Tagging jets of strongly interacting particles initiated by energetic strange quarks is one of the few largely unexplored Standard Model object classification problems remaining in high energy collider physics. In this paper we investigate the purest version of this classification problem in the form of distinguishing strange-quark jets from down-quark jets. Our strategy relies on the fact that a strange-quark jet contains on average a higher ratio of neutral kaon energy to neutral pion energy than does a down-quark jet. Long-lived neutral kaons deposit energy mainly in the hadronic calorimeter of a high energy detector, while neutral pions decay promptly to photons that deposit energy mainly in the electromagnetic calorimeter. In addition, short-lived neutral kaons that decay in flight to charged pion pairs can be identified as a secondary vertex in the inner tracking system. Using these handles we study different approaches to distinguishing strange-quark from down-quark jets, including single variable cut-based methods, a boosted decision tree (BDT) with a small number of simple variables, and a deep learning convolutional neural network (CNN) architecture with jet images. We show that modest gains are possible from the CNN compared with the BDT or a single variable. Starting from jet samples with only strange-quark and down-quark jets, the CNN algorithm can improve the strange to down ratio by a factor of roughly 2 for strange tagging efficiencies below 0.2, and by a factor of 2.5 for strange tagging efficiencies near 0.02.
We propose a method to probe the coupling of the Higgs to strange quarks by tagging strange jets at future lepton colliders. For this purpose we describe a jet-flavor observable, $J_F$, that is correlated with the flavor of the quark associated with the hard part of the jet. Using this variable, we set up a strangeness tagger aimed at studying the decay $h\to s\bar{s}$. We determine the sensitivity of our method to the strange Yukawa coupling, and find it to be of the order of the standard-model expectation.
The Cabibbo-Kobayashi-Maskawa (CKM) element $V_{ts}$, representing the coupling between the top and strange quarks, is currently best determined through fits based on the unitarity of the CKM matrix, and measured indirectly through box-diagram oscillations, and loop-mediated rare decays of the $B$ or $K$ mesons. It has been previously proposed to use the tree level decay of the $t$ quark to the $s$ quark to determine $|V_{ts}|$ at the LHC, which has become a top factory. In this paper, we extend the proposal by performing a detailed analysis of measuring $t \to sW$ in dileptonic $t\bar{t}$ eve…
We present a new technique for tagging heavy-flavor jets with p_T > 500 GeV called "mu_x tagging." Current track-based methods of b-jet tagging lose efficiency and experience a large rise in fake rate in the boosted regime. Using muons from B hadron decay, we combine angular information and jet substructure to tag b jets, c jets, light jets, and "light-heavy" jets (those containing B hadrons from gluon splitting). We find tagging efficiencies of epsilon_b = 14%, epsilon_c = 6.5%, epsilon_{light-light} = 0.14%, and epsilon_{light-heavy} = 0.5%, respectively, that are nearly independent of trans…
I present a new scheme for tagging boosted heavy flavor jets called "$μ_x$ tagging" and its application to TeV-scale physics beyond the Standard Model. Using muons from B hadron decay to define a particular combination "x" of angular information, and jet substructure variables, we identify a clean ($ε_{\mathrm{fake}}/ε_b\sim 1/100$) good efficiency ($ε_b = 14\%$) tag. I demonstrate the usefulness of this new scheme by showing the reach for discovery of leptophobic $Z^\prime\to b\bar b$ and $tH^\pm\to t t b$.
