yet despite all e orts no significant deviations from the SM predictions have been found to date.

The way that starts is priceless!

The LHC hasn’t delivered its first collisions yet. ATLAS and CMS haven’t taken collider data yet. But we already have to plan for the next steps. There was a recent kickoff event at CERN for people working on the upgrade to the LHC - the so-called SLHC (Super Large Hadron Collider).

That picture above is a simulation of what the CMS tracker would look like at a luminosity of 10^35 - that is 4 orders of magnitude greater than what we expect to be running at by the middle of 2009. Being able to reconstruct that many particles is going to require both experiments to replace their tracking detectors with more robust and more accurate detectors. This takes years and years to prepare for - the R&D for much of the replacement is already well underway. They are talking about installing these new detectors in 2013 - 5 years from now.

The accelerator talk is also fascinating — but my favorite talk was from MLM who was summarizing some of the physics possibilities of the SLHC:

While there is no guarantee that any deviation from the Standard Model will be found, the existence of physics beyond the Standard Model will demand and fully justify these studies: we’ll be measuring the properties, however trivial, of something which we know exists, as opposed to blindly looking for “we don’t know what” as we are unfortunately doing today!

Worth a look if you are curious about the next step!

Ok, this wasn’t April 1st, rather April 4th. What is worse is CMS saw him first. Darn!

That picture is of the ATLAS detector and Peter Higgs, the fellow whose last name is attached to the Higgs particle - the particle that all of us are after.

See? ATLAS saw him!

Coincidentally an email conversation broke out on a D0 mailing list around the time of this picture discussing the origins of the Higgs mechanism. It was sparked by this yahoo news article. The title is “‘God particle’ expected to be found soon.” Hmmm. Expected to be found? Not sure we are that sure… At any rate.

The email conversation was interesting because because it pointed out that in science often more than one person has the same idea at the same time. Discovery is partly having all the bits in place to build the discovery on. Once all the bits are in place then several people can make the leap.

I’m not familiar with this bit of history, besides Peter Higgs, there was also Robert Brout, Francois Englert, and Tom Kibble in Europe. There are two in America too - Gerald Guralnik and C.R. Hagen. I note that on the Englert page what we normally call the Higgs mechanism is called the Brout-Englert-Higgs mechanism. On the Kibble page it notes that he is credited with the co-discovery of the Higgs with Guralnik and Hagen, the beauty of wikipedia! [they are all basically right, I believe]. Oh — hey — and the UR home page has something up about Hagen as well.

I went to the University of Rochester for my graduate work and my quantum mechanics class was taught by Hagen. At the time I didn’t fully appreciate the work he had done.

A few posts ago I poked fun at the idea that we’d be running 10 TeV Monte Carlo in ATLAS. Not Even Wrong linked to it. So, now I have to eat my words.

We will all be running the Monte Carlo.

Here is the deal. In an experiment like ATLAS we have a huge software base. Think of it like your favorite operating system - Windows, Mac OS, or Linux. Every now and then a new version is created. It is a huge undertaking each time. Lots of source code, lots of updates, lots of new functionality, lots of old things break, etc.

It is the same thing for us in particle physics. The software code to run these experiments, simulate Monte Carlo, reconstruct the data, and analyze the physics is in constant flux. Hopefully improving. Every now and then (say every 6 months or a year or so) all the recent changes are gathered up and released. Once the release is shown to work we let it loose on all of our computer farms with the express task of generating Monte Carlo for us.

This means we regenerate most of our Monte Carlo about once or twice a year. In ATLAS we are working on the version of the code we expect to run when data taking finally arrives (how exciting is that - when data arrives!!). If all goes well in a few months or so it will be in good enough shape to start producing Monte Carlo. And guess what. Whatever the LHC will initially turn on at - that is the energy we will produce the Monte Carlo.

So the whole experiment will be producing Monte Carlo at this energy, not just someone in a back room in secret. Oh well.

ATLAS has just finished one of its large collaboration meeting. One of the nice things about these meetings is we get to hear a fairly detailed report on the machine status - something I don’t always hear except in rumors. In this case it was filling in some of the blanks that were in the recent press release explaining that the start up of the LHC would be at the reduced energy of 10 TeV instead of 14 TeV.

The problem is some of the dipole magnets. They have to be trained to run at full field. Full field for most magnets is 8 Tesla, which is about 133333 times stronger than the earth’s magnetic field. They have to be that strong in order to bend the very high energy 7 TeV beams of protons (magnets are to charged particles like protons what lenses are to light). The power requirements are stupendous (scientific term). In fact, they would probably melt if they were made out of regular copper wire. Instead they make them out a special wire that is superconducting when it is very cold. About -270 degrees Celsius.

The beauty about superconducting wire is that it doesn’t dissipate any energy of the current it is carrying. You know how an overloaded plug socket gets warm? That is because some of the current is converted into heat instead of being used to run your computer - a waste. When dealing with the currents in these magnets - well, it would be so hot that it would melt the magnet.

