arXiv subjects

Aditya Nath Mishra

Publications and source records attributed to Aditya Nath Mishra.

At least 19 recordsLinked to original sources

arXiv2026

Evolution of the underlying event and non-extensive thermodynamics in pp collisions from RHIC to LHC energies

We investigate the geometrical and thermodynamical aspects of particle production in pp collisions over a broad center-of-mass energy, ranging from $\sqrt{s}=62.4$ GeV to 13 TeV using PYTHIA8. We study the azimuthal dependence of charged-particle production relative to the leading particle. This includes the study of the Tsallis--Pareto parameters extracted from the charged-particle transverse-momentum spectra in fixed $Δϕ$ intervals relative to the leading charged particle. The simultaneous analysis of charged-particle multiplicity and event topology demonstrates that the underlying event (UE) dominated region can be extended beyond the conventional transverse side region across RHIC and LHC energies. To further disentangle effects from soft and hard particle production mechanisms, the study is performed in different transverse spherocity and charged-particle flattenicity classes. We demonstrate that the UE region extends beyond the conventional transverse region, validating an enlarged angular interval of $40^\circ\lesssim|Δϕ|\lesssim140^\circ$ from RHIC to LHC energies. Event-shape selections reveal that jetty events consistently exhibit larger $q$ and lower $T_{\rm s}$ than isotropic events. The $Δϕ$ profiles of charged-particle multiplicity and transverse spherocity remain universal in shape across collision energies despite the strong increase in overall event activity, whereas the Tsallis parameters retain a residual, leading-particle-driven energy dependence in the near- and away-side regions.

hep-ph↗

arXiv2024

A Deep Learning Based Estimator for Light Flavour Elliptic Flow in Heavy Ion Collisions at LHC Energies

We developed a deep learning feed-forward network for estimating elliptic flow ($v_2$) coefficients in heavy-ion collisions from RHIC to LHC energies. The success of our model is mainly the estimation of $v_2$ from final state particle kinematic information and learning the centrality and the transverse momentum ($p_{\rm T}$) dependence of $v_2$ in wide $p_{\rm T}$ regime. The deep learning model is trained with AMPT-generated Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV minimum bias events. We present $v_2$ estimates for $π^{\pm}$, $\rm K^{\pm}$, and $\rm p+\bar{p}$ in heavy-ion collisions at various LHC energies. These results are compared with the available experimental data wherever possible.

hep-ph↗

arXiv2023

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↗

arXiv2023

Exploring the QGP phase above the deconfinement temperature in $pp$ and $A-A$ collisions at LHC energies

In the present work we have analyzed the transverse momentum spectra of charged particles in high multiplicity ${\it pp}$ collisions at LHC energies $\sqrt s = $ 5.02 and 13 TeV published by the ALICE Collaboration using the Color String Percolation Model (CSPM). For heavy ions Pb-Pb at $\sqrt {s_{NN}} =$ 2.76 and 5.02 TeV along with Xe-Xe at $\sqrt {s_{NN}} = $ 5.44 TeV have been analyzed. The initial temperature is extracted both in low and high multiplicity events in ${\it pp}$ collisions. For $A-A$ collisions the temperature is obtained as a function of centrality. A universal scaling in the temperature from $pp$ and $A-A$ collisions is obtained when multiplicity is scaled by the transverse interaction area.From the measured energy density $\bm \varepsilon$ and the temperature the dimensionless quantity $\bm \varepsilon/T^{4}$ is obtained. Our results for Pb-Pb and Xe-Xe collisions show a sharp increase in $\bm \varepsilon/T^{4}$ above T $\sim$ 210 MeV and reaching the ideal gas of quarks and gluons value of $\bm \varepsilon/T^{4} \sim$ 16 at temperature $\sim $ 230 MeV. In case of $pp$ collisions only $\bm \varepsilon/T^{4} \sim $ 10 corresponding to $\sim$ 30 degrees of freedom.

hep-ph↗

arXiv2023

Deep learning predicted elliptic flow of identified particles in heavy-ion collisions at the RHIC and LHC energies

