Every week I try to take a few hours to study something different. The idea being that this will give me a broader sense of what’s going on within the ATLAS collaboration and the world of particle physics at large. Last week I was mostly watching Gavin Salam’s superb lectures on jets. They’re available as videos from here.

So what is a jet? It’s certainly nothing to do with aeroplanes. Jets are what we observe at ATLAS when a highly energetic quark or a gluon (collectively referred to here as partons) is produced in a collision.

I won’t take the time to explain the physics behind a jet and how they come into being. Those interested can see Flip’s excellent post. In essence, instead of the individual partons, what we see in the detector is a spray of collimated particles. This is what we refer to as a “jet”.

At hadron colliders, such as the LHC, jets are everywhere. In fact the vast majority of interactions at a hadron collider will result in the creation of multiple jets. They are our window on partons and on to the strong force itself.

Being so ubiquitous it’s important that we’re able to reliably identify these within our detector. Unfortunately this isn’t always such an easy task. The event display below illustrates a typical jet event. How many jets do you see?

 

 

Here is ATLAS’s answer.

 

 

In this case the jets have helpfully been colour coded. In real life, this doesn’t happen.

As you can tell the definition of a jet can be somewhat ambiguous. At ATLAS the trigger system has to quickly identify thousands of jets a second in order to pick out the interesting events to record. Identifying such a large number of jets is no easy feat.

To solve this problem we use jet algorithms. These are pieces of software which define jets based on what we see in the detector. They come in all sorts of shapes and sizes, from “simple” versions where a jet is defined as all the particles inside a cone, to more advanced versions which sequentially combine together individual particles based on their separation and energy.

Different algorithms have different strengths and weaknesses. Cone based jets are relatively simple and provide nice, round jets. Unfortunately though, the jets they identify can easily be altered by changes within the jet itself, or by small amounts of energy coming from unrelated collisions. This makes them very hard to compare to the predictions from theory. More complicated algorithms such as the “kT” algorithm remove these ambiguities, but often result in “ugly” irregularly shaped jets.

The current vogue algorithm both at CMS and ATLAS is the so called “anti-kT” algorithm. This starts from the most energetic single particles and sequentially combines them with everything nearby, stopping at some pre-defined distance. This algorithm results in the identification of nice, round jets, and does this consistently regardless of the small amounts of additional energy or the structure of the jets themselves.

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For years the internet has been a wonderful tool for people all over the world, bringing distant communities together, changing the way think about communication and information and having a huge impact for the better in nearly every aspect of our lives. Unfortunately there are still major problems when it comes to sharing scientific knowledge. This is changing very quickly though, making this an exciting time for internet-savvy scientists.

How did this kind of situation arise? Science journals have had their own markup language, LaTeX, for decades, predating the internet by many years. LaTeX is available to anyone makes it very easy to generate simple, attractive documents with excellent support for a wide variety of mathematical symbols. (Making complicated documents isn’t quite so easy, but still possible!) Making documents like this can be very intensive, as every margin and the space between every character is analyzed, with restrictions imposed by paper sizes.

On the other hand, the hypertext markup language (HTML) and cascading style sheets (CSS) are the standards which are widely used on the internet, and they are focused mainly on the aesthetics of more popular kinds of journalism. The HTML standards are intended to work on any operating system, and they should give a semantic description of the content of a webpage, without consideration for style. The CSS then take over and decide how the information is displayed on the screen. (Check out the CSS Zen Garden to see the power of CSS.) In principle, writing a webpage that follows the HTML and CSS standards is quite easy, but in reality it’s it can be a very problematic and tedious task. The internet is a dynamic medium, with different developers trying different tricks, different browsers supporting different features and no real control concerning the best practices. Groups such as W3C have tried to standardize HTML and CSS, with quite a lot of success, but it’s a slow process and it has taken years to get to where we are today.

Trying to get mathematical markup with these kinds of constraints is quite tricky! Math is inherently two dimensional, making good use of subscripts, superscripts, indices, fraction, square roots… HTML is much better at handling long passages of text which flow from one line to the next, without much scope for anything as exciting as a nested superscript. And so for a long time it became very awkward to include math on a webpage.

Over the years there have been many approaches to this problem, including LaTeX2HTML, MathML, using images, or expecting the poor user to interpret LaTeX markup! Eventually, the CSS standards settled down, browsers started to conform to the same behavior, and it became possible to display math without the use of any images, plugins or other suboptimal solutions.

