It’s that time of year again: hard-working college seniors all over the world are getting e-mails from American universities offering them positions as PhD students in, among many other fields, physics. [Other countries have slightly different time-scales and procedures for PhD applications.] To all of you who have gotten these letters: congratulations!

Image from PhD Comics, (c) Jorge Cham.

Now comes the hard part: you have to commit to a PhD program which will frame your education and research for the next 4 to 6(-ish) years. If you’ve gotten this far, then you already mastered the ‘rules of the game’ for your undergrad years: work hard, do well in courses, and start doing some research. Here’s the hitch:

Picking a grad school is the first of many decisions before you where there is no clear path and no obvious set of rules.

Welcome to grad school!

Since this can be a bit of an overwhelming decision, I’d like to offer my thoughts on this matter with the caveat that they are based on my own personal experience in theoretical particle physics and may not apply to everyone. (I’ll do my best to be as general and objective as possible.) Most of my thoughts on this matter are collected in some detail an old post on an old blog, but I’d like to provide an updated and shorter presentation here.

How not to pick grad schools

The first thing you should know: grad school is not one-size fits all. There’s no clear hierarchy of programs. Your mother might want you to go to a big-name Ivy League university, but that is irrelevant unless that university has a strong program in your field. You have no obligation to go to a program just because the university is ‘more prestigious.’ You are judging particular programs (maybe even a particular advisers) and what matters most is finding a place where you can do good research and set yourself up for the next stage of your career. So unless your mother is a professor in your field, do not listen to what she says. (Unless it is ‘I love you’ and ‘I’m proud of you.’)

Similarly, let’s settle this right now: it does not matter what the climate is like or how big the city around the university is. Your job is to find a place where you can do exceptional science and if that means that for a few years you have to live outside your comfort zone, then so be it. (Besides, as a senior in college I’m not convinced that people even know what their ‘comfort zone’ is. You might be surprised.)

Gather the right information

Rule number two: visit each school and talk to as many people as you can. (They won’t mind too much if you skip all of the tours to talk to people in your field.) Most importantly, speak directly to any potential advisers. There are a few important questions that you should always ask faculty and their current grad students:

1. How are students paired with faculty? What is the likelihood that you will be able to work with the faculty that you want?
2. How often does each professor talk to his/her graduate students? Do the grad students play central roles in the group, or do they follow their faculty?
3. What kind of funding does the group offer? How much will you have to teach, how many semesters will the group support you without having to teach? (This is especially important in theoretical physics.)
4. How have the professor’s past students done? Have they found good postdocs and gone on to faculty jobs?
5. What are they working on? Note: you should already have a good idea about this based on databases like SPIRES (for particle physicists).

Question #1 is especially important in theoretical particle physics where groups tend to be smaller. Having verbal assurance that an adviser will take you goes a very long way. I’ve seen too many students chose a grad program where they thought they could work with Prof. Y but then ended up having to find a back-up plan because that professor didn’t take any students that year.

Find the right fit: it’s all about you

Rule number three: figure out what kind of students benefit the most from each program, and decide if you match the profile. Some schools do an excellent job with preparatory coursework, but this would be very frustrating for students who already have a strong course background. On the other side of the spectrum, some schools expect students to be very independent from the very beginning, which may frustrate students who could use more mentoring early on.

Here’s what’s difficult: suppose you are choosing between two universities, X and Y, which have strong departments in your field. You think that X would provide the support you need, but Y is more prestigious and tends to do well placing its graduate students. You worry that going to X will reduce your chances of getting a good postdoc.

It won’t. Trust me. I’ve seen too many good students who have become frustrated at top-name schools because the program wasn’t the right fit for them, and I’ve seen just as many excellent students who have done exceptionally well after going to a lesser-known school with a program that was just right for them.

Evaluating advisers

How do you know which adviser is right for you? This is also a very personal choice.

• Do you need someone with a more hands-on approach, or someone who can ‘point you in the right direction’ and let you explore? [If you haven't done research before, then you probably want someone hands-on.]
• Is the professor working on something you are interested in? (You should already have a good idea of what you are interested in!)
• How have their past students done? How are they as an adviser? A Nobel laureate might be great for a letter of recommendation, but that doesn’t help if s/he isn’t there to help you develop into a good scientist as well.

