arXiv subjects

Raghav Kunnawalkam Elayavalli

Publications and source records attributed to Raghav Kunnawalkam Elayavalli.

At least 19 recordsLinked to original sources

arXiv2026

Energy-energy correlators inside single inclusive jets in heavy-ion collisions with CoLBT-hydro model

The energy-energy correlator (EEC) inside jets is a sensitive observable for studying jet modification in the quark-gluon plasma (QGP). However, its interpretation in heavy-ion collisions remains challenging, requiring a consistent understanding of jet evolution across multiple dynamical scales together with a proper treatment of the background subtraction. In this work, we employ an updated CoLBT-hydro framework in which a medium scale $Q_M$ = 2.0 GeV is introduced to separate the vacuum and in-medium stages of the parton shower, enabling a more self-consistent treatment of jet evolution. Using a theoretical background subtraction within the model, the resulting simulation reproduces the recent CMS measurement of the in-jet EEC, and through a decomposition of different contributions, highlights the impact of medium modification on the observable. To further validate the experimental procedure, we also implement the CMS mixed-event background-subtraction method directly in the simulation and find the results are consistent with those obtained with the theoretical background subtraction. Using $p_T$-ranked jets in each event, we further investigate the dependence of medium modification on the in-medium path length, reflected in the different EECs of leading and sub-leading jets. Finally, we explore the dependence of the leading-jet EEC on the dijet rapidity gap as a signal of the jet-induced diffusion wake.

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arXiv2025

Living on the edge: radius effects in the angular substructure of heavy-ion jets

Jet substructure observables serve as essential tools for probing the quark-gluon plasma produced in relativistic heavy-ion collisions. Their interpretation, however, is often complicated by edge effects, which arise when correlated particles fall outside the reconstructed jet radius, introducing distortions that obscure the underlying QCD dynamics. In this work, we present a comprehensive phenomenological study of edge effects in soft-insensitive angular observables, taking the two-point energy correlator (EEC) as a representative example. We argue that these distortions scale linearly with the average angular separation between the winner-take-all and $E$-scheme axes $\langle ϕ\rangle$, and validate this behavior across proton-proton (p-p) simulations with Pythia8 and Herwig7, as well as lead-lead (Pb-Pb) simulations using JEWEL and CoLBT. In p-p collisions, edge effects are strongly suppressed, scaling as $(R_L/R)^4$, whereas medium-modified jets can exhibit larger distortions, with contributions scaling as $(R_L/R)^2$ and $(R_L/R)^4$. Taking Pb-Pb/p-p ratios of the EEC substantially reduces, but does not completely eliminate, these distortions, highlighting the need of accounting for edge effects in the interpretation of heavy-ion jet substructure measurements. Since edge effects are largely governed by the $\langle ϕ\rangle$ distribution, studying this distribution provides a new handle for benchmarking and constraining the modeling of edge effects in heavy-ion event generators.

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arXiv2025

Deep Image Reconstruction for Background Subtraction in Heavy-Ion Collisions

Jet reconstruction in an ultra-relativistic heavy-ion collision suffers from a notoriously large, fluctuating thermal background. Traditional background subtraction methods struggle to remove this soft background while preserving the jet's hard substructure. In this Letter, we present DeepSub, the first machine learning-based approach for full-event background subtraction. DeepSub utilizes a model based on Swin Transformer layers to denoise jet images and disentangle hard jets from the heavy-ion background. DeepSub significantly outperforms existing subtraction techniques by reproducing key jet observables such as jet $p_\mathrm{T}$ and mass, and substructure observables such as girth and the energy correlation function, at the sub-percent to percent level. As such, DeepSub paves the way for precision heavy-ion measurements in hitherto inaccessible kinematic regimes.

