We study the issue of separating hadronic jets that contain bottom quarks ($b$-jets) from jets featuring light partons only. We develop a novel approach to $b$-tagging that exploits the application of QCD-inspired jet substructure observables such as one-dimensional jet angularities and the two-dimensional primary Lund plane. We demonstrate that these observables can be used as inputs to modern machine-learning algorithms to efficiently separate $b$-jets from light ones. In order to test our tagging procedure, we consider simulated events where a $Z$ boson is produced is association with jets and show that using jet angularities as an input for a deep neural network, as well as using images obtained from the primary Lund jet plane as input to a convolutional neural network, one can achieve tagging accuracy comparable with the accuracy of conventional track-based taggers. We argue that the complementary usage of the track-based taggers together with the ones based upon QCD-inspired observables could improve $b$-tagging accuracy.
In the top quark pair production in association with the Higgs boson decaying to a b quark pair t-tbar H (b-bbar), the final state has an irreducible nonresonant background from the production of a top quark pair in association with a b quark pair t-tbar b-bbar. Therefore, understanding of the t-tbar b-bbar process precisely in particular differential cross-section as functions of the properties of the additional b jets not from the top quark decay is essential for improving the sensitivity of a search for the t-tbar H b-bbar process. The two additional b jets can be identified by using variou…
We propose a new method for measuring the top-quark width based on the on-/off-shell ratio of $b$-charge asymmetry in $pp\to Wbj$ production at the LHC. The charge asymmetry removes virtually all backgrounds and related uncertainties, while remaining systematic and theoretical uncertainties can be taken under control by the ratio of cross sections. Limited only by statistical error, in an optimistic scenario, we find that our approach leads to good precision at high integrated luminosity, at a few hundred MeV assuming 300-3000 fb$^{-1}$ at the LHC. The approach directly probes the total width,…
At the Large Hadron Collider, numerous physics processes expected within the standard model and theories beyond it give rise to very high momentum particles decaying to multihadronic final states. Development of algorithms for efficient identification of such "boosted" particles while rejecting the background from multihadron jets from light quarks and gluons can greatly aid in the sensitivity of measurements and new particle searches. This paper presents a new method for identifying boosted high-mass particles using event shapes in Lorentz-boosted reference frames. Variables calculated in the…
We investigate full off-shell effects in $t\bar{t}b\bar{b}$ production in the dilepton channel at the LHC with the center-of-mass energy $\sqrt{s} = 13$ TeV. Specifically, we compute NLO QCD corrections to the $pp \to e^+ ν_e μ^- \barν_μb \bar{b} b \bar{b} + X$ process and provide a prescription for $b$-jet identification to distinguish prompt $b$ jets from $b$ jets originating from the decay of the top quarks. As an important irreducible background to $pp \to t\bar{t}H (H\to b\bar{b})$, $t\bar{t}$ production in association with two prompt $b$ jets is a primary source of uncertainty in the mea…
We introduce a new jet observable {\em zest} defined on exclusively constructed jets and study its potential to discriminate jets originated from Standard Model heavy particles like $W,~Z$ bosons and top quark from gluon initiated jets. Zest exhibits properties such as boost invariance, stability against global color exchange among partons, and inclusion or exclusion of a few soft particles in the jet. We also observe that for gluon jets, zest distribution is mostly insensitive to the jet mass. These properties make zest a suitable candidate for vetoing gluon jets at the colliders. Zest when u…
This Letter presents a study of the reconstruction and identification of $H\to WW^*$ with high transverse momentum, where both $W^{(*)}$ bosons decay hadronically. We show that the boosted $H\to WW^*$ can be effectively reconstructed as a single jet and identified using jet substructures in the center-of-mass frame of the jet. Such a reconstruction and identification approach can discriminate the boosted $H\to WW^*$ in the full hadronic final state from QCD jets. This result will significantly improve experimental sensitivities of searches for potential new physics phenomena beyond the standar…
Following on our earlier work on leading-logarithmic (LLR) resummations for the properties of jets with a small radius, R, we here examine the phenomenological considerations for the inclusive jet spectrum. We discuss how to match the NLO predictions with small-R resummation. As part of the study we propose a new, physically-inspired prescription for fixed-order predictions and their uncertainties. We investigate the R-dependent part of the next-to-next-to-leading order (NNLO) corrections, which is found to be substantial, and comment on the implications for scale choices in inclusive jet calc…
We propose a method to identify jets consisting of all the visible remnants of boosted top particles when these decay semileptonically to electrons. Within these jets, the electron shower overlaps with the shower initiated by the $b$ quark, which makes the identification of the electron hard. Even if an electron inside a jet is identified, it is difficult to pinpoint whether the electron rich jet is indeed due to top quark decay or not, since the invisible neutrino carries away a nontrivial part of the energy-momentum of the original top quark. Broadly speaking, the method proposed here has th…
This paper presents a novel method of searching for boosted hadronically decaying objects by treating them as anomalous elements of a contaminated dataset. A Variational Recurrent Neural Network (VRNN) is used to model jets as sequences of constituent four-vectors. After applying a pre-processing method which boosts each jet to the same reference mass and energy, the VRNN provides each jet an Anomaly Score that distinguishes between the structure of signal and background jets. The model is trained in an entirely unsupervised setting and without high level variables, making the score more robus…
We establish the possibility of having a pseudo-Nambu-Goldstone boson (pNGB) Dark Matter (DM) candidate in the inspired Froggatt-Nielsen Singlet Model (iFNSM) wherein a direct connection exists between the DM mass and new flavon symmetry-breaking scale. We find a considerable allowed region of parameter space for the ensuing pseudoscalar DM, which is dependent upon the flavon Vacuum Expectation Value (VEV) and Yukawa couplings, over which it may be possible to explain the fermion mass hierarchy. Finally, we choose a Benchmark Point (BP) and perform detailed collider analyses to probe this DM s…
