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Kalyan Dey

Publications and source records attributed to Kalyan Dey.

9 recordsLinked to original sources

Observation of partonic collectivity via $p_{\rm T}$-differential radial flow fluctuations in Au+Au collisions at $\sqrt{s_{\rm NN}} = 200$ GeV

We report the observation of partonic radial collectivity in Au+Au collisions at $\sqrt{s_{\rm NN}} = 200$~GeV via the $p_{\rm T}$-differential flow observable $v_{0}(p_{\rm T})$ using the \texttt{AMPT} String Melting model. For inclusive charged hadrons, we establish three signatures of collectivity: long-range pseudorapidity correlations, the factorization of two-particle correlations, and a centrality-independent scaling of $v_{0}(p_{\rm T})$ normalized by its $p_{\rm T}$-integrated value $v_{0}$, analogous to anisotropic flow. For identified particles ($\pi^{\pm}, K^{\pm}, p + \overline p$), the $v_{0}(p_{\rm T})$ spectra show mass ordering at low-$p_{\rm T}$ and meson-baryon separation at intermediate-$p_{\rm T}$. In \textit{central} collisions, $v_{0}(p_{\rm T})/n_{q}$ exhibits robust \textit{Number of Constituent Quark} (NCQ) scaling with $(m_{\rm T} - m_{0})/n_{q}$, a scaling that breaks down in \textit{peripheral} collisions and is more precise at RHIC than at LHC energies, consistent with earlier $v_{2}$ studies. These findings provide strong evidence that radial collectivity originates predominantly at the partonic stage, extending the paradigm of quark-level dynamics from anisotropic to isotropic flow.

nucl-ex

Harnessing data-driven methods for precise model independent event shape estimation in relativistic heavy-ion collisions

This study demonstrates the application of supervised machine learning (ML) techniques to distinguish between isotropic and jet-like event topologies in heavy-ion collisions via the spherocity observable. State-of-the-art ML algorithms, optimized through systematic hyperparameter tuning, are employed to predict both traditional transverse spherocity $S_{0}$ and unweighted transverse spherocity $S_{0}^{p_{\rm T}=1}$ directly from raw event data. Moreover, the results from this study demonstrated that our approach remains largely model-independent, underscoring its potential applicability in future experimental heavy-ion physics analyses.

hep-ph

Probing non-perturbative QCD aspects on particle production in pp collisions with forward-backward correlations using \texttt{PYTHIA8}

We employ PYTHIA8 simulations to study forward-backward (FB) correlations in pp collisions at LHC energies, probing non-perturbative QCD dynamics via color reconnection (CR) and QCD radiation (ISR/FSR). Using \texttt{PYTHIA8} (v8.311) under ALICE/ATLAS kinematics, we analyze: extensive: FB multiplicity ($b_{\rm corr}^{\rm mult}$) and summed $p_{\rm T}$ ($b_{\rm corr}^{\sum p_{\rm T}}$) correlations; intensive: FB mean $p_{\rm T}$ ($b_{\rm corr}^{\overline p_{\rm T}}$) correlations; and \textit{strongly intensive:} $Σ_{\rm N_F N_B}$ quantity in symmetric pseudorapidity intervals, validated against available experimental data. Systematic studies of $b_{\rm corr}^{\rm mult}$ as functions of $η_{\rm gap}$, $η_{\rm sep}$, and $η$-$φ$ sectors show MPI-based CR (ranges 3.6, 5.4) and QCD Color Rope significantly improve agreement with data. ISR/FSR critically influence $b_{\rm corr}^{\rm mult}$ and $b_{\rm corr}^{\sum p_{\rm T}}$, with ISR dominant than FSR. Disabling ISR/FSR fails to replicate $η_{\rm gap}$-dependent trends. Further, $b_{\rm corr}^{\sum p_{\rm T}}$ shows minimal CR-range sensitivity but the correlation strength increases when CR is disabled. Intensive quantity, $b_{\rm corr}^{\overline p_{\rm T}}$, exhibit the opposite behavior to extensive observables i.e. the magnitude of $b_{\rm corr}^{\overline p_{\rm T}}$ increases with the increase of CR strength, highlighting the distinct influence of CR on intensive versus extensive observables. Its azimuthal dependence indicates that parton showers drive short-range correlations. The analysis of the strongly intensive quantity as a function of pseudorapidity gap indicates that FSR plays a dominant role at larger gaps, in contrast to the behavior observed in FB multiplicity correlations.

hep-ph

Estimating centrality in heavy-ion collisions using Transfer Learning technique

In this study, we explore the applicability of Transfer Learning techniques for estimating collision centrality in terms of the number of participants ($N_{\rm part}$) in high-energy heavy-ion collisions. In the present work, we leverage popular pre-trained CNN models such as VGG16, ResNet50, and DenseNet121 to determine $N_{\rm part}$ in Au+Au collisions at $\sqrt{s}=200$ GeV on an event-by-event basis. Remarkably, all three models achieved good performance despite the pre-trained models being trained for databases of other domains. Particularly noteworthy is the superior performance of the VGG16 model, showcasing the potential of transfer learning techniques for extracting diverse observables from heavy-ion collision data.

hep-ph

Effect of color reconnection and rope formation on strange particle production in p+p collisions at $\sqrt{s}=13$ TeV