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arXiv2025

Flavor dependence of Energy-energy correlators

Energy-energy correlators (EECs) within high energy jets serve as a key experimentally accessible quantity to probe the scale and structure of the quark-gluon plasma (QGP) in relativistic heavy-ion collisions. The CMS Collaboration's first measurement of the modification to the EEC within single inclusive jets in Pb+Pb collisions relative to p+p collisions reveals a significant enhancement at small angles, which may arise from jet transverse momentum $p_T$ selection biases due to jet energy loss. We investigate the dependence of jet EECs on the flavor of the initiating parton. The EEC distribution of a gluon jet is broader and the peak of transition from perturbative to non-perturbative regime occurs at a larger angle than a quark jet. Such flavor dependence leads to the different EECs for $γ$-jets and single inclusive jets due to their different flavor composition. It is also responsible for a colliding energy dependence of EECs of single inclusive jets at fixed jet energy. We also investigate the impact of flavor composition variation on the $p_T$ dependence of the jet EEC. We further propose that a change in the gluon jet fraction in A+A collisions compared to p+p can also contribute to a non-negligible enhancement of the medium modified EEC at small angles. Using the \textsc{Jewel} model, we predict the reduction of the gluon jet fraction in A+A collisions and estimate its impact on the EEC.

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arXiv2025

Minimizing Selection Bias in Inclusive Jets in Heavy-Ion Collisions with Energy Correlators

The first-ever measurement of energy correlators within inclusive jets produced in heavy-ion collisions, revealed by the CMS Collaboration, shows a clear enhancement at large angles relative to the proton-proton (p-p) baseline. However, interpreting this enhancement is complicated due to selection bias from energy loss, which also distorts the energy correlator heavy-ion to p-p ratio in the hadronization region, hindering our understanding of parton/hadron dynamics in a colored medium. In this Letter, we introduce a new ratio of energy correlator observables that removes the leading effects of selection bias from the two-point energy correlator spectrum (E2C). Pythia and Herwig simulations show that the impact of selection bias in the E2C is reduced by an order of magnitude, while sensitivity to any other medium modifications is retained. This quantity can be obtained directly from the experimental measurements presented by CMS, as illustrated in the accompanying note.

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arXiv2025

Enhancing charge ratio sensitivity to hadronization effects via jet selections on resolved SoftDrop splitting

The study of Quantum Chromodynamics (QCD) at ultra-relativistic energies can be performed in a controlled environment through lepton-hadron deep inelastic scatterings. In such collisions, the high-energy partonic emissions that follow from the ejected hard partons are accurately described by perturbative QCD. However, the lower energy scales at which quarks and gluons experience colour confinement, i.e. hadronization mechanism, fall outside the validity regions for perturbative calculations, requiring phenomenological models tuned to data to describe it. As such, hadronization physics cannot be currently derived from first principles alone. Monte Carlo event generators are useful tools to describe these processes as they simulate both the perturbative and the non-perturbative interactions, with model-dependent energy scales that control parton dynamics. This work employs jets - experimental reconstructions of final-state particles likely to have a common partonic origin - to inspect this transition further. Although originally proposed to circumvent hadronization effects, we show that jets can be utilised as probes of non-perturbative phenomena via their substructure. The charge correlation ratio was recently shown to be sensitive to hadronization effects. Our work further improves this sensitivity to non-perturbative scales by introducing a new selection based on the relative placement of the \textit{resolved SoftDrop splitting} within the clustering tree, defined as the unclustering that resolves the jet's leading charged particles.

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arXiv2024

Model-Agnostic Tagging of Quenched Jets in Heavy-Ion Collisions

Measurements of jet substructure in ultra-relativistic heavy-ion collisions indicate that interactions with the quark-gluon plasma quench the jet showering process. Modern data-driven methods have shown promise in probing these modifications in the jet's hard substructure. In this Letter, we present a machine learning framework to identify quenched jets while accounting for pileup, uncorrelated soft particle background, and detector effects; a more experimentally realistic and challenging scenario than previously addressed. Our approach leverages an interpretable sequential attention-based mechanism that integrates representations of individual jet constituents alongside global jet observables as features. The framework sets a new benchmark for tagging quenched jets with reduced model dependence.

