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At least 19 records

Identifying quenched jets in heavy ion collisions with machine learning

Measurements of jet substructure in ultra-relativistic heavy ion collisions suggest that the jet showering process is modified by the interaction with the quark-gluon plasma. Modifications of the hard substructure of jets can be explored with modern data-driven techniques. In this study, a machine learning approach to the identification of quenched jets is designed. Jet showering processes are simulated with a jet quenching model JEWEL and a non-quenching model PYTHIA 8. Sequential substructure variables are extracted from the jet clustering history following an angular-ordered sequence and are used in the training of a neural network built on top of a long short-term memory network. We show that this approach successfully identifies the quenching effect in the presence of the large uncorrelated background of soft particles created in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enhanced signal of momentum broadening in hard splittings for $γ$-tagged jets in a multistage approach

We investigate medium-induced modifications to jet substructure observables that characterize hard splitting patterns in central Pb-Pb collisions at the top energy of the Large Hadron Collider (LHC). Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and $γ$-tagged jets. The results show that quark jets undergo a non-monotonic modification compared to gluon jets in observables such as the Pb-Pb to $p$-$p$ ratio of the Soft Drop prong angle $r_g$, the relative prong transverse momentum $k_{T,g}$ and the groomed mass $m_g$ distributions. Due to this non-monotonic modification, $γ$-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. This work highlights the potential of hard substructures in $γ$-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions. All simulations for $γ$-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.

FOS: Physical sciences↗

Effect of recoils on soft-drop-groomed observables in 𝛾-tagged jets in a multistage approach

We investigate medium-induced modifications to jet substructure observables that characterize hard components in central Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV. Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and 𝛾-tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to 𝑝−𝑝 ratio of the soft drop prong angle 𝑟 𝑔 , the relative prong transverse momentum 𝑘 𝑇,𝑔 , and the groomed mass 𝑚 𝑔 distributions. Due to this nonmonotonic modification, 𝛾-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. Further systematic studies demonstrate that these effects are dominated by recoil medium response. This work highlights the potential of hard substructures in 𝛾-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions, in particular by enabling detailed investigations of jet-medium parton scatterings via their associated medium response. All simulations for 𝛾-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Linear Boltzmann transport for jet propagation in the quark-gluon plasma: Inelastic processes and jet modification

A linear Boltzmann transport (LBT) Monte Carlo model has been developed to describe jet propagation and interaction with the quark-gluon plasma (QGP) in relativistic heavy-ion collisions. A complete set of elastic-scattering processes and medium-induced gluon emissions based on the higher-twist formalism are incorporated for both jet shower and medium recoil partons. It has been employed to describe experimental data on large transverse momentum hadron and jet spectra, correlation and jet substructures in high-energy heavy-ion collisions. Here, we document in detail the structure of the model and validation of the Monte Carlo implementations of the physics processes in LBT, in particular, the inelastic process of medium-induced gluon radiation. We carry out a comprehensive examination of the jet-medium interaction as implemented in LBT through energy loss and momentum broadening of a single hard parton, the energy and transverse momentum transfer from leading partons to medium-induced gluons and jet-induced medium excitation, and medium modification of reconstructed jets in a static and uniform medium. With realistic and event-by-event hydrodynamic medium in heavy-ion collisions, we compute and compare with experimental data on the jet cone-size dependence of the single inclusive jet suppression at both the BNL Relativistic Heavy-Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC), the dijet asymmetry at the LHC and γ-jet correlation at RHIC. Effects of medium-induced gluon emissions and jet-induced medium excitation on jet observables are systematically examined. Rescatterings of the radiated gluons and recoil partons with the QGP are found essential to account for the enhancement of soft particle yield toward the edge of the jet cone.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Search for Quasiparticle Scattering in the Quark-Gluon Plasma with Jet Splittings in 𝑝⁢𝑝 and Pb-Pb Collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The ALICE Collaboration reports measurements of the large relative transverse momentum (𝑘 𝑇 ) component of jet substructure in 𝑝⁢𝑝 and Pb-Pb collisions at center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV. Enhancement in the yield of such large-𝑘 T emissions in head-on Pb-Pb collisions is predicted to arise from partonic scattering with quasiparticles of the quark-gluon plasma. The analysis utilizes charged-particle jets reconstructed by the anti-𝑘 T algorithm with resolution parameter 𝑅 = 0.2 in the transverse-momentum interval 60 < 𝑝 T,ch,jet < 80 GeV/𝑐. The soft drop and dynamical grooming algorithms are used to identify high transverse momentum splittings in the jet shower. Comparison of measurements in Pb-Pb and 𝑝⁢𝑝 collisions shows medium-induced narrowing, corresponding to yield suppression of high-𝑘 𝑇 splittings, in contrast to the expectation of yield enhancement due to quasiparticle scattering. The measurements are compared to theoretical model calculations incorporating jet modification due to jet-medium interactions (“jet quenching”), both with and without quasiparticle scattering effects. These measurements provide new insight into the underlying mechanisms and theoretical modeling of jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Probing the Short-Distance Structure of the Quark-Gluon Plasma with Energy Correlators

