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AMVA4NewPhysics

A Marie Sklodowska-Curie ITN funded by the Horizon2020 program of the European Commission

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Particle Physics

Art & Science 4: Canvas Installation

by the AMVA4NewPhysics press office

Chiara Cattelan and Lorenzo Banchieri, two students of Liceo Marco Foscarini in Venice, are the authors of the work presented in this post, which along with the others presented in the former posts partecipates in the artistic contest for the EPS 2017 conference, organized by the EU project “CREATIONS” and sponsored by our network.

The two young artists have conceived an installation made up by two canvases set up back to back, representing a particle collision at the LHC from two different viewing angles – the one at the scale of the detector, which is Continue reading “Art & Science 4: Canvas Installation”

Art & Science 3: The Universe Between My Fingers

by the AMVA4NewPhysics press office

Today Ivan Bianchi, professor of Contemporary art at the University of Padova, visited along with the AMVA4NewPhysics network coordinator the Liceo “Marco Foscarini” in Venice, to assess the status of the projects produced by the students for the “Arte & Scienza” contest.

The project has been described previously. In a nutshell, it foresees artistic work by high-school students, inspured by high-energy Continue reading “Art & Science 3: The Universe Between My Fingers”

Recasting new physics searches at the LHC

The AMVA4NewPhysics work package I am involved in is related to developing tools for recasting new physics searches, with a particular focus on multivariate analyses. I would like to explain a little more about it in this article.
Let me begin by describing the motivation to look for new physics at the Large Hadron Collider (LHC). Despite the fact that the Standard Model (SM) of particle physics is very successful at describing most properties of elementary particles, there are many reasons to believe that nature is much more complicated and there is new physics, or physics beyond the Standard Model (BSM). Firstly, there is the hierarchy problem that asks why the electroweak scale or the Higgs mass, 125 GeV can be so light compared to the cutoff scale of the SM, the Planck scale if there is no BSM physics, which is 17 orders of magnitude larger than the electroweak scale. The Higgs mass is unprotected by any symmetry in the SM, and the quantum corrections to its mass are proportional to the cutoff scale. One requires an extreme fine tuning to keep the Higgs boson light while renormalizing the quantum effects, which seems to be totally unnatural. Secondly, as explained previously, there exists dark matter, which is thought by many to be a new type of elementary particle. For these and many other motivations, people are excited at the prospects of discovering BSM physics at the LHC.

Continue reading “Recasting new physics searches at the LHC”

INSIGHTS: a New Little Brother for AMVA4NewPhysics

by the AMVA4NewPhysics Press Office

AMVA4NewPhysics has a little brother, INSIGHTS. The latter is in fact young but not so little, as it starts big: it is a new ITN that has just been approved and will be funded for four years with 3.14 million euros, starting in September 2017. Like AMVA4NewPhysics, INSIGHTS is a child of the marriage of particle physics and statistics, and like AMVA4NewPhysics it will train highly-skilled graduate students on a wide range of topics, bringing interdisciplinarity into their genes. Finally, like its older brother, INSIGHTS has INFN as a beneficiary partner, and it will bring funding to its Naples and Padova section, in the latter case with Dorigo, who is also the scientific coordinator of AMVA4NewPhysics, as PI.

It is important to recall that the whole concept of the ITN institution, one of the “Marie-Curie Actions” of the Research Executive Continue reading “INSIGHTS: a New Little Brother for AMVA4NewPhysics”

Convolutional Neural Networks and neutrinos

by Cecilia Tosciri

Have you ever wondered how Facebook suggests the tags for the picture you post on your wall, or how the photo library on your computer manages to automatically create albums containing pictures of particular people? Well, they use facial recognition software based on Convolutional Neural Network (CNN).

CNN is the most popular and effective method for object recognition, and it is a specialized kind of neural network for processing data that has a known grid-like topology. The network employs a mathematical operation Continue reading “Convolutional Neural Networks and neutrinos”

My First Time at CMS

by Alessia Saggio

Every year, my university organizes a trip to CERN for Bachelor’s students only, to give them the chance to get acquainted with the world of Particle Physics before starting the Master. This year I was one of the three PhD students who accompanied them, and I thought it would be nice to share my feelings here with you since it was a really nice experience.

In fact, it was my fourth time at CERN, but despite that I had never had the chance to visit the CMS detector, the experiment Continue reading “My First Time at CMS”

Dark Matter Hunting at the LHC

by Seng Pei Liew

photo1Hello there! My name is Seng Pei Liew, and I am the “Marie Sklodowska-Curie Actions” Innovative Training Network (AMVA4NewPhysics) early-stage researcher based at the Technische Universitat Munich (TUM). I am tasked in the network to look for new physics at the Large Hadron Collider (LHC) using advanced statistical tools. In my very first article here, I would like to talk Continue reading “Dark Matter Hunting at the LHC”

W Mass: Closing In

by Tommaso Dorigo

After a lot of agonizing work on tiny systematic uncertainties, the ATLAS collaboration released in time for the Moriond conference their latest measurement of the W boson mass (in fact the only one so far). The result is in close match with previous determinations, and has a slightly larger error bar than those. So why bother discussing it here ?

There is a reason. The W boson is one of the most important subatomic particles Continue reading “W Mass: Closing In”

Big LHC Experiments Go Deep

by Markus Stoye

This week the first Inter-experimental LHC Machine Learning IML workshop took place at CERN. I showed my results on using deep learning for hadronic particle labeling (flavour tagging), a method that offers significant improvements in the labeling of heavy flavour jets for the CMS experiment (which I am member of). Despite deep learning as a topic is all over the media, the big CERN experiments have not used it a lot this far. In fact my application is, to my knowledge, the very first deep-learning application in CMS reconstruction.

The workshop featured several presentations on deep learning using Continue reading “Big LHC Experiments Go Deep”

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