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arXiv2024

A New Herwig7 Underlying Event Tune: from RHIC to LHC Energies

We present parameter sets corresponding to new underlying event tunes for the Herwig7.3 Monte Carlo event generator. The existing Herwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass energies below $\sqrt{s}=300$ GeV. The tunes presented in this study can describe mid-rapidity data collected at the nominal RHIC energy of $\sqrt{s }=200$ GeV, as well as higher center-of-mass energies utilized by experiments elsewhere, such as the LHC. The base "New Haven" tune is developed by fitting minimum-bias simulations of proton-proton collisions to mid-rapidity identified hadron and jet data from the STAR experiment. The "Nashville" tune includes a separate set of parameters developed by tuning to Tevatron proton-antiproton data at $\sqrt{s}=300$, $900$ and $1960$ GeV from CDF, and LHC proton-proton measurements from CMS at $\sqrt{s}=7$ TeV, in addition to the STAR measurements. Both new tunes demonstrate significant improvements over the recommended default tune currently included in the latest version of Herwig for minimum bias production. As such, we advocate using these tunes for future simulation studies at mid-rapidity by the experimental collaborations at RHIC (STAR and sPHENIX) and the LHC (ATLAS, ALICE, CMS).

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arXiv2023

Holographic transport coefficients and jet energy loss for the hot and dense quark-gluon plasma

We employ an Einstein-Maxwell-dilaton model, based on the gauge/gravity correspondence, to obtain the thermodynamics and transport properties for the hot and dense quark-gluon plasma. The model, which is constrained to reproduce lattice QCD thermodynamics at zero density, predicts a critical point and a first order line at finite temperature and density, is used to quantify jet energy loss through simulations of high-energy collision events.

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arXiv2023

Resolving the Scales of the Quark-Gluon Plasma with Energy Correlators

Jets provide us with ideal probes of the quark-gluon plasma (QGP) produced in heavy-ion collisions, since its dynamics at its different scales is imprinted into the multi-scale substructure of the final state jets. We present a new approach to jet substructure in heavy-ion collisions based on the study of correlation functions of energy flow operators. By analysing the two-point correlator of an in-medium quark jet, we demonstrate that the spectra of correlation functions robustly identify the scales defined by the properties of the QGP, particularly those associated with the onset of colour coherence.

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arXiv2022

Exploring and exploiting various regimes within the jet shower

The last few years have seen community-wide excitement in the study of jet substructure derived from the inner workings of clustering algorithms. Such efforts have resulted in the design of new observables which are related to partonic processes from final state hadrons. Since jets are multi-scale objects, they necessarily encode information about both the perturbative (pQCD) parton shower and non-perturbative (npQCD) physics including hadronization. Recent high precision measurements of jet substructure in proton-proton (pp) collisions have pushed the theoretical community into extending their predictions to higher orders resulting in the observation of large theoretical uncertainties from the non-perturbative regime of the calculations. We emphasize the importance of understanding a jet shower from a multi-dimensional point of view and highlight a recent measurement focused on distinguishing the pQCD vs. npQCD regimes within a jet shower. We introduce and discuss the utility of the formation time evaluated at varying stages of the jet shower in pp collisions. Finally, we present a monte-carlo study of the formation time of charged particles within the jet to gain a handle on hadronization mechanisms including string-breaking, and outline a path forward for such observables in heavy ion collisions.

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arXiv2022

PYTHIA 8 underlying event tune For RHIC energies

We report an underlying event tune for the PYTHIA 8 Monte Carlo event generator that is applicable for hadron collisions primarily at $\sqrt{s}$ ranges available at the Relativistic Heavy-Ion Collider (RHIC). We compare our new PYTHIA 8 tuned predictions to mid-rapidity inclusive $π^{\pm}$ spectra, jet sub-structure, Drell-Yan production, and underlying event measurements from RHIC and the Tevatron, as well as underlying event data from the Large Hadron Collider. With respect to the default PYTHIA 8 Monash Tune, the new `Detroit' tune shows significant improvements in the description of the experimental data. Additionally, we explore the validity of PYTHIA 8 predictions for forward rapidity $π$ in $\sqrt{s}$ = 200 GeV collisions, where neither tune is able to sufficiently describe the data. We advocate for the new tune to be used for PYTHIA 8 studies at current and future RHIC experiments, and discuss future tuning exercises at lower center-of-mass energies, where forward/backward kinematics are essential at the upcoming Electron-Ion collider.

