Identification of the quark jet charge in e+e−→W+W− using neural networks and discriminant analysis methods

Lepton number violation may arise via the spontaneous breakdown of a global symmetry. In extra dimensions, spontaneous lepton number violation in the bulk implies the existence of a Goldstone boson, the majoron J (0) , as well as an accompanying tower of Kaluza-Klein (KK) excitations, J (n) . Even if the zero-mode majoron is very weakly interacting, so that detection in low-energy processes is difficult, the sum over the tower of KK modes may partially compensate in processes of relevance at high-energy colliders. Here we consider the inclusive differential and total cross sections for e − e − → W − W − J, where J represents a sum over KK modes. We show that allowed parameter choices exist for which this process may be accessible to a TeV-scale electron collider.

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“…While this is nontrivial, the use of neural networks in extracting the charges in W pair production appears to be a promising approach [16].…”

Section: Discussionmentioning

confidence: 99%

Bulk majorons at colliders

2002

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“…The output layer generates the network response vector Y. Non-linear neural computing performed by the network shown in (Figure 5) can be expressed by (11).…”

Section: Back-propagation Neural Networkmentioning

confidence: 99%

“…Statistical techniques such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) were the first to be used in this field [9][10][11]. The Random Forest Algorithms are based on the decision trees classifier; it has been considered significantly in development of fault machine diagnostics methods through a powerful method for classification and predictions [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches

Ouadine

Mjahed

Ayad³

et al. 2018

Applied Sciences

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Monitoring and diagnosis of rotating machines has become an effective and indispensable tool for the efficient and timely detection of defects, avoiding then incidents that can have serious economic and human consequences. Bearings are the most sensitive parts of these machines; this is why special attention must be paid to its monitoring. This paper presents a methodology for diagnosing an aircraft air compressor bearing using neural networks that have been optimized by genetic algorithms. We used in our study a database of vibratory signals that were recorded on a test bench from bearings with different defects. The faults features are extracted from these noisy signals using the estimate of the spectral density. The diagnostic capacity of obtained model has been demonstrated by a comparative study with two other automatic classifiers, which are discriminant analysis and neural networks whose training has been done with the Back-Propagation algorithm. This approach has the advantage of simultaneously ensuring the optimal structure of the neural network and accomplishing its learning. The importance of this study is the construction of a diagnostic tool that is characterized by efficiency, speed of decision making and ease of implementation not only on the computers on the ground, but also on the mounted calculators on aircraft.

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“…Given the conservation of charge in the hadronisation process, the charge of the originating parton could be identified by the identification of the charge of the hadrons to which a jet is fragmented [181,182]. Similar methods are used to measure the charge of the top quark by both ATLAS and CMS [183,184] to exclude the BSM processes with exotic top quark charge of −4/3.…”

Section: Discussionmentioning

confidence: 99%

Measurement of the W Boson Helicity Fractions in Top/anit-Top Events at 8 TeV in the Lepton + Jets Channel with the ATLAS Detector

Kareem¹

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Precise measurements of the properties of the top quark allow for testing the Standard Model (SM) and can be used to constrain new physics models. The top quark is predicted in the SM to decay almost exclusively to a W boson and b-quark. Thus, studying the W tb vertex structure at high precision and in detail is motivated. This thesis presents a measurement of the W boson helicity fractions in top quark decays with t t events in the lepton + jets final state using proton-proton collisions at a centre-of-mass energy of √ s = 8 TeV recorded in 2012 with the ATLAS detector at the LHC. The data sample corresponds to an integrated luminosity of 20.2 fb −1 . The angular distribution of two different analysers, the charged lepton and the down-type quark in the W boson rest frame are used to measure the helicity fractions. The most precise measurement is obtained from the leptonic analyser and events which contain at least two b-quark tagged jets. The results of F 0 = 0.709 ± 0.012 (stat.+bkg. norm.) +0.015 −0.014 (syst.), F L = 0.299 ± 0.008 (stat.+bkg. norm.) +0.013 −0.012 (syst.), F R = −0.008 ± 0.006 (stat.+bkg. norm.) ±0.012 (syst.), which stand for longitudinal, left-and right-handed W boson helicity fractions respectively, are obtained by performing a combined fit of electron+jets and muon+jets channels to data. The measured helicity fractions are consistent with the Standard Model prediction. As the polarisation state of the W boson in top quark decays is sensitive to the W tb vertex structure, limits on anomalous W tb couplings are set.

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Identification of the quark jet charge in e+e−→W+W− using neural networks and discriminant analysis methods

Cited by 5 publications

References 21 publications

Bulk majorons at colliders

Bulk majorons at colliders

Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches

Measurement of the W Boson Helicity Fractions in Top/anit-Top Events at 8 TeV in the Lepton + Jets Channel with the ATLAS Detector

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