With the exciting developments of Web 2.0, we have access to MathJAX. We can take LaTeX markup and put it directly into a webpage and MathJAX can turn this:

\[
  \nabla \times \vec{H} & = & \vec{J} + \frac{\partial \vec{D}}{\partial t}
\]

into this:

\[
\nabla \times \vec{H} = \vec{J} + \frac{\partial \vec{D}}{\partial t}
\]

Beautiful! It also works inline like this: \(E=mc^2\) becomes \(E=mc^2\). (None of this will work if JavaScript is disabled on your browser, which is a shame for you, because it looks very pretty on the page!) Using MathJAX is as simple as writing normal LaTeX between \[ and \] symbols for block-level text, \( and \) symbols for inline text.

We finally have a way to show equations on any browser, with any operating system, that complies with all the standards laid out by the W3C. So much for math markup. What about technical drawings and graphs? Scientists have been using vector graphics in their work for decades, so it would also be nice to have a way to show these kinds of images.

Some browsers have supported vector graphics for a few years, but once again, different browsers behave differently, and vector graphics have been developed rather late, so there are large performance issues. However, with the development of the next generation of HTML browsers should support a brand new kind of image, the HMTL5 canvas. It allows designers of websites to draw detailed images on the fly, even allowing the user to interact with the images! It will take some time before most of the users on the internet can have access to the HTML5 canvas, so until then we can’t rely on these new features to share information.

On the other hand it means that we living in a very exciting time where anyone can develop their own work using the canvas, and help shape our experiences with the internet in the future! The standards used online have always lagged behind how the latest developers are using the tools at their disposal, and when the standards get updated the ingenuity of the developers is taken into account. Soon the canvas will support 3D graphics, making our online experiences even richer! Want to help shape how this is developed? Then get involved! Try out the canvas today and see what you can create! There are dozens of fascinating examples at Canvas Demos. Here are some of my favorites:

• MolGrabber 3D- a great way to visualize molecules in three dimensions.
• Flot- how to show graphs on a webpage.
• Pacman- a clone of the classic arcade game!

The internet is going to get very cool in the near future, giving us the ability to share information like never before! When anyone can create animations and simulations, blogs like this will become even more interactive, even more compelling and even more useful. I can’t wait to see what MathJAX and the HTML5 canvas will deliver!

We’ve mentioned jets a few times here on the US LHC blog, so I’d like to go into bit more detail about these funny unavoidable objects in hadron colliders. Fortunately, Cornell recently had a visit from David Krohn, a Simons Fellow at Harvard University who is an expert at jet substructure. With his blessing, I’d like to recap parts of his talk to highlight a few jet basics an mention some of the cutting edge work being done in the field.

Hadronic Junk

Let’s review what we know about quantum chromodynamics (QCD). Protons and neutrons are composite objects built out of quarks which are bound together by gluons. Like electrons and photons in quantum electrodynamics (QED), quarks and gluons are assumed to be “fundamental” particles. Unlike electrons and photons, however, we do not observe individual quarks or gluons in isolation. You can pull an electron off of a Hydrogen atom without much ado, but you cannot pull a quark out of a proton without shattering the proton into a bunch of other very different looking things (things like pions).

The reason is that QCD is very nonperturbative at low energies. QCD hates to have color-charged particles floating around, it wants them to immediately bind into color-neutral composite objects, even if that means producing new particles out of the quantum vacuum to make everything neutral. These color-neutral composite objects are called hadrons. Unfortunately, usually the process of hadronizing a quark involves radiating off other quarks of gluons which themselves hadronize. This process continues until you end up with a messy spray of particles in place of the original colored object. This spray is called a jet. (Every time I write about jets I feel like I have to reference West Side Story.)

 

As one can see in the image above, the problem is that the nice Feynman diagrams that we know how to calculate do not directly correspond to the actual mess of particles that form the jets which the LHC experiments measure. And it really is mess. One cannot effectively measure every single particle within each jet and even if one could, it is impractically difficult to calculate Feynman diagrams for very large numbers of particles.

Thus we’re stuck having to work with the jets themselves. High energy jets usually correspond to the production of a single high-energy colored particle, so it makes sense to talk about jets as “single objects” even though they’re really a spray of hadrons.

Identifying Jets

So we’ve accepted the following fact of life for QCD at a particle collider:

Even though our high energy collisions produce ‘fundamental’ particles like quarks and gluons, the only thing we get to observe are jets: messy sprays of hadrons.

Thus one very important task is trying to make the correspondence between the ‘fundamental’ particles in our Feynman diagrams and the hadronic slop that we actually measure. In fact, it’s already very hard to provide a technical definition of a jet. Our detectors can identify most of the “hadronic slop,” but how do we go from this to a measurement of some number of jets?