You might want to think about how active an adviser is (this is correlated with age), whether there are external factors (faculty with young children have less time), and what kind of relationship you want with your adviser (research only, or chummy buddies). If you’re not sure how to evaluate potential advisers as scientists, the best people to ask are the faculty at your current university.

Let me emphasize once again: a personal assurance that you can work with a particular faculty member goes a long way. You do not want to end up at a university where none of the faculty have room for another student in your field.

More advice is good advice

Anyway, hopefully these paragraphs can help get the ball rolling. Probably the best advice I can give is to solicit advice from as many relevant sources as possible (especially faculty at your university) and figure out which is most relevant for you.

-Flip for US/LHC blogs.

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Hi sports fans!

Of course, being an American here at CERN, we have to find some way to keep up with American sports! Tonight was the US vs. Canada Olympic Hockey final, and I went to the nearest pub to take in the action. That was an incredible game, for anyone who missed it, and we watched in a crowd of Canadians and Americans (with a Swede and a few others in the mix):

A crowd of Canadians and Americans focused on a great hockey match

It seems there are British Pubs no matter where in the world one goes. So we headed down to our regular pub in Geneva to enjoy the game. The last few weeks we’ve had to compete for viewing space with the Carling Cup and a few Champions’ League matches (that’s European football for the baffled Americans…), but we’ve been able to find enough space. And watching the US beat the Swiss team twice in 10 days was quite a treat! In fact, one of the best Swiss teams is the Geneva-Servette Hockey Club, and they (and the league, I assume) took three weeks off to let some of their players head for the Games (Servette is the neighborhood of Geneva just west of the main train station, where I happen to live).

Next week baseball’s spring training games will start, which can be even harder to find on the television over here. I’m lucky that the Cubs have a long history of playing many day games, which are night games over here (the Superbowl started at 2am over here…). But we find a way to watch when the big games come around – frequently via internet, or even via videochat with a friend who’s willing to point there computer at the television!

During the summer, I play on one of the CERN softball teams, called the “Quarks,” in the Geneva Softball League. It serves as a little trip back to American every Sunday. The games are hosted, very kindly, at the US Marine Corps House just north of Geneva, and the league includes a team of Marines (jocks vs nerds anyone?), a team of Cubans (Buena Vista Softball Club), and two CERN teams (the Quarks and the Leptons). Our team is usually about half homesick Americans wanting to swing a bat, and half Europeans wondering why the bat isn’t flat and there are four bases instead of two. But we have a lot of fun, and we even occasionally win a game.

The 2009 Quarks Softball Team!

But I’m a Cubs fan, so I know it’s not all about winning….

–Zach

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It’s Like Work

Several bloggers have talked about the LHC Computing Grid already. We use a lot of computing resources as physicists. The WLCG homepage actually has some nice information about the Grid, including cool pictures of what’s online now:

There’s a wonderful thing that comes along with using all these computing resources. Frequently, I’ll set up some task and set it off to run on a few hundred computers somewhere. It feels like I’m working hard – even if the computers are doing all of the heavy lifting!! It also lets you justify a long coffee break: “I’m working right now! The Grid is whirring away because of me!!”

I’ve spent a lot of my time working on improving the ATLAS software (usually trying to make it faster). Most computers these days use around 80 Watts of electricity – about as much as a bright light bulb (or one of those lightbulbs you might find in a dimming lamp). That means, if we leave them on and running year-round, we spend about $100 for the electricity for each computer we have. The Grids that ATLAS uses (there are three, actually) have about 30,000 computers on them, which means that we spend about $3M a year for the electricity to run the computers on the Grid.

Of course, you have to cool all those machines, and most of the buildings that they live in are not the most elegant, modern, energy-efficient buildings that you might construct today. So you can guess that we spend about the same amount on air conditioning – another $3M (that is actually pretty close to right, based on CERN’s experience).

Recently, ATLAS changed the operating system that we run our applications on – like an upgrade from Windows XP to Vista, or Mac OS X 10.5 (Leopard) to 10.6 (Snow Leopard). The operating system we use is called “Scientific Linux,” and we moved from Scientific Linux 4 to Scientific Linux 5. Because of a few of the fancy new tricks that came along with that change, our software suddenly runs 20% faster.

So an operating system upgrade just saved us $1.2M a year!!

