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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

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”

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”

Anomaly! Now Available As E-Book

by Tommaso Dorigo

Today I would like to mention that my book “Anomaly! Collider Physics and the Quest for New Phenomena at Fermilab” is now available for purchase as E-Book at its World Scientific site.
For the occasional readers and the absent-minded regulars, below I paste a summary of what the book is about, the endorsements it received from distinguished scientists in the field, and a few links to reviews in internet resources. The web site of the book at World Scientific is here. At the WS site you Continue reading “Anomaly! Now Available As E-Book”

Tagging and probing

by Alexander Held

The winter conferences are approaching, where both ATLAS and CMS are aiming to show their latest scientific results with the data gathered in the last year. 2016 saw a huge increase in the size of this dataset, which results in a drastic increase in sensitivity to some of the phenomena we are searching for. A large amount of work goes into understanding this data and ensuring that the models we are Continue reading “Tagging and probing”

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