scholarly journals Jet substructure in p+p and p+Au collisions at $\sqrt{s_\mathrm{NN}}$ = 200 GeV at STAR

2021 ◽  
Author(s):  
Isaac Mooney ◽  
Keyword(s):  
Jet Substructure ◽  
200 Gev

scholarly journals Measurement of groomed jet substructure observables in p+p collisions at s=200 GeV with STAR

2020 ◽  
Vol 811 ◽  
pp. 135846 ◽  
Author(s):  
J. Adam ◽  
L. Adamczyk ◽  
J.R. Adams ◽  
J.K. Adkins ◽  
G. Agakishiev ◽  
...  
Keyword(s):  
Jet Substructure ◽  
200 Gev

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.

scholarly journals Exploring the Partonic Phase at Finite Chemical Potential in and out-of Equilibrium

Particles ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 178-192 ◽  
Author(s):  
O. Soloveva ◽  
P. Moreau ◽  
L. Oliva ◽  
V. Voronyuk ◽  
V. Kireyeu ◽  
...  
Keyword(s):  
Cross Sections ◽  
Chemical Potential ◽  
Transport Coefficients ◽  
Gluon Plasma ◽  
Entropy Density ◽  
Baryon Chemical Potential ◽  
Equilibrium Study ◽  
200 Gev ◽  
Quasiparticle Model ◽  
Scattering Cross Sections

We study the influence of the baryon chemical potential μ B on the properties of the Quark–Gluon–Plasma (QGP) in and out-of equilibrium. The description of the QGP in equilibrium is based on the effective propagators and couplings from the Dynamical QuasiParticle Model (DQPM) that is matched to reproduce the equation-of-state of the partonic system above the deconfinement temperature T c from lattice Quantum Chromodynamics (QCD). We study the transport coefficients such as the ratio of shear viscosity η and bulk viscosity ζ over entropy density s, i.e., η / s and ζ / s in the ( T , μ ) plane and compare to other model results available at μ B = 0 . The out-of equilibrium study of the QGP is performed within the Parton–Hadron–String Dynamics (PHSD) transport approach extended in the partonic sector by explicitly calculating the total and differential partonic scattering cross sections based on the DQPM and the evaluated at actual temperature T and baryon chemical potential μ B in each individual space-time cell where partonic scattering takes place. The traces of their μ B dependences are investigated in different observables for symmetric Au + Au and asymmetric Cu + Au collisions such as rapidity and m T -distributions and directed and elliptic flow coefficients v 1 , v 2 in the energy range 7.7 GeV ≤ s N N ≤ 200 GeV.

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 Semihard scattering of partons ats=17vs 200 GeV: A study in contrast

2002 ◽  
Vol 66 (6) ◽  
Author(s):  
Steffen A. Bass ◽  
Berndt Müller ◽  
Dinesh K. Srivastava
Keyword(s):  
200 Gev
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