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AMVA4NewPhysics

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

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Art And Science: Students At Work

By Tommaso Dorigo

The project “Art and Science: the colours of the Higgs boson” is in full swing in Venice, where 15 to 17-year-old students from three schools (the Liceo Stefanini, the Liceo Foscarini and the Liceo Benedetti) are producing artwork inspired by the CMS experiment and the Higgs boson. In this blog we already reported of conferences held at the schools by the Ph.D. students of the AMVA4NewPhysics network in January.  Now it is time for the students to build on the inspiration provided by those lectures and by the images of particle collisions, detector pieces, and Feynman diagrams.

Today I visited the students who participate to the project at Liceo Foscarini, and gave some hints and suggestions to the students on how to Continue reading “Art And Science: Students At Work”

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”

Some More Info on the IML Workshop

by Giles Strong

Below is a short summary of the IML workshop at CERN, which Markus Stoye has also reported on in the previous post.

Day 1 was a discussion with industry experts about the state and future of ML. In the afternoon there was work on the community white-paper that the IML plans to publish. This document is meant to be a road-map for where we want HEP to be in 10 years time with regards to ML. The proto-document is Continue reading “Some More Info on the IML Workshop”

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”

Fighting Gender Bias

by Tommaso Dorigo

As the few regulars of this blog know, the AMVA4NewPhysics network has in its genes a strong will to fight for gender neutrality in its areas of operation – research in Particle Physics and Applied Statistics. We started off this endeavour 2.5 years ago by including three women as PI of beneficiary nodes out of a total of eight, which was *almost* good. But their research record was outstanding, too, which helped us getting funded!

So that was easy. What was less easy was to deliver what we promised in our programme – a hiring practice capable of producing a gender-balanced pool Continue reading “Fighting Gender Bias”

Tales of a nomadic researcher

by Pablo de Castro

This is a short essay about the perks and quirks of living away and travelling as part of the job description, which is part of the deal when you join a Maria Skłodowska-Curie Innovative Training Network (ITN) as AMVA4NewPhysics and might apply for the most part to other research positions. The points made here are based on my own personal experiences and discussions with people in analogous situations. I am eager to hear your thoughts regarding this matter in the comment section!

Continue reading “Tales of a nomadic researcher”

AMVA4NewPhysics Deliverable 4.1: Report of the Performance of Algorithms for Data-Driven Background Shape Modeling

by AMVA4NewPhysics press office

And here it is, the second – but really synchronous in publication with the first – scientific deliverable of our network. Deliverable 4.1, titled “Report of the Performance of Algorithms for Data-Driven Background Shape Modeling“, is a report of studies performed by network members operating within Work Package 4, also known as “New Statistical Learning Tools for HEP Analysis“.

The research presented in this document aims at constructing a precise representation of background processes to searches for small signals in hadron collider data. Specifically, we focused on the multijet QCD background, Continue reading “AMVA4NewPhysics Deliverable 4.1: Report of the Performance of Algorithms for Data-Driven Background Shape Modeling”

AMVA4NewPhysics Deliverable 1.1: MVA for Higgs Boson Searches at the LHC

by the AMVA4NP press office

It is with a certain satisfaction that I can announce today that the AMVA4NewPhysics network is in complete control of its planned schedule, and has now started to provide real research-grade output, delivering its first two scientific products of relevance. Deliverable 1.1 (from work package 1, which focuses on MVA applications to Higgs boson studies) and Deliverable 4.1 (from work package 4, which focuses on the development of entirely new Machine Learning tools with in mind their application to specific HEP Continue reading “AMVA4NewPhysics Deliverable 1.1: MVA for Higgs Boson Searches at the LHC”

Decision Trees, Explained to Kids

by Tommaso Dorigo

Decision trees are one of the many players in the booming field of supervised machine learning. They can be used to classify elements into two or more classes, depending on their characteristics. Their interest in particle physics applications is large, as we always need to try and decide on a statistical basis what kind of physics process originated the particle collision we see in Continue reading “Decision Trees, Explained to Kids”

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