Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userEnergy profile of b-jet for boosted top quarks
105
0
0.0
(
0
)
Authors
Yoshio Kitadono
Ask ChatGPT about the research
No Arabic abstract
We analyse the semileptonic decay of a polarised top-quark with a large velocity based on the perturbative QCD factorisation framework. Thanks to the factorisation and the spin decomposition, the production part and the decay part can be factorised and the spin dependence is introduced in the decay part. The decay part is converted to the top-jet function which describes the distribution of jet observables and the spin is translated to the helicity of the boosted top. Using this top-jet function, the energy profile of b-jet is investigated and it is turned out that the sub-jet energy for the helicity-minus top is accumulated faster than that for the helicity-plus top. This behaviour for the boosted top can be understood with the negative spin-analysing-power of b-quark in the polarised-top decay.
rate research
Read More
We study jet substructures of a boosted polarized top quark, which undergoes the semileptonic decay $tto bell u$, in the perturbative QCD framework. The jet mass distribution (energy profile) is factorized into the convolution of a hard top-quark decay kernel with the bottom-quark jet function (jet energy function). Computing the hard kernel to leading order in QCD and inputting the latter functions from the resummation formalism, we observe that the jet mass distribution is not sensitive to the helicity of the top quark, but the energy profile is: energy is accumulated faster within a left-handed top jet than within a right-handed one, a feature related to the $V-A$ structure of weak interaction. It is pointed out that the energy profile is a simple and useful jet observable for helicity discrimination of a boosted top quark, which helps identification of physics beyond the Standard Model at the Large Hadron Collider. The extension of our analysis to other jet substructures, including those associated with a hadronically decaying polarized top quark, is proposed.
Top polarization is an important probe of new physics that couples to the top sector, and which may be discovered at the 14 TeV LHC. Taking the example of the MSSM, we argue that top polarization measurements can put a constraint on the soft supersymmetry breaking parameter A_t. In light of the recent discovery of a Higgs-like boson of mass ~125 GeV, a large A_t is a prediction of many supersymmetric models. To this end, we develop a *detector level* analysis methodology for extracting polarization information from hadronic tops using boosted jet substructure. We show that with 100 fb^(-1) of data, left and right 600 GeV stops can be distinguished to 4sigma, and 800 GeV stops can be distinguished to 3sigma.
At high values of the pair invariant mass the differential cross section for top-quark pair production at hadron colliders factorizes into soft, hard, and fragmentation functions. In this paper we calculate the next-to-next-to-leading-order (NNLO) corrections to the soft function appearing in this factorization formula, thus providing the final piece needed to evaluate at NNLO the differential cross section in the virtual plus soft approximation in the large invariant-mass limit. Technically, this amounts to evaluating the vacuum expectation value of a soft Wilson loop operator built out of light-like Wilson lines for each of the four partons participating in the hard scattering process, with a certain constraint on the total energy of the soft radiation. Our result turns out to be surprisingly simple, because in the sum of all graphs the three and four parton contributions multiply color structures whose coefficients are governed by the non-abelian exponentiation theorem.
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use low-level detector information from the simulated CMS Open Data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves an AUC score of 0.975$pm$0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier AUC score increases to 0.9824$pm$0.0013, serving as the first performance benchmark for these CMS Open Data samples. We additionally provide a timing performance comparison of different processor unit architectures for training the network.
We present results for the 2-jettiness differential distribution for boosted top quark pairs produced in $e^+e^-$ collisions in the peak region accounting for QCD large-logarithm resummation at next-to-next-to-next-to-leading logarithmic (N$^3$LL) order and fixed-order corrections to matrix elements at next-to-next-to-leading order (NNLO) calculated in the framework of soft-collinear effective theory and boosted heavy quark effective theory. Electroweak and finite-width effects are included at leading order. We study the perturbative convergence of the cross section in the pole and MSR mass schemes, with and without soft gap subtractions. We find that there is a partial cancellation between the pole mass and soft function renormalons. When renormalon subtractions concerning the top mass and the soft function are implemented, the perturbative uncertainties are, however, systematically smaller and an improvement in the stability of the peak position is observed. We find that the top MSR mass may be determined with perturbative uncertainties well below $100$,MeV from the peak position of the 2-jettiness distribution. This result has important applications for Monte Carlo top quark mass calibrations.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
