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Some Notes On The Utility Function Of Fundamental Science Experiments

Earlier this year I mentioned here that I would be writing an article on how the utility function...

Understanding Expected Limits, Observed Limits, Exclusion Regions In Particle Physics Graphs

I recently got engaged in a conversation with a famous retired mathematician / cosmologist about...

Establishing Benchmarks For Use Of AI In Fundamental Science: Two Proposals To Move Forward

These days I am in the middle of a collaborative effort to write a roadmap for the organization...

Optimization In Valencia

Last week I was in Valencia, to attend the fourth MODE Workshop on Differentiable Programming for...

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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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In the previous post I have described some of the main functionalities of the RadiaCode 103 radiation spectrometer, which the company graciously made available for my tests. Here I want to discuss some additional tests I have done, using radioactive samples from my minerals collection as well as a couple of test sources we have in our Physics department in Padova.
A few days ago I put my hands on a RadiaCode 103, a pocket radiation counter, dosimeter, and spectrometer that has recently appeared on the market. The company that produces it, RadiaCode, is located in Cyprus (see https://radiacode.com). The instrument is a portable device that pairs up with a smartphone or a PC for maximum functionality, but can well operate as a standalone unit to provide quite a bit more functionality than the standard monitoring and dosimeter capabilities of other instruments.
Here is the unit as it comes, packaged in a style similar to that of smartphones. The package contains the unit and a USB-C cable, plus a card with a QR-code link to the manuals and software.


Time and again, I play a "good" blitz chess game. In blitz chess you have 5 minutes thinking for the totality of your game. This demands quick reasoning and a certain level of dexterity - with the mouse, if you are playing online as I usually do.
My blitz rating on the chess.com site hovers around 2150-2200 elo points, which puts me at the level of a strong candidate master or something like that, which is more or less how I would describe myself. But time is of course running at a slower, but more unforgiving pace in my life, and I know that my sport prowess is going to decline - hell, it has already. So it makes me happy when I see that I can still play a blitz game at a decent level. Today is one of those days.
Yesterday I was in Oslo, where I was invited tro serve as the leading opposer in the Ph.D. defense of a student of Alex Read, who is a particle physicist and a member of the ATLAS collaboration. Although I have served in similar committees several times in the past, this turned out to be a special experience for me for a couple of reasons.
Yesterday I gladly attended a symposium in honor of Giorgio Bellettini, who just turned 90. The italian physicist, who had a very big impact in particle physics in his long and illustrious career, is still very active -e.g. he makes all the hard questions at the conferences he attends, as he has always done. The symposium included recollections of Giorgio's career and achievements by colleagues who collaborated with him and/or shared a part of his path. Among them there were talks by Samuel Ting, Paul Grannis, Michelangelo Mangano, Hans Grasmann, Mario Greco.
I also was allowed to give a short recollection of a couple of episodes, that underline the exceptional disposition of Giorgio with students. Here is a quick-and-dirty English translation of my speech (it was in Italian).
... if you are a researcher in physics or astrophysics and you are working with machine learning, that is.

Between September 23 and 25 - just when summer is over - we will meet in Valencia, Spain, to discuss the latest developments in deep learning applications to optimization of experiments in fundamental science. This is the fourth workshop of the MODE Collaboration, which focuses on a new frontier of application of deep learning: co-design and high-level optimization, and the tools to pull it off.