A canister, containing AMS being loaded onto the space shuttle Endeavour. Photo from NASA.
I had a plan for this first post, but unfortunately, like so much in life, it didn’t work out quite as I hoped. The plan went like this: On April 19th the space shuttle Endeavour was set to launch from the Kennedy Space Centre in Florida. Having recently relocated to Louisiana from the UK, I found myself within “easy” travelling distance of a launch for the first time ever. So like any good, space-obsessed 26-year-old, I immediately set plans in action to journey across the US and set up camp on the beach to watch this once-in–a-lifetime event.
Endeavour was set to transport the Alpha Magnetic Spectrometer 2 (AMS-02) to the International Space Station. AMS is a nifty little particle physics detector (little in the context of LHC-style detectors) designed to study the content of cosmic rays for evidence of dark matter and anti-helium. This provided the perfect tie–in between a trip to see the big rockets and my day-to-day work on ATLAS.
Even more so as I spent my PhD years helping design search strategies for neutralinos. Which are the hypothesised partner particles to the Standard Model gauge bosons, the force-carrying particles, proposed by a particularly popular extension to the Standard Model, Supersymmetry. And they represent a prime dark matter candidate.
Unfortunately though, this plan came crashing down when NASA postponed the launch date of the shuttle by 10 days, putting it right in the middle of a conference I’m scheduled to attend and hence scuppering both my travel and blog plans.
This set me thinking about delays and how delays to big experiments have a defining role in so many careers. The biggest and most public delay of recent years was the postponing of the LHC physics programme following the quenching incident of ’08. I was present at CERN at the time and remember well the sense of disappointment that surrounded this. Of course, it was quickly replaced with a cheery optimism as everyone settled in for another year with our treasured simulations and the always-relished chance to polish our respective code bases. I was lucky enough to be studying at a UK university at the time, so I was able to continue my studies — and complete the vast bulk of my thesis — using only these simulations and very little real data.
A lot of my US contemporaries were not so lucky. They needed data in order to be able to graduate. This led to a lost generation of students who had to either switch experiments or ride out the new LHC schedule and wait for the data. A lot of these students are still around today, all putting the finishing touches to their theses, and generally being massively over qualified for the post-doctoral positions they are only now applying for.
All of which goes to show that planning your life around science doesn’t always turn out the way you expected.
