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One More Episode In The Dark Matter Search Saga

Do you remember the DAMA-LIBRA experiment? It is a underground detector made of sodium iodide crystals...

A Homage To Ludwig Van Beethoven

A long time ago, before starting the studies which would lead to a career as a particle physicist...

Searching In The Dark: Unsupervised Learning Meets Fundamental Science

The title of this post is the same of a non-technical presentation I gave today at the 2021 USERN...

A Few Lectures You May Want To Attend To

In the next few days I have a busy schedule with a few lectures gravitating around the use of deep...

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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 experiment at the CERN LHC. He coordinates the European network... Read More »

With the delta variant of Covid-19 surging in many countries - e.g., over 100,000 new cases per day foreseen in the UK in the next few days, and many other countries following suit - we may feel depressed at the thought that this pandemic is going to stay with us for a lot longer than some originally foresaw.
In truth, if you could sort out your sources well, you would have predicted this a long time ago: epidemiologists had in fact foreseen that there would continue to be waves of contagions, although at some point mitigated by the vaccination campaigns. However, so much misinformation and falsehood on the topic has been since dumped on all media, and in particular on the internet, that it is easy to pick up wrong information.
Following my strong belief that science dissemination, and open borders science, is too important to pursue as a goal to constrain it by fears of being stripped of good ideas and scooped by fast competitors, I am offering here some ideas on a reserch plan I am going to follow in the coming months.

The benefits of sharing thoughts early on is evident: you may, by reading about them below, be struck with a good idea which may further improve my plan, and decide to share it with me; you might become a collaborator - which would add to the personpower devoted to the research. You might point out problems, issues to address, or mention that some or all of the research has already been done by somebody else, and published - which would save me a lot of time!
After over one year of forced confinement, due to the still ongoing Covid-19 pandemic, academics around the world seem to have settled down on the idea that after all, we can still do our job via videoconferencing. We had to adapt to the situation as everybody else, of course, and in a general sense we are a privileged minority - other human occupations which are only possible in person suffered way more.
One of the reasons why I love my job as a researcher in experimental physics is that every day brings along a new problem to solve, and through decades of practice I have become quick at solving them, so I typically enjoy doing it. And it does not matter whether the problem at hand is an entirely new, challenging one or a textbook thing that has been solved a million times before. It is your problem, and it deserves your attention and dedication.
In the previous post I mentioned a research project that I was about to conclude, centered on the detection of anomalies in multidimensional data. Here I would like to give some more detail of that research, as the article I wrote on the subject is now publically accessible in the Cornell preprint arXiv (and is being sent to a refereed journal).
Usually, when we talk about our research we discuss things we have recently published, highlighting the importance or novelty of their contribution to the advancement of human understanding or knowledge of the specific field of Science we work on. 

So it is only normal for me to try and go against that particular cliché here, and talk about things I will publish in the future. Admittedly, it is a bit of a mine field (it is never easy to be an anticonformist), but I will try to avoid stepping on the most obvious triggers (violations of confidentiality, scooping risks, impossible promises).

1. A new tool for anomaly detection