These magnets have a tendency to quench. Which is a problem. Lets say you have a bundle of wires all at -270 degrees carrying a huge amount of current. Lets say a flaw in one part of one wire causes it suddenly to loose its superconducting property. As a result the current flowing through that bit of wire starts to generate heat. That heat, of course, warms up all the wire around it, which causes it to “go normal” as well. This process rapidly cascades until the whole magnet ceases to be superconducting. This is called a quench. If not handled correctly this can be disastrous - you could melt the whole thing (and these things are expensive!). Part of the magnet design is quench protection.

Now, here is the cool thing. To get to their full field strength you have to train the magnets. This is particularly true when you are pushing the envelope of what the technology can do. You do this by slowly increasing the current in the magnet until it quenches. Once it has, you cool it down again and try again. And repeat.

This process is what will prevent the LHC from being ready to run at 14 TeV this year. The retraining of some magnets is taking too long (all the magnets were trained to full strength before they were installed - so some have become “untrained”). So their plans are to retain these magnets that are not properly trained over the first shutdown in the winter of 2008-2009.

And that, right there, tells us how long we will be running at the reduced energy of 10 TeV. If we are very lucky we will see beam in August and that will be our first run. So, probably a few months. Now, if I’m allowed to put on my old-guy hat, I’m going to guess that we won’t really get collisions until later than that and then the data coming out of our detector won’t make much sense until just around the shutdown. So it could well be this initial 10 TeV run gets almost no useful physics out - but is exactly what we need to get our brand spanking new detector into shape for the first real 14 TeV run.

BTW, I should say that the LHC has not told the experiments at what energy it will actually run yet. People think it will probably be 10 TeV, but the official word has not come from the machine division yet. Next week that should happen.

There were several other things of general note at the meeting (actually, there was a lot, but…). One thing is if you watched Peter Jenni’s talk - he gave out a few links you can go for status info. One has the current cooling status of the accelerator. I don’t think it is meant for everyone to look at, so I won’t post the link. But if you are member of ATLAS you can just look at Peter’s talk on the agenda server. The graphic is cool! I want to make it the background on my computer!

The other thing that, as a member of ATLAS, really makes this time exciting is the detection of cosmic rays. More and more detectors are getting turned on - and the first thing that is done with them is to look for cosmic rays. A few months ago people talked about the first cosmic ray having been seen. Now everyone in ATLAS is showing these things. Maybe this thing will work after all…

There is a joke going around ATLAS right now. There are various people who are obsessed by their physics studies. Each time something new about the detector is found they want to re-run their analysis. Nothing wrong with that - except that if it requires re-simulating the Monte Carlo that can take real resources (minutes per event just to reconstruct the event - we need millions of events in order to do one out of 1000’s of analyses).

Well, a big one was dropped the other day. Actually, we’ve all heard rumors this was coming, but now it is official, so I can joke about it. This is a big one because it changes everything - the production cross sections, average energy will find in our calorimeter, and other things. So, if you want to know how you are going to discover the Higgs at 10 TeV - well, better restart your simulation.

Of course what really matters is how long the accelerator remains at that energy. I don’t know details (perhaps I’ll learn them at ATLAS week next week) but the release claims that the magnets just need some re-training. If that is the case, that is no big deal and we will be at 10 TeV for less time that it will take the detectors to get themselves in shape to take physics-quality data.

At any rate. I’m sure, in some private cluster, somewhere, some 10 TeV data is being simulated as I type this!

A very technical post on the performance of TFractionFitter.

My post the other day about TFractionFitter being written up in a arXiv paper generated a few comments - one in particular that got me a little worried:

Looking at the original Barlow and Beeston paper we found that the approximation breaks down in the case of weighted events. If you want to have some fun, change the initial normalization of the templates that you pass to TFF.

As I mentioned, we used this fit method in some of our current work. For my Friday night entertainment I decided to see if I could test it out a bit.

Constructing a few test cases, and then running them 1000’s of times (ensemble tests) isn’t all that hard (well, see below). Recall TFractionFitter takes several Monte Carlo templates and tries to find components of them in a data histogram. I constructed the templates out of two Gaussians for this test. The data histogram I built was 30% of one of the two Gaussians, and 70% of the other.

In a simple test where I create the data histogram once, with 10,000 entries, and then re-create the template histograms over and over (about 150 times) and perform the fit each time, I found that the fitter got the fractions correct - it correctly identified the 30% and the 70%. Further, as is mentioned in the paper, if I looked at how much it got the fraction incorrect each time, it does indeed look like the errors are underestimated (the exact amount depends on how I arrange the two Gaussians).

To test the weighting as described by Mike, I altered each template’s normalization to be 50% of its initial value, but left the data histogram the same. I got the same result as before. I tried altering the number of entries in one or the other and still the same. So, thankfully, I can’t reproduce this (I was using 5.18 to do this testing).

