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Tommaso DorigoRSS Feed of this column.

Tommaso Dorigo is an experimental particle physicist, who works for the INFN at the University of Padova, and collaborates with the CMS and the SWGO experiments. He is the president of the Read More »

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Dec 13 2018 | comment(s)

It's been a while since I last discussed something personal in this column. The reason is not that I changed my mind with respect to being open and freely share my ideas, experiences, and personal life things here - I have long argued that if a blog is not personal, it is not interesting, and I stand by that assessment. 
Rather, the reason of my not talking much about myself and my personal / work life is the good old one: lack of time. If I have time to write an article, I try to do it on a subject which I suppose will be more interesting to the readers of this site. Hence physics, rather than life and work, takes the precedence. But it needs not be so all the time, so today I will try to go in the other direction.
My CMS colleague Didar Dobur, who chairs the "Top Properties" working group in the experiment, presented today the first observation of the process whereby a top quark is produced in association to a Z boson. I could follow the presentation by videoconference, so I am blogging about this result in close to real time, for a change.
What machine will replace the Large Hadron Collider to further our knowledge of fundamental physics at the high-energy frontier, in the forthcoming decades? 

The question is not at all a far-fetched one: these large machines require two decades to be built - and can then typically be operated for two further decades, amassing collision data that slowly but steadily improve the precision of our estimates of the parameters of nature.
As I mentioned in yesterday's post, there is a workshop going on this week at Fermilab, where 110 attendees - mostly particle physicists, but some computer scientists are also present - discuss how to push for more effective use of machine learning tools in the extraction of information on particle collisions. 

Also one goal is to understand what new ideas from the world of machine learning could find ideal applications in the typical use cases of research in fundamental physics. Here I wish to mention a few interesting things that I heard at the workshop so far, in random order. I will rarely make direct reference to the talks, to encourage you to dig into the pdf files available here.
When I  took Hwy 88-E toward Fermilab, shortly after landing at the Chicago O' Hare Airport yesterday afternoon, it occurred to me that the first time I had driven there happened 26 years and five months ago, in June 1992, when I was 26 years and five months old. 
What makes the observation significant is that the trip to Fermilab I made 26 years ago arguably marked the start of my career as a particle physicist, something that I consider as a non-trivial defining moment in my life. I was still a student back then, but from that point on I started doing serious research with the physics of elementary particles, and I have never stopped doing that since. 
I flew to the US yesterday to get to Fermilab, where I am following a workshop titled Machine learning for jet physics". My goal of this post is to explain what this is about in general terms, such that if I have enough stamina I will give, in follow-ups to it, a few examples of the status of this interesting research activity, which encompasses particle physics and computer science and can provide spin-offs in a number of related areas of fundamental research.