Actually, that’s not quite true. The electricity for computers on the Grid is pretty cheap compared to some of the other parts of the budget. So rather than turning off the computers, we run them more, and we can process more data in the same amount of time. Still, it’s a nice thought! And little calculations like this make me think they should give me a bonus when ever I make our software a little bit faster…

Richard asked about LHC@home after my last post. You can read all about it at their website. That’s a neat project, and we’ve talked about different ways to use it to our advantage. There are a few problems, though, that are perhaps interesting to mention (note: I’m a mere blogger – this is just one fellow’s opinion).

LHC@Home Screensaver

One problem is that the software we use is pretty big. A typical installation is around 7 GB, and runs natively on linux machines. On top of that, the data files are typically a few more GB. There aren’t a whole lot of people who are willing to blow 15GB of their hard drive space on a nice screen saver, so we have to think carefully about whether there is a slimmed down version that we can send out and run on Windows or Apple computers (to reach a broader audience).

Another problem is that our data is still “sensitive.” In order to make full use of our friends’ computers, we would want to give them full access to our data. But we want to be the first to publish results with that data! So it is a bit nervous-making to just send the data to whoever asks for it. More likely, there would be someone out there who would try to use the data, but wouldn’t really understand it, and so would end up misidentifying something interesting. Then we’d have to spend our time trying to fix the things they’d done wrong. There was an interesting discussion about that at a conference I attended a few years ago. Someone asked that all LHC data be made publicly available. Of course, we raised this objection then (that they wouldn’t understand what we were giving them). And then a person asked a very nice question: “The data from the previous experiment at CERN (called LEP) is publicly available. Has anyone looked at it?” No one outside the experiments had. So one more reason to not try to make our data public.

One more problem is dealing with “conditions.” What we get out of the detector depends on the state that the detector is in at the time – which pieces are on or off, what temperature those pieces are, what voltage is being used, and so on. All that information (called “conditions”) is put in a big database at CERN. When ever we want to use the data, we have to read some of that information, and so we have to access the database. If more than a few thousand people tried to connect at the same point, it would bring down the database, and no one would be able to use it! We have duplicates set up around the world now to ease that problem. On top of that, we now have caching servers set up near those. When you ask one of those servers for information, it checks whether it has it around, and only if it doesn’t will it go back to the original database. That way we make the most frequently used conditions available all over. But I am not sure that we have the infrastructure to allow that many new people to request conditions information! And it would be risky to launch a program that might bring our work to a halt, just as the LHC is getting up and running!!

Of course, Moore’s Law continues to hold, and computers continue to get cheaper. So by 2020 this might all be easy, and everyone might be running our software as a screen saver. But for now, it’s quite a challenge!

–Zach

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With the winter shutdown rapidly coming to a close, the ATLAS team has been preparing for the eventual flood of data. I’m sure you remember all those posts the bloggers have made about having lots of meetings, well the number of meetings is exponentially dependent on the expectation of data. Despite my love of meetings, here’s lots to do, so meetings are inevitable. I’ve been trying to get all my early analyses in order because things will happen very quickly. Of course things never go as smoothly as one would hope. The past few weeks I’ve been madly searching for converted photons (in simulated data, of course). Photons, either created during the primary interaction or during other processes, convert in the detector as they pass through material into electron/positron pairs. These are useful in mapping the material in the detector because more conversions occur near more material. They are also useful in calibrating the detector because we can measure how much energy they deposit.
Thankfully I found the little buggers, (I needed to do a photon recovery – which I hadn’t needed to do previously) so the analysis marches on. I’m specifically looking at doing a calibration study – E/p of the converted photons. This is a measurement of the energy deposition (E) in the calorimeter and compare it to the momentum measurement ( p ) from the tracking system. The ratio (for a massless particle of course) should be 1. (Electrons are pretty light compared to the momentum that they have so we can approximate it as zero for now). But this ratio also depends on how well we can determine the momentum of the charged particle in the tracker and how well we measure the energy deposition in the calorimeter.
Charged particles enter the tracking detectors and are bent in the magnetic field. The curvature of the bend is proportional to how fast the particle is going (its momentum) – slow particles have their trajectory affected more than faster particles. Then given the curvature we can calculate the momentum. These particles then enter the calorimeter where they deposit their energy. How quickly they do this depends on the radiation length of the material of the detector and – again – the energy of the entering particle. We can then compare the two values to see how closely the detectors are calibrated to each other.
We have lots of particles that we use to do this kind of calibration. I’m using photons is because we should see a lot of them at the beginning (high cross section). For other particles we’ll have wait a bit. Also we’ll want to be able to calibrate at all different energies to see how the calorimeter and tracking responds. Photons just so happen to get to really high energies (higher than Zs and Ws) and that’s where the exciting physics is going to be.