Recent developments on a deep learning feed-forward network for estimating elliptic flow ($v_2$) coefficients in heavy-ion collisions have shown us the prediction power of this technique. The success of the model is mainly the estimation of $v_2$ from final state particle kinematic information and learning the centrality and the transverse momentum ($p_{\rm T}$) dependence of $v_2$. The deep learning model is trained with Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV minimum bias events simulated with a multiphase transport model (AMPT). We extend this work to estimate $v_2$ for light-flavor identified particles such as $π^{\pm}$, $\rm K^{\pm}$, and $\rm p+\bar{p}$ in heavy-ion collisions at RHIC and LHC energies. The number of constituent quark (NCQ) scaling is also shown. The evolution of $p_{\rm T}$-crossing point of $v_2(p_{\rm T})$, depicting a change in meson-baryon elliptic flow at intermediate-$p_{\rm T}$, is studied for various collision systems and energies. The model is further evaluated by training it for different $p_{\rm T}$ regions. These results are compared with the available experimental data wherever possible.

hep-ph↗

arXiv2022

Predictions on global properties in O+O collisions at the Large Hadron Collider using a multi-phase transport model

Oxygen ($^{16}$O) ions are planned to be injected at the Large Hadron Collider (LHC) in its next runs, and a day of physics run is anticipated for O+O collisions at $\sqrt{s_{\rm{NN}}}$ = 7 TeV. As the system size of O+O collisions has the final state multiplicity overlap with those produced in pp, p+Pb and Pb+Pb collisions, the study of global properties in O+O collisions may provide a deeper insight into the heavy-ion-like behavior observed in small collision systems and its similarities/differences with a larger system like Pb+Pb collisions. In the present work, we report the predictions for global properties in O+O collisions at $\sqrt{s_{\rm{NN}}}$ = 7 TeV using a multi-phase transport model (AMPT). We report the mid-rapidity charged-particle multiplicity, transverse mass, Bjorken energy density, pseudo-rapidity distributions, squared speed of sound, transverse momentum ($p_{\rm T}$) spectra, the kinetic freeze-out parameters, and $p_{\rm T}$-differential particle ratio as a function of collision centrality. Further, we have studied the transverse momentum-dependent elliptic flow of charged particles. The results are shown for Woods-Saxon and harmonic oscillator nuclear density profiles. In addition, we have compared the results with an $α$-clustered structure incorporated inside the oxygen nucleus. Average charged-particle multiplicity and the Bjorken energy density show a significant increase in most central collisions for the harmonic oscillator density profile, while other global properties show less dependence on the density profiles considered in this work. The results from the $α$-clustered structure incorporated inside the oxygen nucleus show similar initial energy density and final charged-particle multiplicity as observed for the harmonic oscillator density profile.

hep-ph↗

arXiv2022

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.

nucl-th↗

arXiv2022

Estimating Elliptic Flow Coefficient in Heavy Ion Collisions using Deep Learning

Machine Learning (ML) techniques have been employed for the high energy physics (HEP) community since the early 80s to deal with a broad spectrum of problems. This work explores the prospects of using Deep Learning techniques to estimate elliptic flow ($v_2$) in heavy-ion collisions at the RHIC and LHC energies. A novel method is developed to process the input observables from particle kinematic information. The proposed DNN model is trained with Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV minimum bias events simulated with AMPT model. The predictions from the ML technique are compared to both simulation and experiment. The Deep Learning model seems to preserve the centrality and energy dependence of $v_2$ for the LHC and RHIC energies. The DNN model is also quite successful in predicting the $p_{\rm T}$ dependence of $v_2$. When subjected to event simulation with additional noise, the proposed DNN model still keeps the robustness and prediction accuracy intact up to a reasonable extent.

hep-ph↗

arXiv2022

Jet Transport Coefficient at the Large Hadron Collider Energies in a Color String Percolation Approach