Energy-energy correlators (EECs) are promising observables to study the dynamics of jet evolution in the quark-gluon plasma (QGP) through its imprint on angular scales in the energy flux of final-state particles. We carry out the first complete calculation of EECs using realistic simulations of high-energy heavy-ion collisions and dissect the different dynamics underlying the final distribution through analyses of jet propagation in a uniform medium. The EECs of γ -jets in heavy-ion collisions are found to be enhanced by the medium response from elastic scatterings instead of induced gluon radiation at large angles. In the meantime, EECs are suppressed at small angles due to energy loss and transverse momentum broadening of jet shower partons. These modifications are further shown to be sensitive to the angular scale of the in-medium interaction, as characterized by the Debye screening mass. Experimental verification and measurement of such modifications will shed light on this scale and the short-distance structure of the QGP in heavy-ion collisions. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Semi-visible jets + X: illuminating dark showers with radiation

We investigate the potential to search for semi-visible jets (SVJs) at the Large Hadron Collider (LHC) using initial-state radiation (ISR). Both photon ISR and jet ISR channels are considered, using a benchmark signal model with the decay of a leptophobic Z$^{′}$ mediator forming two SVJs. We compare and extend several techniques to decompose the missing transverse momentum into per-jet contributions, in order to reconstruct the mediator mass and to define a new observable measuring the fraction of invisible dark hadrons. The presence of ISR facilitates the identification of the SVJs, and the resulting boost improves the resolution of the observables, especially for models with high invisible fractions. We combine the two observables to propose a complete search strategy and discuss an extension of the strategy to probe the whole model parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

How to understand limitations of generative networks

Well-trained classifiers and their complete weight distributions provide us with a well-motivated and practicable method to test generative networks in particle physics. We illustrate their benefits for distribution-shifted jets, calorimeter showers, and reconstruction-level events. In all cases, the classifier weights make for a powerful test of the generative network, identify potential problems in the density estimation, relate them to the underlying physics, and tie in with a comprehensive precision and uncertainty treatment for generative networks.

Physics↗

Reconstruction of boosted and resolved multi-Higgs-boson events with symmetry-preserving attention networks

The production of multiple Higgs bosons at the CERN LHC provides a direct way to measure the trilinear and quartic Higgs self-interaction strengths as well as potential access to beyond the standard model effects that can enhance production at large transverse momentum p T . The largest event fraction arises from the fully hadronic final state in which every Higgs boson decays to a bottom quark-antiquark pair ($b\bar{b}$). This introduces a combinatorial challenge known as the jet assignment problem: assigning jets to sets representing Higgs boson candidates. Symmetry-preserving attention networks (SPA-Nets) have been developed to address this challenge. However, the complexity of jet assignment increases when simultaneously considering both H → $b\bar{b}$ reconstruction possibilities, i.e., two “resolved” small-radius jets each containing a shower initiated by a b quark or one “boosted” large-radius jet containing a merged shower initiated by a $b\bar{b}$ pair. The latter improves the reconstruction efficiency at high p T . In this work, we introduce a generalization to the SPA-Net approach to simultaneously consider both boosted and resolved reconstruction possibilities and unambiguously interpret an event as “fully resolved”, “fully boosted”, or in between. We report the performance of baseline methods, the original SPA-Net approach, and our generalized version on nonresonant HH and HHH production at the LHC. Considering both boosted and resolved topologies, our SPA-Net approach increases the Higgs boson reconstruction purity by 56–80% and the efficiency by 37–38% compared to the baseline method depending on the final state.

Higgs Production↗

QCD jets in a hot and dense medium: A study of shower formation time and collision kernels

With the use of , a model which considers evolving QCD jets against a fluid dynamical background, it is shown that the introduction of formation time to the parton shower after the initial hard scattering is essential for a simultaneous description of charged hadron and jet R A A . This inclusion also improves jet shape ratios at small angle and jet fragmentation function ratios of leading charged hadrons. The framework is then aimed at a study of the leading-order, next-to-leading-order, and nonperturbative collision kernels. Sizable differences in the modification of jet substructure observables, i.e., jet shape and fragmentation functions, are observed. Such differences are caused by the difference in the radiation rates of relatively soft gluons that survive in the evolution in medium. Published by the American Physical Society 2025

Modarresi-Yazdi, Rouzbeh (ORCID:0000000290377447)↗

Non-relativistic quantum chromodynamics in parton showers

Measurements of quarkonia isolation in jets at the Large Hadron Collider (LHC) have been shown to disagree with fixed-order non-relativistic quantum chromodynamics (NRQCD) calculations, even at higher orders. Calculations using the fragmenting jet function formalism are able to better describe data but cannot provide full event-level predictions. In this work we provide an alternative model via NRQCD production of quarkonia in a timelike parton shower. We include this model in the PYTHIA 8 event generator and validate our parton-shower implementation against analytic forms of the relevant fragmentation functions. Finally, we make inclusive predictions of quarkonia production for the decay of the standard-model Higgs boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