-Regina

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Hi there blog enthusiasts!

I thought it would be appropriate to write my first post sitting here in the ATLAS control room. I’m manning the very same desk that Seth blogged about over a year ago as we prep ATLAS for the restart of the LHC in the next week or so. It’s late Saturday night (Sunday morning? Which one is it at 4am?), and so it seems like a good time for an existential crisis.

How did I get here?

I was always a math and science kid. One of my friends read The Physics of Star Trek in 6th or 7th grade, explained it to me, and eventually loaned me his copy. That was enough for me. I was ready to find E.T. My parents are both English professors, and they had no idea where they went wrong. My Mom was a product of New Math, and my Dad gave up on physics as soon as electricity and magnetism came around (“Field Lines???”).

I had two great physics teachers in High School (for the real physics nerds: I went to the same High School as Michael Peskin and Jack Steinberger). Those two convinced me that physics was as interesting as I hoped and that it was something I could actually do for a living. One bit of advice that I took to heart: “Take math until you really don’t understand it any more. Then stop.”

At the end of High School, I decided to go to Berkeley (Go Bears!!) and major in math and physics. My first physics professor was a young Russian, one of the smartest and hardest working guys I’ve ever met. I spent the rest of college working for him on an experiment at SLAC. I had a great time in the physics department there, and settled on the idea of graduate school around my Sophomore year. The only questions were where, and doing what.

Until my Junior year, I thought I might be a theorist (much like Flip). Then two things happened in one year: I stopped understanding math, and I took a full-year lab course that was some of the most fun I’d had at Cal. The course was repeating famous physics experiments: working on a C02 laser, measuring Rutherford Scattering, measuring the flux of cosmic rays, making Joshephson junctions… I loved every minute of it. And there were a lot of minutes to love!

So I tried to see what the experimental physicists I respected most were doing. Many of them were heading towards the LHC (I also thought about IceCube, but the thought of spending a few winters at the south pole was hard to stomach). I applied to graduate school knowing I wanted to work on the LHC, and even knowing which professors I wanted to work for. Physics professors pick their projects, so heading to Caltech was the last major decision I’ve made on my own. Since then, I’ve worked on the ATLAS simulation software (full details to come) and pixel detector, and I’m heading back into the world of “jets” (like these, but using the calorimeter).

And now, here I am in the control room on a Saturday night. It does make one wonder. Either I really love what I’m doing, or I have made some horrible choices along the way. But since these shifts are all volunteer work, the choice is obvious, right?!?

Even though none of the green lights have turned red yet, I’ll stop here for the time being. More about science, and less about me, soon!

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This weekend our department had a Physics Fair, free to the public, where hundreds of parents and kids came and learned about the research we’re involved in. There were grad students and professors available from many research groups including plasma, condensed matter, astrophysics, particle physics, and more.

Hey that's my experiment!

I enjoyed interacting with the public and letting them know people from their community are involved in a project they’ve actually heard about in the news. Of course, many people who had heard of a “hadron collider”, heard about it because of “black hole” fear stories.  Not that anyone was really afraid, it’s just that newspapers liked to make eye-catching, sensational headlines (like shown here).

If that’s what it takes to get on the cover of some newspapers, I’ll take it.  It’s a starting point, and at least gets people talking.

We had a few things for kids to look at, including a cloud chamber to see particles from cosmic rays.

Another thing we had for kids was a “quark puzzle”, which was an improved design from previous fairs.  See it here:

Quark Puzzle! (click to see larger image)

With this, kids could put together up and down quarks in whatever combinations of 3 they wished to create ether a delta-minus, neutron, proton, or delta-plus-plus.  Then they pasted them together using a “gluon” glue stick.  The quarks fit together in such a way that they can only make a circle with quarks of all three colors: red, green, and blue.

I know, I know, it’s way low budget, but a surprising number of kids enjoyed pasting quarks together.  Some kids made pasted together a bunch of quarks and were really excited to be bringing home so many particles.