Within the color string percolation model (CSPM), jet transport coefficient, $\hat{q}$, is calculated for various multiplicity classes in proton-proton and centrality classes in nucleus-nucleus collisions at the Large Hadron Collider energies for a better understanding of the matter formed in ultra-relativistic collisions. $\hat{q}$ is studied as a function of final state charged particle multiplicity (pseudorapiditydensity at midrapidity), initial state percolation temperature and energy density. The CSPM results are then compared with different theoretical calculations from the JET Collaboration those incorporate particle energy loss in the medium.

hep-ph↗

arXiv2021

Study of the jet transport coefficient at the Large Hadron Collider energies using Color String Percolation Model

In order to have a better understanding of the matter formed in ultra-relativistic collisions, we estimate the jet transport coefficient, $\hat q$, within the Color Sting Percolation Model (CSPM) for various multiplicity classes in proton-proton collisions and centrality classes in nucleus-nucleus collisions at the Large Hadron Collider energies. We study $\hat q$ as a function of final state charged-particle multiplicity and initial percolation temperature. Finally, we compare our obtained results with those calculated from the JET collaboration.

hep-ph↗

arXiv2021

Implementation of machine learning techniques to predict impact parameter and transverse spherocity in heavy-ion collisions at the LHC

Machine learning techniques have been quite popular recently in the high-energy physics community and have led to numerous developments in this field. In heavy-ion collisions, one of the crucial observables, the impact parameter, plays an important role in the final-state particle production. This being extremely small (i.e. of the order of a few fermi), it is almost impossible to measure impact parameter in experiments. In this work, we implement the ML-based regression technique via Gradient Boosting Decision Trees (GBDT) to obtain a prediction of impact parameter in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV using A Multi-Phase Transport (AMPT) model. After its successful implementation in small collision systems, transverse spherocity, an event shape observable, holds an opportunity to reveal more about the particle production in heavy-ion collisions as well. In the absence of any experimental exploration in this direction at the LHC yet, we suggest an ML-based regression method to estimate centrality-wise transverse spherocity distributions in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV by training the model with minimum bias collision data. Throughout this work, we have used a few final state observables as the input to the ML-model, which could be easily made available from collision data. Our method seems to work quite well as we see a good agreement between the simulated true values and the predicted values from the ML-model.

hep-ph↗

arXiv2021

Quantifying the Underlying Event: Investigating Angular Dependence of Multiplicity Classes and Transverse-momentum Spectra in High-energy pp Collisions at LHC Energies

We present a study of the transverse momentum spectra and their evolution in function of the position of the azimuthal of the particles associated to the leading particle. Additionally, the behavior of the spherocity distribution in the same azimuthal bins is reported. The studies were made using proton-proton collisions at $\sqrt{s}$ = 13 TeV using PYTHIA8 Monte Carlo event generator. The Multiplicity and midrapidity transverse momentum spectra of charged hadrons have been analyzed in the non-extensive statistical framework. The results on the findings corresponding to the Underlying Event are reported.

hep-ph↗

arXiv2021

Estimation of Impact Parameter and Transverse Spherocity in heavy-ion collisions at the LHC energies using Machine Learning

Recently, machine learning (ML) techniques have led to a range of numerous developments in the field of nuclear and high-energy physics. In heavy-ion collisions, the impact parameter of a collision is one of the crucial observables which has a significant impact on the final state particle production. However, calculation of such a quantity is nearly impossible in experiments as the length scale ranges in the level of a few fermi. In this work, we implement the ML-based regression technique via Boosted Decision Tree (BDT) to obtain a prediction of impact parameter in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV using A Multi-Phase Transport (AMPT) model. In addition, we predict an event shape observable, transverse spherocity in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 2.76 and 5.02 TeV using AMPT and PYTHIA8 based on Angantyr model. After a successful implementation in small collision systems, the use of transverse spherocity in heavy-ion collisions has potential to reveal new results from heavy-ion collisions where the production of a QGP medium is already established. We predict the centrality dependent spherocity distributions from the training of minimum bias simulated data and it was found that the predictions from BDT based ML technique match with true simulated data. In the absence of experimental measurements, we propose to implement Machine learning based regression technique to obtain transverse spherocity from the known final state observables in heavy-ion collisions.