‘Flux+Mutability’: a conditional generative approach to one-class classification and anomaly detection

Abstract Anomaly Detection is becoming increasingly popular within the experimental physics community. At experiments such as the Large Hadron Collider, anomaly detection is growing in interest for finding new physics beyond the Standard Model. This paper details the implementation of a novel Machine Learning architecture, called Flux+Mutability, which combines cutting-edge conditional generative models with clustering algorithms. In the ‘flux’ stage we learn the distribution of a reference class. The ‘mutability’ stage at inference addresses if data significantly deviates from the reference class. We demonstrate the validity of our approach and its connection to multiple problems spanning from one-class classification to anomaly detection. In particular, we apply our method to the isolation of neutral showers in an electromagnetic calorimeter and show its performance in detecting anomalous dijets events from standard QCD background. This approach limits assumptions on the reference sample and remains agnostic to the complementary class of objects of a given problem. We describe the possibility of dynamically generating a reference population and defining selection criteria via quantile cuts. Remarkably this flexible architecture can be deployed for a wide range of problems, and applications like multi-class classification or data quality control are left for further exploration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for Dark Showers from Higgs Boson Decays Through the Photon Portal

One of the primary goals of the CMS detector is to find particles beyond the standard model. We present a search for dark showers produced from decays of the Higgs boson using collision data from the CMS experiment at the LHC. These dark showers then decay into jets made entirely of photons, which we can observe in the detector. Thus, our analysis focuses on reconstructing and analyzing these jets and maximizing signal selection efficiency for data from the Monte Carlo simulation. The photon signature of dark jets can then be confirmed via an invariant-mass distribution of these two photon jets. If found, these particles would provide evidence of physics theories beyond the Standard Model.

MacMullin, Alexandra [Skidmore Coll.]↗

Modified coherence and the transverse extent of jets

We present a study of the transverse size of parton showers and their diminishing interaction with the medium in the high virtuality stage of jet evolution. We consider the process of a hard quark produced in deep inelastic scattering off a large nucleus. Single gluon radiation from this quark, in the absence of scattering, is rederived using wave packets. This allows for a derivation of the quantum uncertainty size of the hard quark, at the point of splitting. This uncertainty size is then incorporated within a Monte Carlo shower routine yielding transverse shower sizes noticeably larger than the classical antenna size of the shower. No clear relation is found between the full uncertainty size of the shower and the virtuality of the originating parton. The single gluon emission from the hard quark is then reanalyzed for the case of single rescattering off the remainder of the nucleus. A relation is derived between the jet transport coefficient $\hat{𝑞}$ and the gluon Transverse momentum-dependent parton distribution function (gTMDPDF). Solving this relation, for a simple case, clearly demonstrates the weakening of $\hat{𝑞}$ with the virtuality of the hard splitting parton.

jet quenching↗

Deep learning assisted jet tomography for the study of Mach cones in QGP

Abstract Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and gluons traverse the hot medium at a velocity faster than the speed of sound in high-energy heavy-ion collisions. The shape of the Mach cone and the associated diffusion wake are sensitive to the initial jet production location and the propagation direction of the parton shower relative to the radial flow because of the distortion caused by the collective expansion of the QGP and the large density gradient. The shape of jet-induced Mach cones and their distortions in heavy-ion collisions provide a unique and direct probe of the dynamical evolution and the equation of state of QGP. However, it is difficult to identify the Mach cone and the diffusion wake in current experimental measurements of final hadron distributions because they are averaged over all possible initial jet production locations and parton-shower propagation directions. To overcome this difficulty, we develop a deep learning assisted jet tomography which uses the full information of the final hadrons from jets to localize the initial jet production positions. This method can help to constrain the initial regions of jet production in heavy-ion collisions and enable a differential study of Mach-cones with different path lengths and orientations relative to the radial flow of the QGP in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring the universality of hadronic jet classification

The modeling of jet substructure significantly differs between Parton Shower Monte Carlo (PSMC) programs. Despite this, we observe that machine learning classifiers trained on different PSMCs learn nearly the same function. This means that when these classifiers are applied to the same PSMC for testing, they result in nearly the same performance. This classifier universality indicates that a machine learning model trained on one simulation and tested on another simulation (or data) will likely be optimal. Our observations are based on detailed studies of shallow and deep neural networks applied to simulated Lorentz boosted Higgs jet tagging at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

$t\overline{t}b\overline{b}$ at NLO precision in a variable flavor number scheme

Top-quark pair production in association with two $b$-jets is computed at next-to-leading order QCD precision, including effects of the $b$-quark mass, and matched to a $t\overline{t}$+jets simulation in a variable flavor number scheme. The Monte Carlo realization of this method, called fusing, consistently embeds the four-flavor calculation in a particle-level event generator. As a first phenomenological application, we present observables relevant to the data-driven estimation of irreducible backgrounds to $t\overline{t}H$ -production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