An important aspect of the study of Quark-Gluon Plasma (QGP) in ultra-relativistic collisions of heavy ions is the ability to identify, in experimental data, a subset of the jets that were strongly modified by the interaction with the QGP. In this work, we propose studying deep learning techniques for this purpose. Samples of $Z+$jet events were simulated in vacuum and medium and used to train deep neural networks with the objective of discriminating between medium- and vacuum-like jets. Dedicated Convolutional Neural Networks, Dense Neural Networks and Recurrent Neural Networks were developed…
We investigate the performance of a jet identification algorithm based on interaction networks (JEDI-net) to identify all-hadronic decays of high-momentum heavy particles produced at the LHC and distinguish them from ordinary jets originating from the hadronization of quarks and gluons. The jet dynamics are described as a set of one-to-one interactions between the jet constituents. Based on a representation learned from these interactions, the jet is associated to one of the considered categories. Unlike other architectures, the JEDI-net models achieve their performance without special handlin…
Jet identification tools are crucial for new physics searches at the LHC and at future colliders. We introduce the concept of Mass Unspecific Supervised Tagging (MUST) which relies on considering both jet mass and transverse momentum varying over wide ranges as input variables - together with jet substructure observables - of a multivariate tool. This approach not only provides a single efficient tagger for arbitrary ranges of jet mass and transverse momentum, but also an optimal solution for the mass correlation problem inherent to current taggers. By training neural networks, we build MUST-i…
Multiplicity distributions in QCD jets and jet topics
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Fudan University（复旦大学现代物理研究所核物理与离子束应用教育部重点实验室）；Shanghai Research Center for Theoretical Nuclear Physics, NSFC and Fudan University（国家自然科学基金委与复旦大学理论物理上海研究中心）；Instituto Galego de Física de Altas Enerxías IGFAE, Universidade de Santiago de Compostela（圣地亚哥德孔波斯特拉大学加利西亚高能物理研究所）；Axencia Galega de Innovación (GAIN), Xunta de Galicia（加利西亚自治区创新署）
We present a new observable zest and demonstrate its potential to differentiate between jets originated by gluons, top quark and vector bosons. Zest has salient properties such as boost invariance, stability against global color flow of partons and inclusion or exclusion of a few soft particles to the jet. For a gluon jet, zest distribution is also insensitive to the jet mass. We show that when zest is used in conjunction with other observables, it can yield high gluon rejection while retaining high signal sample.
Inspired by direct and indirect maximal center gauge methods which identify vortices in lattice calculations, and by using the connection formalism, we show that under some appropriate gauge transformations, vortices and chains appear in the continuum limit of QCD vacuum.
Discriminating between quark- and gluon-initiated jets has long been a central focus of jet substructure, leading to the introduction of numerous observables and calculations to high perturbative accuracy. At the same time, there have been many attempts to fully exploit the jet radiation pattern using tools from statistics and machine learning. We propose a new approach that combines a deep analytic understanding of jet substructure with the optimality promised by machine learning and statistics. After specifying an approximation to the full emission phase space, we show how to construct the o…
We introduce a new 'quantile' analysis strategy to study the modification of jets as they traverse through a droplet of quark-gluon plasma. To date, most jet modification studies have been based on comparing the jet properties measured in heavy-ion collisions to a proton-proton baseline at the same reconstructed jet transverse momentum ($p_T$). It is well known, however, that the quenching of jets from their interaction with the medium leads to a migration of jets from higher to lower $p_T$, making it challenging to directly infer the degree and mechanism of jet energy loss. Our proposed quant…
The sensitivity of top quark pair production at the Large Hadron Collider to the presence and nature of an underlying Z' boson is studied, accounting for six-fermion decay with full tree-level Standard Model ttbar interference and all intermediate particles allowed off-shell. Focus is placed on the lepton-plus-jets final state, emulating experimental conditions, including kinematic requirements and top quark pair reconstruction in the presence of missing transverse energy and combinatorial ambiguity in jet-top assignment. Considering a resonance with mass of 4 TeV, and assuming 300 inverse fb …
Generalised Dynamic Radius Jets for Robust Collider Analyses
Jožef Stefan Institute（约瑟夫·斯特凡研究所）；The Institute of Mathematical Sciences（数学科学研究所）；Indian Institute of Science Education and Research Kolkata（印度教育研究科学院加尔各答分校）
We present a novel approach to construct a color tagger, i.e. an observable that is able to discriminate the decay of a color-singlet into two jets from a two-jet background in a different color configuration. We do this by explicitly taking the ratio of the corresponding leading-order matrix elements in the soft limit, thus obtaining an observable that is provably optimal within our approximation. We call this observable the "jet color ring" and we compare its performance to other color-sensitive observables such as jet pull and dipolarity. We also assess the performance of the jet color ring…
Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach
Department of Physics, Sinop University（锡诺普大学物理系）；Institute for Quantum Materials and Technologies, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院量子材料与技术研究所）
In this work, we continue our exploration of TeV-scale vector-like fermion signatures inspired by a Grand Unification scenario based on the trinification gauge group. A particular focus is given to pair-production topologies of vector-like quarks (VLQs) at the LHC, in a multi-jet plus a charged lepton and a missing energy signature. We employ Deep Learning methods and techniques based in evolutive algorithms that optimize hyper-parameters in the neural network construction, whose objective is to maximise the Asimov estimate for distinct VLQ masses. In this article, we consider the implications…