One thing I discovered — my initial choice of Gaussians had the second Gaussian about 20% off the end of the histogram I was using. The result? TFractionFitter got the answer wrong consistently by about 5%. 5% isn’t that big a deal if you get your errors right — but it didn’t. It was almost always more than one sigma low or high (depending on which fraction you looked at) - a clear bias. The distributions we are using in our work look more like falling exponential - so I’ll have to test that out and see if that shows the same thing. This is another buyer-be-ware comment similar to Mike’s.

I used this weekend project as an excuse to put my money where my mouth is… sort of (meaning I spent time, not money!). I’ve long talked about, on this blog and other places, that if we are to really take advantage of multi-core processors we are going to have to change the way we write code. So for this little project I thought was a perfect excuse to use a new programming language — a functional programming language. I used F#, which is based on ML (OCaml is the current standard implementation of ML). If anyone is interested, I can write some (also technical like this post) posts on what it was like. I used F# instead of OCaml, in part because it has access to all the ROOT libraries due to some other work I’ve done.

An arXiv paper went by the other day that I found interesting for several reasons: “A pitfall in the use of extended likelihood for fitting fractions of pure samples in mixed samples”.

The paper discusses a technique of fitting templates of various sources to data in order to extract constituent fractions. For example, lets say you have a series of particle jets. The jets come from light quarks (up, down, strange), charm quarks, or bottom quarks. You want to know the fraction of each of those types that makes up your series of jets. You are clever - you have a variable that behaves differently for each of the quark types. So, now you can make a template for each jet type in this variable, add them together, vary the fractional size of each template until it fits the variable in your data - and “boom” you have the fractional makeup of your series of jets.

There are a number of tools around that will help you do this so you don’t have to write them yourself. In particular, in ROOT, there is TFractionFitter. This paper calls out an error in TFractionFitter by name. This is the first reason I find this article interesting. This is appearing in a physics paper archive and it specifically targets a tool. It isn’t about physics in particular, but the improper application of a statistical technique. I’m fairly sure (though not 100% positive) that no one has written a paper about TFractionFitter’s operation. Sometimes you’ll see papers written to point out errors in other papers, and then rebuttals. But this is a paper to point out an error in C++ code - ROOT. And, ha, it doesn’t even mention a version number for ROOT - which may be a problem if the error is corrected!

The error is subtle. TFractionFitter will get the fit correct. So the raw numbers that come out will be correct. The probably is when it tries to calculate the errors. Apparently the method it uses to calculate the errors are not valid unless one evaluates things at the central value — which ruins the point because the whole idea of an error is to understand how much things change as you move away from the central value.

Which brings me to the second reason I am interested in this article. A group I am part of in ATLAS is using TFractionFitter! Ops!

Yesterday, at the Moriond QCD conference, Uli Heintz gave the Tevatron Top Mass talk (pdf). New mass results have made the Higgs a little less mysterious. Summer results had a measured top mass of 171.3+-1.7 GeV and now it is 172.8 +- 1.4 GeV. This is good news for the Standard Model.

One of the beauties of the Standard Model is that it holds together so well as a theory. It predicts many different experimental measurements. And all those measurements must be in line with each other — the model cannot accommodate a measurement that is out of whack. And the better we make these measurements the better we can tell when one is out of whack.

The Higgs mass is no different. Even though we’ve not seen it yet, the Standard Model predicts its mass. With the new top mass result, the predicted mass is 87 +36-27 GeV. Using last summer’s top mass the predicted Higgs mass was 76 +33-24 GeV. Note the very large errors on those numbers - there is a lot of slop in that measurement!

This is good for the Standard Model because of work done at the LEP collider. They searched for the Higgs and didn’t see it - they know that the Higgs mass is more than 114 GeV. The summer’s prediction put the Standard Model more out of whack than the current one - the new predicted value of the top mass is more in line with the LEP Higgs search.

Still - I’d love to know where that thing is hiding (along with everyone else)! The latest Higgs results should have been released - but I’ve not seen them publicly posted yet.

N.B. That plot is the summer plot — I couldn’t find the plot with the most recent results - I found it only in Uli’s talk.

A friend  of a friend was investigating the Tunguksa explosion. Mirror matter has been offered up as an explanation. I’ve never heard of mirror matter before (wikipedia has a very quick introduction). The idea, basically, is to restore CP as a fundamental symmetry of our world. And, because the mirror matter would only weakly interact with our world, it might be a good dark matter candidate. There are other predictable effects as well — all having to do with astro observations. And there are even papers in real journals about it (but not many; it never seemed to really catch on the way some theories do).

All good so far. So how come I’ve never heard of it? Do I just live in a hole? Or is it because it is really only testable in an astrophysics experiment and I’ve not paid them enough attention?