IML Machine Learning Workshop

Session

Identification and Tagging Mini-Workshop

21 Mar 2017, 09:00

222/R-001 (CERN)

Conveners

Identification and Tagging Mini-Workshop: Flavour tagging session

• Paul Seyfert (Universita & INFN, Milano-Bicocca (IT))
• Michele Floris (CERN)

Description

Tagging Mini-Workshop Part I

1. Session introduction

21/03/2017, 09:00

2. Jet reconstruction and heavy jet tagging at LHCb

Lorenzo Sestini (Universita e INFN, Padova (IT))

21/03/2017, 09:05

The jet reconstruction and the heavy jet flavour tagging at LHCb will be discussed with focus on the last published measurements such as the measurement of forward tt, W+bb and W+cc production in pp collisions at √s=8 TeV and the search for the SM Higgs boson decaying in bbbar or ccbar in association to W or Z boson.

3. Identification of Jets Containing b-Hadrons with Recurrent Neural Networks at the ATLAS Experiment

Daniel Hay Guest (University of California Irvine (US))

21/03/2017, 09:45

A novel b-jet identification algorithm is constructed with a Recurrent Neural Network (RNN) at the ATLAS Experiment. This talk presents the expected performance of the RNN based b-tagging in simulated $t \bar t$ events. The RNN based b-tagging processes properties of tracks associated to jets which are represented in sequences. In contrast to traditional impact-parameter-based b-tagging...

4. Exploring neural networks to improve b-jet tagging with the ALICE detector

Rudiger Haake (CERN)

21/03/2017, 10:10

Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions. Jets are collimated sprays of charged and neutral particles, which are produced in the fragmentation of hard scattered partons in an early stage of the collision. Heavy-quark jets, originating from beauty or charm quarks (b- and c-jets), are particularly good probes to shed light on the...

5. DeepFlavour in CMS

Markus Stoye (CERN)

21/03/2017, 10:35

Flavour-tagging of jets is an important task in collider based high energy physics and a field where machine learning tools are applied by all major experiments. A new tagger (DeepFlavour) was developed and commissioned in CMS that is based on an advanced machine learning procedure. A deep neural network is used to do multi-classification of jets that origin from a b-quark, two b-quarks, a...

6. Flavor Tagging with Deep Neural Networks at Belle II

Jochen Gemmler (KIT/IEKP)

21/03/2017, 11:30

The Belle II experiment is mainly designed to investigate the decay of B meson pairs from $\Upsilon(4S)$ decays, produced by the asymmetric electron-positron collider SuperKEKB. The determination of the B meson flavor, so-called flavor tagging, plays an important role in analyses and can be inferred in many cases directly from the final state particles. In this talk a successful approach of...

7. Inclusive tagging of B-flavour at LHCb [Vidyo]

Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

21/03/2017, 11:55

One of the most important procedure needed for the study of CP violation in Beauty sector is the tagging of the flavour of neutral B-mesons at production. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present a proposal to upgrade current flavour tagging strategy in LHCb experiment. This strategy consists of inclusive tagging ensemble...

8. Quark/gluon jet discrimination: a reproducible analysis using R

Dr Andrew Lowe (Hungarian Academy of Sciences (HU))

21/03/2017, 12:20

The power to discriminate between light-quark jets and gluon jets would have a huge impact on many searches for new physics at CERN and beyond. This talk will present a walk-through of the development of a prototype machine learning classifier for differentiating between quark and gluon jets at experiments like those at the Large Hadron Collider at CERN. A new fast feature selection method...