scholarly journals Looking for a vectorlike B quark at the LHC using jet substructure

2021 ◽  
Vol 104 (3) ◽  
Author(s):  
Debajyoti Choudhury ◽  
Kuldeep Deka ◽  
Nilanjana Kumar
Keyword(s):  
Jet Substructure ◽  
B Quark

scholarly journals Identification of boosted Higgs bosons decaying into b-quark pairs with the ATLAS detector at 13 $$\text {TeV}$$

2019 ◽  
Vol 79 (10) ◽  
Author(s):  
G. Aad ◽  
◽  
B. Abbott ◽  
D. C. Abbott ◽  
O. Abdinov ◽  
...  
Keyword(s):  
Top Quark ◽  
Hadron Collider ◽  
Atlas Detector ◽  
Higgs Bosons ◽  
Proton Collision ◽  
Jet Substructure ◽  
Proton Proton ◽  
Quark Pairs ◽  
Systematic Uncertainties ◽  
B Quark

Abstract This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, $$H \rightarrow b\bar{b}$$H→bb¯, for proton–proton collision data collected by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy $$\sqrt{s}=13$$s=13 $$\text {TeV}$$TeV. These decays are reconstructed from calorimeter jets found with the anti-$$k_{t}$$kt$$R = 1.0$$R=1.0 jet algorithm. To tag Higgs bosons, a combination of requirements is used: b-tagging of $$R = 0.2$$R=0.2 track-jets matched to the large-R calorimeter jet, and requirements on the jet mass and other jet substructure variables. The Higgs boson tagging efficiency and corresponding multijet and hadronic top-quark background rejections are evaluated using Monte Carlo simulation. Several benchmark tagging selections are defined for different signal efficiency targets. The modelling of the relevant input distributions used to tag Higgs bosons is studied in 36 fb$$^{-1}$$-1 of data collected in 2015 and 2016 using $$g\rightarrow b\bar{b}$$g→bb¯ and $$Z(\rightarrow b\bar{b})\gamma $$Z(→bb¯)γ event selections in data. Both processes are found to be well modelled within the statistical and systematic uncertainties.

scholarly journals Contribution of the Darwin operator to non-leptonic decays of heavy quarks

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
Alexander Lenz ◽  
Maria Laura Piscopo ◽  
Aleksey V. Rusov
Keyword(s):  
Standard Technique ◽  
Quark Propagator ◽  
Leptonic Decay ◽  
Leptonic Decays ◽  
Interference Contribution ◽  
The Standard Model ◽  
Strength Tensor ◽  
Quark Flavour ◽  
Quark Decay ◽  
B Quark

Abstract We compute the Darwin operator contribution ($$ 1/{m}_b^3 $$ 1 / m b 3 correction) to the width of the inclusive non-leptonic decay of a B meson (B+, Bd or Bs), stemming from the quark flavour-changing transition b → $$ {q}_1{\overline{q}}_2{q}_3 $$ q 1 q ¯ 2 q 3 , where q1, q2 = u, c and q3 = d, s. The key ideas of the computation are the local expansion of the quark propagator in the external gluon field including terms with a covariant derivative of the gluon field strength tensor and the standard technique of the Heavy Quark Expansion (HQE). We confirm the previously known expressions of the $$ 1/{m}_b^3 $$ 1 / m b 3 contributions to the semi-leptonic decay b → $$ {q}_1\mathrm{\ell}{\overline{\nu}}_{\mathrm{\ell}} $$ q 1 ℓ ν ¯ ℓ , with ℓ = e, μ, τ and of the $$ 1/{m}_b^2 $$ 1 / m b 2 contributions to the non-leptonic modes. We find that this new term can give a sizeable correction of about −4 % to the non-leptonic decay width of a B meson. For Bd and Bs mesons this turns out to be the dominant correction to the free b-quark decay, while for the B+ meson the Darwin term gives the second most important correction — roughly 1/2 to 1/3 of the phase space enhanced Pauli interference contribution. Due to the tiny experimental uncertainties in lifetime measurements the incorporation of the Darwin term contribution is crucial for precision tests of the Standard Model.

scholarly journals Explainable AI for ML jet taggers using expert variables and layerwise relevance propagation

2021 ◽  
Vol 2021 (5) ◽  
Author(s):  
Garvita Agarwal ◽  
Lauren Hay ◽  
Ia Iashvili ◽  
Benjamin Mannix ◽  
Christine McLean ◽  
...  
Keyword(s):  
Network Performance ◽  
Deep Neural Network ◽  
Relevant Information ◽  
Jet Substructure ◽  
Discrimination Ability ◽  
Low Level ◽  
Performance Improvements ◽  
Intermediate Layers ◽  
Explainable Ai ◽  
General Method

Abstract A framework is presented to extract and understand decision-making information from a deep neural network (DNN) classifier of jet substructure tagging techniques. The general method studied is to provide expert variables that augment inputs (“eXpert AUGmented” variables, or XAUG variables), then apply layerwise relevance propagation (LRP) to networks both with and without XAUG variables. The XAUG variables are concatenated with the intermediate layers after network-specific operations (such as convolution or recurrence), and used in the final layers of the network. The results of comparing networks with and without the addition of XAUG variables show that XAUG variables can be used to interpret classifier behavior, increase discrimination ability when combined with low-level features, and in some cases capture the behavior of the classifier completely. The LRP technique can be used to find relevant information the network is using, and when combined with the XAUG variables, can be used to rank features, allowing one to find a reduced set of features that capture part of the network performance. In the studies presented, adding XAUG variables to low-level DNNs increased the efficiency of classifiers by as much as 30-40%. In addition to performance improvements, an approach to quantify numerical uncertainties in the training of these DNNs is presented.