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I came back from Washington D.C. a couple of days ago.  I was attending the APS “April” Meeting (yes it took place on February), which was held at the Marriot Wardman Park hotel.  It was fun, and I got to give a quick presentation about the analysis that I was working on earlier last year, in preparation for physics analysis at CMS. It was based on simulation and was about exploring electroweak symmetry breaking (EWSB) scenarios beyond the Standard Model. In particular, “Higgsless” scenarios like Technicolor models or the Minimal Higgsless Model.

It was scheduled that professor Peter Higgs (one of the proponents of the Standard Model EWSB mechanism) would recieve the prestigious Sakurai Prize for theoretical physics along with many other great theorists that were involved in developing such formalism.  I was really looking forward to see professor Higgs giving one of the acceptance talks, but unfortunately he did not make it to the APS meeting on Monday: it was a Higgsless APS meeting!!! As Higgsless as the models we are trying to study, isn’t that neat??

There are many physical and even philosophical reasons (well, let me say more like aesthetic reasons) for which many of us believe that we will not find the “Higgs” particle per se, i.e., not as a fundamental scalar particle but maybe as composite or none at all (although something must be there).  One of these reasons is, for example, that we have never seen a fundamental scalar particle in nature before.  I dislike the idea of the Higgs boson being a special component, why would that be?  …. Well, I guess we are at the brink of finding out… stay tuned as the LHC will resume very soon!!!!

Edgar Carrera (Boston University)

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This weekend/week is the APS “April” meeting in Washington, DC. Every year the APS has a series of meetings for each of the physics disciplines. The April meeting is reserved for Nuclear/Particle/Astrophysics. This year I submitted an abstract and gave a talk about the work I did on the uniformity study of the calorimeter (See my previous post). You can check out my abstract here.

You can actually check out all the abstracts, but I’m just giving you a link for mine . At the meeting we get the opportunity to meet other physicists to see what other experiments are working on. There’s lots of interesting science and a great opportunity to network. I joined lots of my colleagues from the Phenix collaboration. But… April meeting in February, you ask? This year it was a joint meeting with the American Association of Physics Teachers. It was a great opportunity for physicists and physics teachers to get together and discuss how to get more students interested in physics. These talks are particularly interesting because there’s always an emphasis on getting more girls into physics – something I’m obviously very interested in.

Also as I learned this week, it’s actually possible for anyone to give a talk at the APS meeting (provided they are a member – which means they pay membership feel), so every year there are people from the non-scientific community who come and present their theories. Most of these talks end up in the same session or two, so they’re easy and kind of fun to go to. Most of these are crazy and logically inconsistent or just plain wrong. If they are particularly crazy they fall into the realm of “crackpot”. I was shown a list of criteria for determining who is the biggest crackpot. See the them listed.

See if you can read the abstracts and find the ones that fall in this realm.

-Regina

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There are few things more iconic of particle physics than Feynman diagrams. These little figures of squiggly show up prominently on particle physicists’ chalkboards alongside scribbled equations. Here’s a ‘typical’ example from a previous post.

The simplicity of these diagrams has a certain aesthetic appeal, though as one might imagine there are many layers of meaning behind them. The good news is that’s it’s really easy to understand the first few layers and today you will learn how to draw your own Feynman diagrams and interpret their physical meaning.

You do not need to know any fancy-schmancy math or physics to do this!

That’s right. I know a lot of people are intimidated by physics: don’t be! Today there will be no equations, just non-threatening squiggly lines. Even school children can learn how to draw Feynman diagrams (and, I hope, some cool science). Particle physics: fun for the whole family.

For now, think of this as a game. You’ll need a piece of paper and a pen/pencil. The rules are as follows (read these carefully):

1. You can draw two kinds of lines, a straight line with an arrow or a wiggly line:
   You can draw these pointing in any direction.
2. You may only connect these lines if you have two lines with arrows meeting a single wiggly line.
   
   Note that the orientation of the arrows is important! You must have exactly one arrow going into the vertex and exactly one arrow coming out.
3. Your diagram should only contain connected pieces. That is every line must connect to at least one vertex. There shouldn’t be any disconnected part of the diagram.
   
   In the image above the diagram on the left is allowed while the one on the right is not since the top and bottom parts don’t connect.
4. What’s really important are the endpoints of each line, so we can get rid of excess curves. You should treat each line as a shoelace and pull each line taut to make them nice and neat. They should be as straight as possible. (But the wiggly line stays wiggly!)
   