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arXiv2021

Measurement of splittings along a jet shower in $\sqrt{s} = 200$ GeV pp collisions at STAR

Jets are algorithmic proxies of hard scattered partons, i.e. quarks and gluons, in high energy particle collisions. The STAR collaboration presents the first measurements of substructure observables at the first, second and third splits in the jet clustering tree via the iterative SoftDrop procedure. For each of these splits, we measure the fully corrected groomed shared momentum fraction (\zg) and groomed jet radius (\rg). We discuss the evolution of jet substructure in both the angular and momentum scales which allows for a self-similarity test of the DGLAP splitting function. We compare the fully corrected data to Monte Carlo models, providing stringent constraints on model parameters related to the parton shower and non-perturbative effects such as hadronization.

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arXiv2021

Identifying Heavy-Flavor Jets Using Vectors of Locally Aggregated Descriptors

Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly towards understanding partonic energy loss in the QGP medium and its related modifications of the jet shower and fragmentation. Since the QGP is a colored medium, the extent of jet quenching and consequently, the transport properties of the medium are expected to be sensitive to fundamental properties of the jets such as the flavor of the parton that initiates the jet. Identifying the jet flavor enables an extraction of the mass dependence in jet-QGP interactions. We present a novel approach to tagging heavy-flavor jets at collider experiments utilizing the information contained within jet constituents via the \texttt{JetVLAD} model architecture. We show the performance of this model in proton-proton collisions at center of mass energy $\sqrt{s} = 200$ GeV as characterized by common metrics and showcase its ability to extract high purity heavy-flavor jet sample at various jet momenta and realistic production cross-sections including a brief discussion on the impact of out-of-time pile-up. Such studies open new opportunities for future high purity heavy-flavor measurements at jet energies accessible at current and future collider experiments.

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arXiv2020

Constraining parton energy loss via angular and momentum based differential jet measurements at STAR

Parton energy loss has been established as an essential signature of the Quark-Gluon Plasma (QGP) in heavy ion collisions since the earliest measurements at RHIC indicating suppression of hadron spectra at high $p_{\rm{T}}$ and coincidence yields. Understanding this phenomenon of jet quenching is a requirement for extracting the microscopic properties of the QGP via jet-tomography. STAR has recently introduced a technique called Jet Geometry Engineering (JGE) wherein we enforce particular selection criteria imposed on the jet collection, such as recoiling off a high $p_{\rm{T}}$ hadron trigger along with an additional transverse momentum threshold for jet constituents in events with back-to-back di-jets. With JGE, we are able to control the extent of energy loss ranging from quenched/imbalanced to recovered/balanced di-jets. Since jet quenching is also expected to be dependent on the resolution/transverse-length scales with which the jet probes the medium, it is necessary to perform differential measurements with a handle on both momentum and angular scales. To quantify the angular scale within jets, we present the first measurement of the jet's inherent angular structure in Au$+$Au collisions at $\sqrt{s_{\mathrm{NN}}} = $ 200 GeV via the opening angle between the two leading sub-jets ($θ_{\rm{SJ}}$). We also measure the di-jet asymmetry $A_{\rm{J}}$ differentially as a function of the $θ_{\rm{SJ}}$ observable for these di-jets and find no significant dependence of the energy loss on the opening angle of the recoil jet.

