A Quantum Diaries Survivor

I was happy to meet Giorgio Bellettini at the Pisa Meeting on Advanced Detectors this week, and I thought I would write here a note about him. At 89 years of age Giorgio still has all his wits around him, and he is still as compelling and unstoppable as anybody who has met him will recall. It is a real pleasure to see that he still attends all sessions, always curious to hear the latest developments in detector design and performance. 

Two recent analyses by the CMS experiments stand out, in my opinion, for their suggestive results. They both produce evidence at the two-three sigmaish level of the signals they were after: this means that the probability of the observed data under the no-signal hypothesis is between a few percent and a one in a thousand, so nothing really unmistakable. But the origin of the observed effects are probably of opposite nature - one is a genuine signal that is slowly but surely sticking its head up as we improve our analysis techniques and collect more data, while the other is a fluctuation that we bumped into. 

The recent precise measurement of the W boson mass produced by the non-dead CDF collaboration last month continues to be at the focus of attention by the scientific community, for a good reason - if correct, the CDF measurement in and of itself would be the conclusive proof that our trust in the Standard Model of particle physics when producing predictions of particle phenomenology needs a significant overhaul. 

My attendance to the JENAS symposium in Madrid this week provided me with the opportunity to meet some of the senior colleagues who will influence the future development of technologies for fundamental research in the coming decade and more. Over coffee-break discussions, poster sessions, and social dinner I exploited the situation by stressing a few points which I have come to consider absolutely crucial for our field. Of course I am moved not only by caring for the progress of humanity but also by the fact that I would like the research plan I have put together in collaboration with a few colleagues to succeed... Ultimately, the two things are very well aligned though!

As I write these few lines, I am sitting in the nice auditorium at CSIC in Madrid, where I came for a congress that is a bit different to many others that take place around the world at all times. Truth be told, covid-19 took a big hit on the organization of these events, but slowly things are getting back to normality - the only visible sign of something different from 2019 in the auditorium is the fact that about 80 percent of the 180 scientists sitting around me wear a mask.

The "Learning to Discover" workshops and "AI and Physics" conference are taking place at Institut Pascal, a centre set on the top of a hill surrounded by woods near Orsay, France. The event focuses on new artificial intelligence techniques to improve the discovery potential of fundamental science experiments.Below you can see a summary of the event agenda: - Apr 19-20 Representation learning workshop- Apr 21-22 Dealing with uncertainties workshop- Apr 25-26 Generative models workshop- Apr 27-29 AI and Physics Conference

No.... Ok, ok, I will elaborate. But first I feel the need to explain what we are talking about here, to anybody who does not have a Ph.D. in particle physics and is still reading this column.Background: The Tevatron, CDF, and the W boson

Ever since experimental physics was a thing, the worth of scientists could be appraised by how carefully they designed their experiments, making sure that their devices could answer as precisely as possible the questions that crowded their mind. Indeed, the success of their research depended on making the right choices on what apparatus to build, with what materials, what precise geometry, and how to operate it for best results.(Above: Ramsay and Pierre Curie in their lab)

The late Martin Gardner held for many years a fantastic feature in the popular Scientific American magazine. It was called "Mathematical Games", and it was worth the whole magazine by itself, although SciAm always featured many interesting articles about scientific advancements. Upon picking the magazine up at a newsstand, "Mathematical Games" was the first article I would read as a teenager eager to learn about the endless tricks Gardner taught there, in his wonderful tale-telling style.

Like the vast majority of readers of this column, I very strongly condemn the Russian invasion of Ukraine and the ensuing atrocities. War is never an answer to international controversies. And I would like to add: I am in favor of all sanctions that financially hit the aggressor, including cutting Russia from use of international banking circuits and similar impactful actions.That said, I will say here what I think about this ongoing rush to find ways to hurt a country whose citizens are largely innocent of their leader's crimes. I think most of these creative initiatives are counter-productive, reaching the nonsensical, the irrational, and the plain nuts. 

Over the course of the past two decades we have witnessed the rise of deep learning as a paradigm-changing technology. Deep learning allows algorithms to dramatically improve their performance on multivariate analysis tasks. Deep neural networks, in particular, are very flexible models capable of effective generalization of available data, with unbeatable results in their predictions. Indeed, from the outside, nowadays it looks as if the game changer in predictive analysis was the construction of large neural network architectures. But it was not.

The behaviour of matter at quantum level includes a number of surprising effects, which we are lucky enough to be able to study and observe in different physical systems. Some of these effects are due to the radically different properties of particles endowed with integer amounts of spin (which we call bosons), and particles endowed with half-integer amounts of spin (which we call fermions).