This process is called clustering and involves developing algorithms to divide hadrons into groups which are each likely to have come from a single high energy colored particle (quarks or gluons). For example, for the simple picture above, one could develop a set of rules that cluster hadrons together by drawing narrow cones around the most energetic directions and defining everything within the cone to be part of the jet:

One can then measure the energy contained within the cone and say that this must equal the energy of the initial particle which produced the jets, and hence we learn something about fundamental object. I’ll note that this kind of “cone algorithms” for jet clustering can be a little crude and there are more sophisticated techniques on the market (“sequential recombination”).

Boosted Jets

Even though the above cartoon was very nice, you can imagine how things can become complicated. For example, what if the two cones started to approach each other? How would you know if there was one big jet or two narrow jets right next to each other? In fact, this is precisely what happens when you have a highly boosted object decaying into jets.

By “boosted” I mean that the decaying particle has a lot of kinetic energy. This means that even though the particle decays into two colored objects—i.e. two jets—the jets don’t have much time to separate from one another before hitting the detector. Thus instead of two well-separated jets as we saw in the example above, we end up with two jets that overlap:

Now things become very tricky. Here’s a concrete example. At the LHC we expect to produce a lot of top/anti-top pairs (t–t-bar). Each of these tops immediately decays into a b-quark and a W. Thus we have

t, t-bar → b, b-bar, W W

(As an exercise, you can draw a Feynman diagram for top pair production and the subsequent decay.) These Ws are also fairly massive particles and can each decay into either a charged lepton and a neutrino, or a pair of quarks. Leptons are not colored objects and so they do not form jets; thus the charged lepton (typically a muon) is a very nice signal. One promising channel to look for top pair production, then, is the case where one of the Ws decays into a lepton and neutrino and the other decays into two quarks:

t, t-bar → b, b-bar, W W → b, b-bar, q, q-bar, lepton, ν

The neutrino is not detected, and all of the quarks (including the bottoms) turn into jets. We thus can search for top pair production by counting the number of four jet events with a high energy lepton. For this discussion we won’t worry about background events, but suffice it to say that one of the reasons why we require a lepton is to help discriminate against background.

Here’s what such an event might look like:

Here “pT” refers to the energy (momentum perpendicular to the beam) of the top quarks. In the above event the tops have a modest kinetic energy. On the other hand, it might be the case that the tops are highly boosted—for example, they might have come from the decay of a very heavy particle which thus gives them a lot of kinetic energy. In the following simulated event display, the tops have a pT that is ten times larger than the previous event:

Now things are tricky! Instead of four clean jets, it looks like two slightly fat jets. Even though this simulated event actually had the “b, b-bar, q, q-bar, lepton, ν” signal we were looking for, we probably wouldn’t have counted this event because the jets are collimated.

There are other ways that jets tend to be miscounted. For example, if a jet (or anything really) is pointed in the direction of the beam, then it is not detected. This is why it’s something of an art to identify the kinds of signals that one should look for at a hadron collider. One will often find searches where the event selection criteria requires “at least” some number of jets (rather than a fixed number) with some restriction on the minimum jet energy.

Jet substructure

One thing you might say is that even though the boosted top pair seemed to only produce two jets, shouldn’t there be some relic that they’re actually two small jets rather than one big jet? There has been a lot of recent progress in this field.

The main point is that one can hope to use the “internal radiation distribution” to determine whether a “spray of hadrons” contains a single jet or more than one jets. As you can see from the plots above, this is an art that is similar to reading tea leaves. (… and I only say that with the slightest hint of sarcasm!)

[For experts: the reason why the QCD jets look so different are the Alterelli-Parisi splitting functions: quarks and gluons really want to emit soft, collinear stuff.]

There’s now a bit of an industry for developing ways to quantify the likelihood that a jet is really a jet (rather than two jets). This process is called jet substructure. Typically one defines an algorithm that takes detector data and spits out a number called a jet shape variable that tells you something about the internal distribution of hadrons within the jet. The hope is that some of these variables will be reliable and efficient enough to help us squeeze as much useful information as we can out of each of our events. There also seems to be a rule in physics that the longer you let theorists play with an idea, the more likely it is that they’ll give it a silly name. One recent example is the “N-subjettiness” variable.

Jet superstructure

In addition to substructure, there has also been recent progress in the field of jet superstructure, where one looks at correlations between two or more jets. The basic idea boils down to something very intuitive. We know that the Hydrogen atom is composed of a proton and an electron. As a whole, the Hydrogen atom is electrically neutral so it doesn’t emit an electric field. (Of course, this isn’t quite true; there is a dipole field which comes from the fact that the atom is actually composed of smaller things which are charged.) The point, however, is that far away from the atom, it looks like a neutral object so we wouldn’t expect it to emit an electric field.