We present a new scheme for tagging high-$p_{T}$ bottom and charm jets using energetic muons. Contemporary track-based $b$ tags lose their ability to reject light jet background as jet $p_{T}\rightarrow\mathcal{O}(\mathrm{TeV})$, where the massive boost exposes fundamental limits in tracking resolution. For our "$μ_{x}$" tag, the signal efficiency and light jet rejection is robust versus $p_{T}$. In the tested regime (jet $p_{T}\in[\mathrm{0.5,2.1}]$ TeV), $μ_{x}$ tags $\sim14\%$ of $b$ jets, $\sim6.5\%$ of $c$ jets and $\sim0.65\%$ of light jets. Since $μ_{x}$ tagging should be immediately us…
Convolutional neural networks are basic structures using jet images as input for the jet tagging problems. However, what they have learned during the training process is always difficult to understand just through feature maps. Inspired by the attention mechanism popular in machine learning fields, we propose a novel attention-based neural network (ABNN) to get insight of this problem. The ABNN combines a jet image with average jet images from the signal and the background to generate attention maps which show clearly the relevant importance according to the different origination of jets. Comp…
Deep learning methods have been increasingly adopted to study jets in particle physics. Since symmetry-preserving behavior has been shown to be an important factor for improving the performance of deep learning in many applications, Lorentz group equivariance - a fundamental spacetime symmetry for elementary particles - has recently been incorporated into a deep learning model for jet tagging. However, the design is computationally costly due to the analytic construction of high-order tensors. In this article, we introduce LorentzNet, a new symmetry-preserving deep learning model for jet taggi…
We consider the process $p p \to t {\bar t} H$. This process can give rise to many signatures of the Higgs boson. The signatures can have electrons, muons and jets. We consider the signatures that have two electrons/muons and jets. Tagging of a tau jet and a bottom jet can help reduce the backgrounds significantly. In particular, we examine the usefulness of the signatures "isolated 2 electrons/muons + a bottom jet + a tau jet", "isolated 2 electrons/muons + 2 tau jets", "isolated 2 electrons/muons + 2 bottom jets + a tau jet", and "isolated 2 electrons/muons + a bottom jet + 2 tau jets". We f…
We introduce a novel anomaly search method based on (i) jet tagging to select interesting events, which are less likely to be produced by background processes; (ii) comparison of the untagged and tagged samples to single out features (such as bumps produced by the decay of new particles) in the latter. We demonstrate the usefulness of this method by applying it to a final state with two massive boosted jets: for the new physics benchmarks considered, the signal significance increases an order of magnitude, up to a factor of 40. We compare to other anomaly detection methods in the literature an…
Jet tagging has become an essential tool for new physics searches at the high-energy frontier. For jets that contain energetic charged leptons we introduce Feature Extended Supervised Tagging (FEST) which, in addition to jet substructure, considers the features of the charged lepton within the jet. With this method we build dedicated taggers to discriminate among boosted $H \to \ell νq \bar q$, $t \to \ell νb$, and QCD jets (with $\ell$ an electron or muon). The taggers have an impressive performance, allowing for overall light jet rejection factors of $10^4-10^5$, for top quark / Higgs boson …
Jet flavour identification algorithms are of paramount importance to maximise the physics potential of future collider experiments. This work describes a novel set of tools allowing for a realistic simulation and reconstruction of particle level observables that are necessary ingredients to jet flavour identification. An algorithm for reconstructing the track parameters and covariance matrix of charged particles for an arbitrary tracking sub-detector geometries has been developed. Additional modules allowing for particle identification using time-of-flight and ionizing energy loss information …
We present a new tagger which aims at identifying partially reconstructed objects, in which only some of the constituents are collected in a single jet. As an example, we focus on top decays in which either part of the hadronically decaying W or the b jet is soft or falls outside of the top jet cone. We construct an observable to identify remnant substructure from the decay and employ aggressive jet grooming to reject QCD backgrounds. The tagger is complementary to existing ones and works well in the intermediate boost regime where jet substructure techniques usually fail. It is anticipated th…
We initiate the study of the time substructure of jets, motivated by the fact that the next generation of detectors at particle colliders will resolve the time scale over which jet constituents arrive. This effect is directly related to hadronization, which transforms partons into massive hadrons with a distribution of velocities. We review the basic predictions for the velocity distribution of jet hadrons, and suggest an application for this information in the context of boosted object tagging. By noting that the velocity distribution is determined by the properties of the color string which …