Strange particles are produced only during high-energy collisions and carry important information regarding collision dynamics. Recent results by the ALICE Collaboration on strangeness enhancement in high-multiplicity p+p collisions have highlighted the importance of the rope hadronization mechanism in high-energy nucleon-nucleon collisions. With the help of the \texttt{PYTHIA8} model, we made an attempt to study the strange particle production in high-energy p+p collisions at the LHC energy in the light of different color reconnection models and rope hadronization mechanism. The effect of color reconnection ranges on different observables is also discussed. The integrated yield of strange hadrons and bayon-to-meson ratios as a function of charged-particle multiplicity in p+p collisions at $\sqrt{s}$ = 13 TeV are well described by the hadronization mechanism of color ropes together with the QCD-based color reconnection scheme. The increasing trend of the average transverse momentum, $\langle p_{\rm T}\rangle$, as a function of $\langle dN/dη\rangle_{|η| < 0.5}$ can be explained quantitatively by the MPI-based color reconnection mechanism with a reconnection range of RR = 3.6; on the other hand, it is underestimated by the rope hadronization model.

hep-ph

Effect of event classifiers on jet quenching-like signatures in high-multiplicity $p+p$ collisions at $\sqrt{s} = 13$ TeV

The motivation behind exploring jet quenching-like phenomena in small systems arises from the experimental observation of heavy-ion-like behavior of particle production in high-multiplicity proton-proton ($p+p$) collisions. Quantifying the jet quenching in $p+p$ collisions is a challenging task, as the magnitude of the nuclear modification factor ($R_{\rm AA}$ or $R_{\rm CP}$), which is used to quantify jet quenching, is influenced by several factors, such as the estimation of centrality and the scaling factor. The most common method of centrality estimation employed by the ALICE collaboration is based on measuring charged-particle multiplicity with the V0 detector situated at the forward rapidity. This technique of centrality estimation makes the event sample biased towards hard processes like multijet final states. This bias of the V0 detector towards hard processes makes it difficult to study the jet quenching effect in high-multiplicity $p+p$ collisions. In the present article, we propose to explore the use of a new and robust event classifier, flattenicity which is sensitive to both the multiple soft partonic interactions and hard processes. The $\mathcal{P}_{\rm CP}$, a quantity analogous to $R_{\rm CP}$, has been estimated for high-multiplicity $p+p$ collisions at $\sqrt{s} = 13$ TeV using \texttt{PYTHIA8} model for both the V0M (the multiplicity classes selected based on V0 detector acceptance) as well as flattenicity. The evolution of $\mathcal{P}_{\rm CP}$ with $p_{\rm T}$ shows a heavy-ion-like effect for flattencity which is attributed to the selection of softer transverse momentum particles in high-multiplicity $p+p$ collisions.

hep-ph

Estimation of collision centrality in terms of the number of participating nucleons in heavy-ion collisions using deep learning

The deep learning technique has been applied for the first time to investigate the possibility of centrality determination in terms of the number of participants ($N_{\mathrm{part}}$) in high-energy heavy-ion collisions. For this purpose, supervised learning using both deep neural network (DNN) and convolutional neural network (CNN) is performed with labeled data obtained by modeling relativistic heavy-ion collisions utilizing A Multi-phase Transport Model (AMPT). Event-by-event distributions of pseudorapidity and azimuthal angle of charged hadrons weighted by their transverse momentum are used as input to train the DL models. The DL models did remarkably well in predicting $N_{\mathrm{part}}$ values with CNN slightly outperforming the DNN model. The Mean Squared Logarithmic Error (MSLE) for the CNN model (Model-4) is determined to be 0.0592 for minimum bias collisions and 0.0114 for 0-60\% centrality class, indicating that the model performs better for semi-central and central collisions. Furthermore, the studied DL model is proven to be robust to changes in energy as well as model parameters of the input. The current study demonstrates that the data-driven technique has a distinct potential for determining centrality in terms of the number of participants in high-energy heavy-ion collision experiments.

hep-ph

Strange behavior of rapidity dependent strangeness enhancement of particles containing and not containing leading quarks

Rapidity dependent strangeness enhancement factors for the identified particles have been studied with the help of a string based hadronic transport model UrQMD-3.3 (Ultra-relativistic Quantum Molecular Dynamics) at FAIR energies. A strong rapidity dependent strangeness enhancement could be observed with our generated data for $Au + Au$ collisions at the beam energy of 30\textit{A} GeV. The strangeness enhancement is found to be maximum at mid-rapidity for the particles containing leading quarks while for particles consisting of produced quarks only, the situation is seen to be otherwise. Such rapidity dependent strangeness enhancement could be traced back to the dependence of rapidity width on centrality or otherwise on the distribution of net-baryon density.

hep-ph

Separate mass scaling of the widths of the rapidity distributions for mesons and baryons at energies available at the Facility for Antiproton and Ion research

Evolution of the width of the rapidity distribution on beam rapidity has been studied for a number of produced particles with UrQMD-3.3p1 generated events at various FAIR (Facility for Antiproton and Ion Research) energies. The results for the width of the rapidity distribution with beam rapidity, obtained with UrQMD generated events, are compared with the existing experimental data (E802, E877, E896, E917, NA49). For both UrQMD and experimental data, the width of the rapidity distribution is found to bear scaling behavior with beam rapidity for all the hadrons. Such scaling behavior is found to follow separate mass ordering for the studied mesons and and baryons.

hep-ph