We can say the same thing about color-charged particles. We already know that quarks and gluons want to recombine into color-neutral objects. Before this happens, however, we have high energy collisions with quarks flying all over the place trying to figure out how to become color neutral. Focusing on this time scale, we can imagine that certain intermediate configurations of quarks might already be color neutral and hence would be less likely to emit gluons (since gluons are the color-field). On the other hand, other intermediate configurations might be color-charged, and so would be more likely to emit gluons. This ends up changing the distribution of jet slop.

Here’s a nice example from one of the first papers in this line of work. Consider the production of a Higgs boson through “quark fusion,” i.e. a quark and an antiquark combining into a Higgs boson. We already started to discuss the Higgs in a recent post, where we made two important points: (1) once we produce a Higgs, it is important to figure out how it decays, and (2) once we identify a decay channel, we also have to account for the background (non-Higgs events that contribute to that signal).

One nice decay channel for the Higgs is b b-bar. The reason is that bottom quark jets have a distinct signature—you can often see that the b quark traveled a small distance in the detector before it started showering into more quarks and gluons. Thus the signal we’re looking for is two b-jets. There’s a background for this: instead of qq-bar → Higgs → b-jets, you could also have qq-bar → gluon → b-jets.

The gluon-mediated background is typically very large, so we would like to find a clever way to remove these background events from our data. It turns out that jet superstructure may be able to help out. The difference between the Higgs → b-jets decay versus the gluon → b-jets decay is that the gluon is color-charged. Thus when the gluon decays, the two b-quarks are also color-charged. On the other hand, the Higgs is color-neutral, so that the two b-quarks are also color neutral.

One can draw this heuristically as “color lines” which represent which quarks have the same color charge. In the image below, the first diagram represents the case where an intermediate Higgs is produced, while the second diagram represents an intermediate gluon.

For the intermediate Higgs, the two b-jets must have the same color (one is red, the other is anti-red) so that the combined object is color neutral. For the intermediate gluon, the color lines of the two b-jets are tied up to the remnants of the protons (the thick lines at the top and bottom). The result is that the hadronic spray that makes up the jets tend to be pulled together for the Higgs decays, while pushed apart for the gluon decays. This is shown heuristically below, where again we should understand the plot as being a cylindrical cross section of the detector:

One can thus define a jet superstructure variable (called ‘pull‘) to quantify how much two jets are pulled together or pushed apart. The hope is that this variable can be used to discriminate between signal and background and give us better statistics for our searches for new particles.

Anyway, that’s just a sample of the types of neat things that people have been working on to improve the amount of information we can get out of each event at hadron colliders like the LHC. I’d like to thank David Krohn, once again, for a great talk and very fun discussions. For experts, let me make one more plug for his workshop next month: Boost 2011.

 

My first note’s byline is UC Davis:

Good evening from California!

Well, it’s evening here (10:30 pm), but it’s already tomorrow on the east coast of the U.S., and in fact already time to wake up at CERN.  Here is where I usually face my conundrum: Do I stay awake and watch for the first email reports on the activities at the LHC?  Should I wait for our postdocs and students who live at CERN to respond to my emails?  If I go to sleep, what will I miss?

Unfortunately, I have an 8:00 am video meeting tomorrow, in which our postdocs on the CDF experiment at Fermilab are presenting an introduction to our new analysis, searching for signs of light dark matter in the CDF data.  (CDF has been in the news recently for an interesting result that has previously been discussed by Flip Tanedo and Michael Schmitt.)

The CDF meeting is followed by a 9:30 am video meeting with fellow CMS colleagues who are working on searches for fourth generation quarks, and it looks like one of our CMS postdocs may have something short to present there.  But this isn’t so bad: on Fridays my first meeting is at 6:30 am, which is 3:30 pm in Geneva, and many meetings are earlier than that, so I usually have to miss them. I am grateful that at least for tomorrow’s CMS meeting at 9:30, those at CERN are willing to have it at 6:30 pm, their time, which for me means I can at least get the kid to daycare and get to work formally before it begins.

Of course, even after these early meetings, the California workday still lies ahead for me, and it sometimes turns in to a very long day.  But the time is worth it— as you have gathered in these blogs, there are lots of exciting things going on in the world of particle physics these days, and I wouldn’t want to miss it!

With that, I’d better say “good night” (*yawn*) and get some sleep… the sun is fast approaching.

