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Travel With Two Infants

The other day I traveled with Kalliopi and our two newborns to Padova from Lulea. After six full...

A Nice Little Combination

Although I have long retired from serious chess tournaments (they take too much time, a luxury...

The Strange Case Of The Monotonous Running Average

These days I am putting the finishing touches on a hybrid algorithm that optimizes a system (a...

Turning 60

Strange how time goes by. And strange I would say that, since I know time does not flow, it is...

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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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Humanity progresses thanks to the diffusion and sharing of human knowledge. In particular, scientific progress is brought forth by the sharing of ideas, measurements and experimental results among scientists, and the distribution of excellent education. We have grown very good at doing that, but can we improve the sharing of knowledge for the common good? 

The answer is certainly yes, as the interconnection of the scientific community and the interdisciplinarity of its efforts are hampered by borders, language barriers, cultural differences, political influences, religious hindrances, education system challenges, and also by different conventions, policies, metrics in the different areas of scientific research.
At about this time of the year I find myself teaching my students about the construction of V-A theory, which is a milestone in the construction of the Standard Model of particle physics. And in so doing I rejoice about having a chance to tell them the details of one of the most brilliant experiments of the twentieth century, one performed in 1957 by Maurice Goldhaber with his colleagues Grodzins and Sunjar, and which has become a cornerstone of the physics of weak interactions and of particle physics in general. 
The DeepLearn school series, now reaching the seventh edition, offers insight into artificial intelligence and applications in a week-long course, tightly packing a significant number of high-profile instructors. The present edition, currently being held at the Technical University of Lulea, in the north of Sweden, features the following:

- Sean Benson, Netherlands Cancer Institute
- Thomas Breuel, Nvidia
- Hao Chen, Hong Kong University of Science and Technology
- Janlin Chen, University of Missouri
- Nadya Chernyavskaya, CERN
- Efstratios Gavves, University of Amsterdam
- Quanquan Gu, University of California Los Angeles
For some reasons, my personal web page features high in web searches for master thesis offers. I got to learn this by inquiring with a few students who asked me to supervise them remotely on some of the offered topics: where did they get to know about my research activities, and what led them to pick my offers? They all answered that they bumped into my web page section "thesis offers". Well, at least that was no wasted time when I wrote it.
In a recent post in this blog I discussed the idea of exploiting the properties of negative muons for a new kind of imaging technique of unknown volumes of material. The idea is based on the fact that negative muons stopped inside matter have a lifetime that is modified by nuclear interactions, so that a precise detection of their lifetime and point of decay becomes a means of inferring the composition of unknown volumes. Here, I want to offer the results of a quick simulation of the processes, to show that the idea is not so far-fetched.

Different techniques for muon tomography
Are you a recently (<8 years) appointed Ph.D. graduate in fundamental physics, who wants to work in Italy? This post is for you. The INFN is opening 20 positions for foreigners who would like to join a group of research in one of the INFN sections (there are 25 across Italy). The positions are for one year, renewable, and the salary is competitive, given that it is roughly at the level of a starting associate professor in Italy. Note, also Ph.D. students who plan to graduate before November 1st 2023 can apply! 


Also, the 8-years limit can be waived if you spent time in maternity, military service, or illness. The winning candidates are expected to start their contract before November 2023.