A method is proposed for distinguishing highly boosted hadronically decaying W's (W-jets) from QCD-jets using jet substructure. Previous methods, such as the filtering/mass-drop method, can give a factor of ~2 improvement in S/sqrt(B) for jet pT > 200 GeV. In contrast, a multivariate approach including new discriminants such as R-cores, which characterize the shape of the W-jet, subjet planar flow, and grooming-sensitivities is shown to provide a much larger factor of ~5 improvement in S/sqrt(B). For longitudinally polarized W's, such as those coming from many new physics models, the discrimin…
The separation of quark and gluon initiated jets can be an important way to improve the sensitivity in searches for new physics or in measurements of Higgs boson properties. We present a simplified version of the shower deconstruction approach as a novel observable for quark-gluon tagging. Assuming topocluster-like objects as input, we compare our observable with energy correlation functions and find a favorable performance for a large variety of jet definitions. When applied to dark matter searches in mono-jet final states limitations from small signal-to-background ratios can be overcome. We…
The main parts of the LHC diffractive physics programme possible to be measured using a proton tagging technique are presented. The geometric acceptance of the ATLAS forward proton detectors: ALFA and AFP for various LHC optics settings are shown. The probabilities of observing a proton originating from a minimum-bias event in ALFA and AFP stations are given. The main properties of single diffractive and double Pomeron exchange production of dijets, photon+jet, jet-gap-jet and W/Z bosons are discussed. The possibility of measuring the jet production in exclusive (double proton tag) and semi-ex…
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…
Heavy flavour jet tagging is widely used in the determination of cross sections including the production of heavy flavoured quarks. This requires the knowledge of heavy and light flavour jet tagging efficiencies and their uncertainties. A system of eight non-linear equations can be used to determine these quantities by means of two different tagging algorithms and two data sets which differ in heavy flavour jet content. The analytical solution of this system of equations, derived by means of resultants is described in detail, including a discussion about its singularities which provide importa…
We study the production of an electroweak boson in association with jets, in processes where the jet with the highest transverse momentum is identified as quark-initiated. The quark/gluon tagging procedure is realised by a cut on a jet angularity and it is therefore theoretically well-defined and exhibits infrared and collinear safety. In this context, exploiting resummed perturbation theory, we are able to provide theoretical predictions for transverse momentum distributions at a well-defined and, in principle, systematically improvable accuracy. In particular, tagging the leading jet as quar…
We propose a novel method in that quark-gluon tagging of the jets emitted as initial state radiation (ISR) can boost searches of invisible Higgs from gluon fusion processes against irreducible electroweak vector boson productions. While quark ISR typically takes up a dominant portion than gluon in the background processes mainly by frequent quark-gluon initiated hard scatterings at the LHC, gluon ISR portion in the gluon fusion can be significantly larger in the central region of detector. Focusing on invisible Higgs searches using jet substructure variables capturing the new features, we demo…
University of California, Santa Barbara（加州大学圣巴巴拉分校）；CERN（欧洲核子研究组织）
How to represent a jet is at the core of machine learning on jet physics. Inspired by the notion of point clouds, we propose a new approach that considers a jet as an unordered set of its constituent particles, effectively a "particle cloud". Such a particle cloud representation of jets is efficient in incorporating raw information of jets and also explicitly respects the permutation symmetry. Based on the particle cloud representation, we propose ParticleNet, a customized neural network architecture using Dynamic Graph Convolutional Neural Network for jet tagging problems. The ParticleNet arc…
We introduce a novel approach to jet tagging and classification through the use of techniques inspired by computer vision. Drawing parallels to the problem of facial recognition in images, we define a jet-image using calorimeter towers as the elements of the image and establish jet-image preprocessing methods. For the jet-image processing step, we develop a discriminant for classifying the jet-images derived using Fisher discriminant analysis. The effectiveness of the technique is shown within the context of identifying boosted hadronic W boson decays with respect to a background of quark- and…
The identification of b jets is a crucial issue to study and characterize various channels like top quark events and many new physics scenarios. Different b-tagging techniques are defined in CMS which benefit from the long life time, high mass and large momentum fraction of the b-hadron produced in b-quark jet. Effcient algorithms have been developed based on the measure of b-hadron secondary vertex or on tracks with a large impact parameter. Data collected in pp collisions at 7TeV in 2011 are used to estimate both the b-tagging effciency and the mistag rate from light flavor jets.