 

 

Hi All,

Perhaps you’ve heard of the Standard Model of Particle Physics. (If you’ve been following Flip’s ongoing series, you’ve certainly heard a lot.) In a nutshell, the Standard Model is a theory describing the fundamental particles of matter and the forces that mediate their interactions, and it’s the theoretical framework in which we at CERN generally understand our experimental data. In the three decades since its formulation, the Standard Model has been extraordinarily successful and accurate in its predictions, and with the notable exception of the SM Higgs boson, all of the pieces to this particle puzzle are already in place.

The Standard Model is so boring.

However, for a variety of reasons that I’ll keep outside the purview of this post, we believe that there’s physics “beyond” the Standard Model. As with most things in high-energy physics (HEP), this has been given a practical acronym: BSM (Beyond the Standard Model) physics. Many BSM theories predict the existence of one or more new (non-SM) particles. Here’s a scandalously abridged list:

• Supersymmetry (SUSY) predicts “superpartners” or “sparticles” corresponding to every current SM particle
• in addition to the three generations of matter particles already observed, there could be a fourth, more massive generation consisting of two quarks and two leptons
• because the SM Higgs just isn’t enough! Little Higgs, Fat Higgs, Composite Higgs, Hidden Higgs …
• W’ and Z’
• Leptoquarks

Theorists are very creative! This list could go on for quite a while…

Given that I’m an experimentalist, however, I’m more directly interested in how one goes about detecting these hypothetical particles. And as an entirely practical matter, the first thing you have to do is actually choose which of these particles you’ll be searching for. This isn’t as simple as it sounds! Here are some general issues to take into consideration when making your decision:

• How much data is needed for a discovery? Or, alternatively, How large is the production cross-section? If your particle has a large production cross-section, it will be produced in copious amounts by the LHC, and therefore less data is required for you to find it. Since the LHC is still relatively young, and the number of collisions recorded by the experiments is only a tiny fraction of the expected total, many analyses — BSM searches especially! — are limited by statistics. We hope to have about 1 fb-1 of data by the end of this year. If you expect to be sensitive to your particle only with 100 fb-1, then you will be waiting an awfully long time…
• Is the particle model-independent? It pays to be general. If your particle is entirely dependent on the viability of a particular BSM model, and that model is subsequently ruled out by experimental data, then where does that leave you? Back at the beginning, looking for a new particle to discover. Furthermore, the more general the particle, the less fine-tuned your analysis will be. Many BSM particles resemble each other, at least in a general sense, so you can imagine a situation where you’re so focused on finding one specific particle that you don’t notice another one lurking in the data.
• Are other people already looking for your particle? Collaboration is essential in a field like ours, but do make sure that there’s room for you on this search before you barge in. Perhaps the other analysts are very territorial. Maybe there are simply too many of them already. Or could it be that you don’t want to share the Nobel Prize when you discover your new particle…? Ask around ahead of time, even email the folks in charge (“conveners”) to find out who is working on what. Given the aforementioned creativity of theorists, there’s sure to be particles still in need of analysts!
• Is it available at The Particle Zoo? Just sayin.

In truth, these are only a few of the many considerations that go into choosing a new particle to search for. From pure theory to pure politics, this decision is not one to be taken lightly! Think carefully before setting your heart on (and devoting many months of work to) your new particle — then go for it.

– Burton

Things aren’t going as quickly as I hoped they would when I wrote my last post on my thesis. I’ve had to choose between actually filing my thesis this semester and getting my results complete and published as quickly as possible — and my collaborators on ATLAS will be pleased to hear I’ve chosen the latter. It feels like robbing Peter to pay Paul, but I have to prioritize somehow. The problem, in the end, was just that writing the introductory chapters of my thesis was more work than I imagined; or maybe it was really that I knew I could use the summer as spare time, so I couldn’t force myself to work hard enough. In any case, I do have the summer, so things will be fine. My results are starting to move through ATLAS, and hopefully the remaining work will mostly be cosmetic. Once that’s definitely in good shape I’ll be able to focus on my thesis and file it in the first month or two of the summer.

In the meantime, I’m cutting back on other things I enjoy working on but don’t have time for. That means no more regular volunteering for the Prison University Project, where I’ve been teaching basic math to prison inmates for most of the time I’ve been in grad school. It also means, a bit more slowly, handing off my organizational responsibilities for the math class there, which have been great practice for academic politics. Finally, it means giving up on blogging for a while; I won’t be able to write more about finishing my thesis, or the transition to my new job — at least not until it’s started and I know if I have time!

So you won’t see me here for several months at the very least. In the meantime, you can see my occasional professional opinions and random comments about coffee on my Twitter feed, @sethzenz. I hope to be back as soon as I can, but in any case, thanks for reading!