Advances in Jet Substructure at the LHC

2021 ◽  
Author(s):  
Roman Kogler
Keyword(s):  
Jet Substructure

scholarly journals Bs → Kℓv form factors with 2+1 flavors

2018 ◽  
Vol 175 ◽  
pp. 13008 ◽  
Author(s):  
Yuzhi Liu ◽  
Jon A. Bailey ◽  
A. Bazavov ◽  
C. Bernard ◽  
C. M. Bouchard ◽  
...  
Keyword(s):  
Quark Mass ◽  
Strange Quark ◽  
Lattice Spacing ◽  
Light Quark ◽  
Form Factors ◽  
Ckm Matrix ◽  
Strange Quark Mass ◽  
Light Quark Mass ◽  
B Quark

Using the MILC 2+1 flavor asqtad quark action ensembles, we are calculating the form factors f0 and f+ for the semileptonic Bs → Kℓv decay. A total of six ensembles with lattice spacing from ≈ 0.12 to 0.06 fm are being used. At the coarsest and finest lattice spacings, the light quark mass m’l is one-tenth the strange quark mass m’s. At the intermediate lattice spacing, the ratio m’l/m’s ranges from 0.05 to 0.2. The valence b quark is treated using the Sheikholeslami-Wohlert Wilson-clover action with the Fermilab interpretation. The other valence quarks use the asqtad action. When combined with (future) measurements from the LHCb and Belle II experiments, these calculations will provide an alternate determination of the CKM matrix element |Vub|.

scholarly journals Search for $$ t\overline{t} $$ resonances in fully hadronic final states in pp collisions at $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

2020 ◽  
Vol 2020 (10) ◽  
Author(s):  
G. Aad ◽  
◽  
B. Abbott ◽  
D. C. Abbott ◽  
A. Abed Abud ◽  
...  
Keyword(s):  
Production Cross ◽  
Hadron Collider ◽  
Top Quarks ◽  
Atlas Detector ◽  
Proton Collision ◽  
Large Radius ◽  
Final States ◽  
Jet Substructure ◽  
High Transverse Momentum ◽  
Hadronic Final States

Abstract This paper presents a search for new heavy particles decaying into a pair of top quarks using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of $$ \sqrt{s} $$ s = 13 TeV with the ATLAS detector at the Large Hadron Collider. The search is performed using events consistent with pair production of high-transverse-momentum top quarks and their subsequent decays into the fully hadronic final states. The analysis is optimized for resonances decaying into a $$ t\overline{t} $$ t t ¯ pair with mass above 1.4 TeV, exploiting a dedicated multivariate technique with jet substructure to identify hadronically decaying top quarks using large-radius jets and evaluating the background expectation from data. No significant deviation from the background prediction is observed. Limits are set on the production cross-section times branching fraction for the new Z′ boson in a topcolor-assisted-technicolor model. The Z′ boson masses below 3.9 and 4.7 TeV are excluded at 95% confidence level for the decay widths of 1% and 3%, respectively.

scholarly journals Jet substructure classification in high-energy physics with deep neural networks

2016 ◽  
Vol 93 (9) ◽  
Author(s):  
Pierre Baldi ◽  
Kevin Bauer ◽  
Clara Eng ◽  
Peter Sadowski ◽  
Daniel Whiteson
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
High Energy Physics ◽  
High Energy ◽  
Jet Substructure ◽  
Energy Physics

scholarly journals Measurement of the effective b quark fragmentation function at the Z resonance

1995 ◽  
Vol 357 (4) ◽  
pp. 699-714 ◽  
Author(s):  
D. Buskulic ◽  
D. Casper ◽  
I. De Bonis ◽  
D. Decamp ◽  
P. Ghez ◽  
...  
Keyword(s):  
Fragmentation Function ◽  
Quark Fragmentation ◽  
B Quark

scholarly journals Probing quarkonium production mechanisms with jet substructure

2014 ◽  
Vol 2014 (11) ◽  
Author(s):  
Matthew Baumgart ◽  
Adam K. Leibovich ◽  
Thomas Mehen ◽  
Ira Z. Rothstein
Keyword(s):  
Jet Substructure ◽  
Quarkonium Production ◽  
Production Mechanisms

NLO corrections to c - and b -quark fragmentation into j/ψ and γ

2017 ◽  
Vol 95 (3) ◽  
Author(s):  
R. Sepahvand ◽  
S. Dadfar
Keyword(s):  
Quark Fragmentation ◽  
B Quark
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