Before you brush off this post with the answer "of course", let me qualify the title. Of course anybody can become a particle physicist, although the learning curve can be steep and hard to climb up. But what I mean here is, can a student who has been trained as a statistician (through his or her bachelor and master degree) become a successful experimental particle physicist, without investing other years of his or her life in studying quantum mechanics and lots of other arcane physics topics ?

The question, as I see it, is important because of the way we do science at those huge particle detectors nowadays. By living and working within the large scientific collaborations that ran the CDF experiment and later the CMS experiment, I have had a chance of observing a statistically significant sample of Ph. D. students (myself included), almost exclusively trained in fundamental physics, being hit by a truck - in the form of the set of competences that are required to successfully complete a thesis on an experimental physics topic at a collider experiment.

The work of a Ph.D. student in a HEP experiment is hardly based on his or her painfully acquired competences in physics. Rather, most of their time (if we exclude the largest chunk, which is eaten out by attending to mostly useless meetings, and a few other smaller "service tasks", which also typically do not require the competences of a trained physicist) is spent writing computer programs and scripts, submitting batch jobs to computer queueing systems, and performing advanced statsitical analysis on the resulting datasets. 

At this point I am kicking myself as this post would have been much more informative and objective if I had taken the time to run a simple twitter poll before I set out to write it. I would have framed it this way: what percentage of time does a typical Ph.D. student at a LHC experiment spend in

A) activities which mostly require high-level knowledge in particle physics to be attended to
B) activities which mostly require high-level knowledge in statistics to be attended to
C) activities which mostly require other skills ?

Still, I think we can continue the discussion here even without the data, if we take my personal estimate: A - 20%; B - 50%; C - 30%. Yes, that is my point: I mean to say that a Ph.D. in experimental physics at a particle collider requires a training in statistics more than it requires a training in physics. Of course, Ph.D. students are smart: if they are confronted with a problem they go to the library and read a book; or they google a solution to it. So the fact that a significant training in statistics is required to perform tasks of relevance to their Ph.D. thesis completion is not a show-stopper for a physicist.

[Incidentally, note that I could have framed the question differently, including the request of an assessment of computing skills requirements; but here I do not need that nuisance parameter to make my point.]

If you accept for a second my above estimates of the kind of training required to a Ph.D. student at the LHC, or even if you insist in changing them by non-revolutionary amounts, you will conclude as I did that it would be good to open the door of a Ph.D. in particle physics to young statisticians. 

Of course, a student who got his or her master in Statistics will be unlikely to be attracted by the low wages and high job volatility of an academic career as a researcher in HEP. But if they are young and foolish, there will be some who may fall for the chant of physics sirens. So what Bruno Scarpa, a professor of Statistics at the University of Padova, suggested me to do was to offer a course of "Particle Physics: fundaments, instruments, and analysis methods" at the Masters in Statistics there. 

Being the lazy bum that I am, I dodged his attractive offer for a while, but finally I yielded, under pressure from my own above-mentioned beliefs. So this semester I am teaching that course, and surprisingly enough there are a dozen charitable souls who decided to take it. So far, so good.

My prospects are the following: of those 12 students, I would be delighted if one or two were to ask me for a thesis based on analysis of data from CMS. If then one of them were to apply for a Ph.D. in physics next year, I would certainly come back here to claim that the plan has worked!

But let's slow down. Between a statistician and a physicist there's a language barrier, made of the different concepts they have been exposed to in their career of studies. So my job these days is, more than teaching particle physics, to bridge that gap. I have thus been discussing the old quantum theory, special relativity, the wave-particle duality, quantum mechanics, symmetries and conservation laws, the quark model, deep inelastic scattering, and so on. In the second part of the course, however, I will try to stimulate their inner statistician in tackling real physics data analysis topics. We'll see how that goes! 


---

Tommaso Dorigo is an experimental particle physicist who works for the INFN at the University of Padova, and collaborates with the CMS experiment at the CERN LHC. He coordinates the European network AMVA4NewPhysics as well as research in accelerator-based physics for INFN-Padova, and is an editor of the journal Reviews in Physics. In 2016 Dorigo published the book “Anomaly! Collider physics and the quest for new phenomena at Fermilab”. You can get a copy of the book on Amazon.