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 …
We introduce a method to discover the Higgs boson at the Large Hadron Collider (LHC) through its decay to W^+W^-, where one boson decays to leptons, and the other decays to c+jet. This mechanism is complementary to the decay into dileptons, but has the potential to measure the invariant mass peak of the Higgs boson, and to avoid large recently discovered QCD backgrounds from heavy flavor decays. In addition, this mechanism motivates the study and creation of a dedicated charm jet tagger at LHC experiments. Existing charm jet tagging, in the form of fakes to bottom jet tagging, provides sensiti…
We describe a new hit-based $b$-tagging technique for high energy jets and study its performance with a Geant4-based simulation. The technique uses the fact that at sufficiently high energy a B meson or baryon can live long enough to traverse the inner layers of pixel detectors such as those in the ATLAS, ALICE, or CMS experiments prior to decay. By first defining a "jet" via the calorimeter, and then counting hits within that jet between pixel layers at increasing radii, we show it is possible to identify jets that contain $b$-quarks by detecting a jump in the number of hits. We show that the…
We demonstrate that the classification of boosted, hadronically-decaying weak gauge bosons can be significantly improved over traditional cut-based and BDT-based methods using deep learning and the jet charge variable. We construct binary taggers for $W^+$ vs. $W^-$ and $Z$ vs. $W$ discrimination, as well as an overall ternary classifier for $W^+$/$W^-$/$Z$ discrimination. Besides a simple convolutional neural network (CNN), we also explore a composite of two CNNs, with different numbers of layers in the jet $p_{T}$ and jet charge channels. We find that this novel structure boosts the performa…
We study the boosted Higgs tagging using the Lund jet plane. The convolutional neural network is used for the Lund images data set to classify hadronically decaying Higgs from the QCD background. We consider $H\to b \bar{b}$ and $H \to gg$ decay for moderate and high Higgs transverse momentum and compare the performance with the cut based approach using the jet color ring observable. The approach using Lund plane images provides good tagging efficiency for all the cases.
For highly energetic top quarks, the products of the decay t->bqq' are collimated. The 3-prong decay structure can no longer be resolved using calorimeter information alone if the particle jet separation approaches the calorimeter granularity. We propose a new method, the HPTTopTagger, that uses tracks of charged particles inside a fat jet to find top quarks with transverse momentum pT >1 TeV. The tracking information is complemented by the calorimeter measurement of the fat jet energy to eliminate the sensitivity to jet-to-jet fluctuations in the charged-to-neutral particle ratio. We show tha…
Searches for invisible Higgs decays in weak boson fusion are a well-known laboratory for jets and QCD studies. We present a series of results on tagging jets and central jet activity. First, precision analyses of the central jet activity require full control of single top production in some analyses. Second, the rate dependence on the size of the tagging jets is not limited to weak boson fusion. For the first time, we show how subjet information on the tagging jets and on the additional jet activity can be used to extract the Higgs signal. The additional observables relieve some of the pressur…
New TeV-scale physics processes at the LHC can produce Higgs bosons with substantive transverse Lorentz boost, such that the Higgs's decay products are nominally contained in a single jet. In the case of a light Higgs decaying predominantly to bb, previous studies have shown that these Higgs-jets can be identified by capitalizing on jet substructure techniques. In this work, we explore the possibility of also utilizing the subdominant but very distinctive decay h -> tau tau. To this end, we introduce the concept of a ``ditau-jet,'' or a jet consisting of two semi-collinear taus where one or bo…
A new jet observable, dipolarity, is introduced that can distinguish whether a pair of subjets arises from a color singlet source. This observable is incorporated into the HEPTopTagger and is shown to improve discrimination between top jets and QCD jets for moderate to high pT.