That’s it! Those are the rules of the game. Any diagram you can draw that passes these rules is a valid Feynman diagram. We will call this game QED. Take some time now to draw a few diagrams. Beware of a few common pitfalls of diagrams that do not work (can you see why?):

After a while, you might notice a few patterns emerging. For example, you could count the number of external lines (one free end) versus the number of internal lines (both ends attached to a vertex).

• How are the number of external lines related to the number of internal lines and vertices?
• If I tell you the number of external lines with arrows point inward, can you tell me the number of external lines with arrows pointing outward? Does a similar relation hole for the number of external wiggly lines?
• If you keep following the arrowed lines, is it possible to end on some internal vertex?
• Did you consider diagrams that contain closed loops? If not, do your answers to the above two questions change?

I won’t answer these questions for you, at least not in this post. Take some time to really play with these diagrams. There’s a lot of intuition you can develop with this “QED” game. After a while, you’ll have a pleasantly silly-looking piece of paper and you’ll be ready to move on to the next discussion:

What does it all mean?

Continue Reading »

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Grad students working for the CMS detector.

The experiments at CERN are, in total, a collaboration of several thousands of physicists, scientists, engineers, and students. Here I show the make-up of just graduate students from just one of the experiments at CERN, the CMS detector.

People come from all over the world to contribute to these projects. It’s fantastic that so many countries and cultures are represented, and work with each other on common goals such as: recreating the big bang in the lab, studying these mini big-bangs to understand out the laws of nature that govern our universe, and then sharing these discoveries with people all over the world.

These are lofty goals, but you can be sure that whatever discoveries are made, with all the languages spoken at CERN, the knowledge will spread far.

-Mike

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First off, we should mention here that CMS’s first paper from collision data has now been accepted for publication by the Journal of High Energy Physics. It’s a measurement of the angular distribution and momentum spectrum of charged particles produced in proton collisions at 0.9 and 2.36 TeV, using about 50,000 collision events recorded in December. It is really wonderful that this result could be turned around so quickly! The first of many papers to come, we hope.

Meanwhile, as already mentioned here, we now have the news of the run plan for the LHC. CERN is preparing for the longest continuous accelerator run of its history, 18 to 24 months. The inverse femtobarn of data to be recorded in that time is a lot, and will give us an opportunity to make many interesting measurements. Whether any of them will be evidence of new physics, I for one am not going to speculate! But if nothing else, this plan sets out what our LHC life for the next ~three years is going to look like.

But a shorter-term question comes to mind — 1 fb-1 over 18 to 24 months is one thing. But what about just the next few months? There is a major international conference coming up in July. What sort of LHC results might be ready by then? That will depend in part on how many collisions are delivered. I’ve seen various estimates for that, but they vary by an order of magnitude depending on the level of optimism, so I’d rather not guess. It will also depend on the experiments’ performance. How efficiently can we record those collisions? How quickly can we process them? How soon will we understand various parts of the detectors well enough to make quality measurements? How smart and clever can we be throughout the entire process? How much sleep is everyone going to get?

Ask me again in July. Meanwhile, game on.

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We are at the stage now where the ability to crank up the intensity and energy of the LHC beams to full power is at hand.  We’re like a toddler that just learned to walk: the urge to run is present and exciting, but the probability of banging our head would be high!

It has been decided through many meetings, and with considerations of experts on the front lines, that the highest, safest energy the beams can be run at without major repairs is 3.5 TeV per beam with an instantaneous luminosity of 2*10³²/cm²/sec. (The LHC was designed for 7 TeV per beam and an intensity of 10³⁴/cm²/sec.)

More intensity means more proton collisions, and more energy means high probability of interesting collisions.  Unfortunately, high intensity and high energy also means high risk of accidents – like the one in Sep 2008.

With that in mind, management decided to balance safety of the machine with the drive to explore and make discoveries.  So, the current plan sets a goal of collecting a specific amount of data, 1 fb^-1, before shutting down for one or two years starting around the beginning of 2012 for repairs and upgrades.

If nature is hiding secrets in areas we now expect them, then this should provide enough data for discovering some of them, or at least allow ruling out some theories – and all without hurting ourselves.

-Mike

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