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arXiv2019

Jet sub-structure and parton shower evolution in p+p and Au+Au collisions at STAR

Recent measurements of jet structure modifications at RHIC and LHC highlight the importance of differential measurements to study the nature of jet quenching. Since these jet structure observables are intimately dependent on parton evolution in both the angular and energy scales, measurements are needed to disentangle these two scales in order to probe the medium at different length scales to study its characteristic properties such as the coherence length. To that effect, the STAR collaboration presents fully unfolded results of jet sub-structure observables designed to extract fundamental quantities related to the parton shower via the SoftDrop shared momentum fraction, the groomed jet radius, and the jet Mass in p+p collisions at 200 GeV as a function of jet transverse momenta. We also showcase the first measurement of iterative softdrop groomed observables for first, second and third splits with an initiator prong transverse momenta ranging from 20-25 GeV. In comparing the un-corrected data to our simulation, we are able to look at snapshots of the jet clustering history leading towards an understand of the time evolution of the parton shower. Having established the p+p baseline, we present the first measurement of the jet's inherent angular structure in Au+Au collisions at 200 GeV via an experimentally robust observable the opening angle between the two leading sub-jets ($θ_{SJ}$). In Au+Au collisions at STAR, we utilize a specific di-jet selection as introduced in our previous momentum imbalance ($A_{J}$) measurement and measure both the $A_{J}$ and the recoil jet spectra differentially as a function of the angular classes based on the $θ_{SJ}$ observable. With such measurements, we probe the medium response to jets at a particular resolution scale and find no significant differences in quenching for jets of different angular scales as given by $θ_{SJ}$.

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arXiv2019

Measurements of the jet internal sub-structure and its relevance to parton shower evolution in p+p and Au+Au collisions at STAR

Recent measurements of jet structure modifications at RHIC and LHC highlight the importance of differential measurements to study the nature of jet quenching. Since these jet structure observables are intimately dependent on parton evolution in both the angular and energy scales, measurements are needed to disentangle these two scales in order to probe the medium at different length scales to study its characteristic properties such as the coherence length. To that effect, the STAR collaboration presents fully unfolded results of a jet's sub-structure via the SoftDrop shared momentum fraction ($z_{g}$) and the groomed jet radius ($R_{g}$) in p+p collisions at $\sqrt{s} = $ 200 GeV as a function of jet momenta. Having established the p+p baseline, we present the first measurement of the jet's inherent angular structure in Au+Au collisions at $\sqrt{s_{NN}} = $ 200 GeV via an experimentally robust observable related to the SoftDrop $R_{g}$: the opening angle between the two leading sub-jets ($θ_{SJ}$). In Au+Au collisions at STAR, we utilize a specific di-jet selection as introduced in our previous momentum imbalance ($A_{J}$) measurement and the recoil jet spectra differentially as a function of jet transverse momentum belonging to particular angular lasses based on the $θ_{SJ}$ observable. With such measurements, we probe the medium response to jets at a particular resolution scale and find no significant differences in quenching for jets of different angular scales as given by $θ_{SJ}$.

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arXiv2018

Probing heavy ion collisions using quark and gluon jet substructure

We study the phenomenon of jet quenching utilizing quark and gluon jet substructures as independent probes of heavy ion collisions. We exploit jet and subjet features to highlight differences between quark and gluon jets in vacuum and in a medium with the jet-quenching model implemented in JEWEL. We begin with a physics-motivated, multivariate analysis of jet substructure observables including the jet mass, the radial moments, the $p_T^D$ and the pixel multiplicity. In comparison, we employ state-of-the-art image-recognition techniques by training a deep convolutional neutral network on jet images. To systematically extract jet substructure information, we introduce the telescoping deconstruction framework exploiting subjet kinematics at multiple angular scales. We draw connections to the soft-drop subjet distribution and illuminate medium-induced jet modifications using Lund diagrams. We find that the quark gluon discrimination performance worsens in heavy ion jets due to significant soft event activity affecting the soft jet substructure. Our work suggests a systematically improvable framework for studying modifications to quark and gluon jet substructures and facilitating direct comparisons between theoretical calculations, simulations and measurements in heavy ion collisions.

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