After the recent discovery of a 125 GeV Higgs-like particle at the Large Hadron Collider (LHC), it is crucial to examine its role in unitarizing high energy W_LW_L scattering, which may reveal its possible deviation from a Standard Model Higgs. We perform an updated study on WW scattering in the semileptonic channel at the LHC, improved by the recently developed W jet tagging method. The resultant statistical significance of a Strongly-Interacting Light Higgs (SILH) model is about 20% larger than that based on the conventionally "gold-plated" dileptonic channel, while 200% more signal events a…
Being able to distinguish light-quark jets from gluon jets on an event-by-event basis could significantly enhance the reach for many new physics searches at the Large Hadron Collider. Through an exhaustive search of existing and novel jet substructure observables, we find that a multivariate approach can filter out over 95% of the gluon jets while keeping more than half of the light-quark jets. Moreover, a combination of two simple variables, the charge track multiplicity and the $p_T$-weighted linear radial moment (girth), can achieve similar results. While this pair appears very promising, o…
Jet flavor tagging with Particle Transformer for Higgs factories
International Center for Elementary Particle Physics, The University of Tokyo（东京大学基础粒子物理国际中心）；Department of Physics, Graduate School of Science, The University of Tokyo（东京大学理学研究科物理学系）；MI-6 Ltd.（MI-6有限公司）
We introduce a jet tagger based on a neural network analyzing the Minkowski Functionals (MFs) of pixellated jet images. The MFs are geometric measures of binary images, and they can be regarded as a generalization of the particle multiplicity, which is an important quantity in jet tagging. Their changes by dilation encode the jet constituents' geometric structures that appear at various angular scales. We explicitly show that this analysis using the MFs together with mathematical morphology can be considered a constrained convolutional neural network (CNN). Conversely, CNN could model the MFs …
The signature produced by the Standard Model Higgs boson in the Vector Boson Fusion (VBF) mechanism is usually pinpointed by requiring two well separated hadronic jets, one of which (at least) of them tends to be in the forward direction. With the increase of instantaneous luminosity at the LHC, the isolation of the Higgs boson produced with the VBF mechanism is rendered more challenging. In this paper the feasibility of single jet tagging is explored in a high-luminosity scenario. It is demonstrated that the separation in rapidity between the tagging jet and the Higgs boson can be effectively…
We study the problem of distinguishing $b$-jets stemming from the decay of a colour singlet, such as the Higgs boson, from those originating from the abundant QCD background. In particular, as a case study, we focus on associate production of a vector boson and a Higgs boson decaying into a pair of $b$-jets, which has been recently observed at the LHC. We consider the combination of several theory-driven observables proposed in the literature, together with Lund jet plane images, in order to design an original $Hbb$ tagger. The observables are combined by means of standard machine learning alg…
Semivisible jets are a characteristic signature of many confining dark sectors and consist of jets of visible hadrons intermixed with invisible stable particles. Since their initial proposal, considerable progress has been made in developing techniques for tagging anomalous jets. In this paper, we show that the ability to tag semivisible jets can be used to define new event-level variables which use generally ignored kinematic information and can considerably increase our ability to discover dark confining sectors. In practice, our best results are obtained by using the coefficients of the dec…
Mila — Quebec Artificial Intelligence Institute（米拉——魁北克人工智能研究所）；Université de Montréal（蒙特利尔大学）
We leverage representation learning and the inductive bias in neural-net-based Standard Model jet classification tasks, to detect non-QCD signal jets. In establishing the framework for classification-based anomaly detection in jet physics, we demonstrate that, with a \emph{well-calibrated} and \emph{powerful enough feature extractor}, a well-trained \emph{mass-decorrelated} supervised Standard Model neural jet classifier can serve as a strong generic anti-QCD jet tagger for effectively reducing the QCD background. Imposing \emph{data-augmented} mass-invariance (and thus decoupling the dominant…
We introduce the energy flow polynomials: a complete set of jet substructure observables which form a discrete linear basis for all infrared- and collinear-safe observables. Energy flow polynomials are multiparticle energy correlators with specific angular structures that are a direct consequence of infrared and collinear safety. We establish a powerful graph-theoretic representation of the energy flow polynomials which allows us to design efficient algorithms for their computation. Many common jet observables are exact linear combinations of energy flow polynomials, and we demonstrate the lin…
A method of top tagging is introduced. Using the anti-kt algorithm to define jets, events with nj = 2 fat jets of cone size R = 1.5 are decomposed into R = 0.6 sub-jets and retained if nj (R= 0.6) \geq 4 . One pair of sub-jets reconstructs the W-mass and another jet is tagged as a b-jet, as necessary for hadronic or semileptonic events of tt origin. This 'hollow cone' method distinguishes the tt events from the light parton QCD dijet events. Our simulations are made for the LHC at 7 TeV.