hep-ph↗

arXiv2020

Parton energy loss in pp collisions at very high multiplicity

We present the results for the evolution of transverse momentum spectra for the jetty and underlying parts of events as a function of multiplicity in pp collisions at 13 TeV measured at midrapidity ($\left|η\right|<0.8$) using PYTHIA8 event generator. The main characteristic of the approach is that it reaches to extreme multiplicities not yet explored by the experiments. We demonstrate that the behavior of both the underlying and hard components are affected by the multiplicity of the events i.e. the energy density. The behavior of the spectra at very high multiplicities suggests that the partons suffer energy loss compensated by an increase in the multiplicity of events.

hep-ph↗

arXiv2019

Effective-energy universality approach describing total multiplicity centrality dependence in heavy-ion collisions

The recently proposed participant dissipating effective-energy approach is applied to describe the dependence on centrality of the multiplicity of charged particles measured in heavy-ion collisions at the collision energies up to the highest LHC energy of 5 TeV. The effective-energy approach relates multihadron production in different types of collisions, by combining, under the proper collision energy scaling, the constituent quark picture with Landau relativistic hydrodynamics. The measurements are shown to be well described in terms of the centrality-dependent effective energy of participants and an explanation of the differences in the measurements at RHIC and LHC are given by means of the recently introduced hypothesis of the energy-balanced limiting fragmentation scaling. A similarity between the centrality data and the data from most central collisions is proposed pointing to the central character of participant interactions independent of centrality. The findings complement our recent investigations of the similar midrapidity pseudorapidity density measurements extending the description to the full pseudorapidity range in view of the considered similarity of multihadron production in nucleon interactions and heavy-ion collisions.

hep-ph↗

arXiv2019

Intriguing similarities between high-$p_{\rm T}$ particle production in pp and A-A collisions

In this paper we study the particle production at high transverse momentum ($p_{\rm T}>8$ GeV/$c$) in both pp and Pb-Pb collisions at LHC energies. The characterization of the spectra is done using a power-law function and the resulting power-law exponent ($n$) is studied as a function of $x_{\rm T}$ for minimum-bias pp collisions at different $\sqrt{s}$. The functional form of $n$ as a function of $x_{\rm T}$ exhibits an approximate universal behavior. PYTHIA~8.212 reproduces the scaling properties and therefore, it is used to study the multiplicity-dependent particle production. Going from low to high multiplicities, the power-law exponent decreases. A similar behavior is also observed in heavy-ion collisions when one studies the centrality-dependent particle production. The interpretation of heavy-ion results requires the quantification of the impact of this correlation (multiplicity and high $p_{\rm T}$) on jet-quenching observables.

hep-ph↗

arXiv2016

Energy and Centrality dependence of $dN_{\rm ch}/dη$ and $dE_{\rm T}/dη$ in Heavy-Ion Collisions from $\sqrt{s_{\rm NN}}$ =7.7 GeV to 5.02 TeV

The centrality dependence of pseudorapidity density of charged particles and transverse energy is studied for a wide range of collision energies for heavy-ion collisions at midrapidity from 7.7 GeV to 5.02 TeV. A two-component model approach has been adopted to quantify the soft and hard components of particle production, coming from nucleon participants and binary nucleon-nucleon collisions, respectively. Within experimental uncertainties, the hard component contributing to the particle production has been found not to show any clear collision energy dependence from RHIC to LHC. The effect of centrality and collision energy in particle production seem to factor out with some degree of dependency on the collision species. The collision of Uranium-like deformed nuclei opens up new challenges in understanding the energy-centrality factorization, which is evident from the centrality dependence of transverse energy density, when compared to collision of symmetric nuclei.

hep-ph↗

arXiv2016

Centrality dependence of midrapidity density from GeV to TeV heavy-ion collisions in the effective-energy universality picture of hadroproduction

The dependence on centrality, or on the number of nucleon participants, of the midrapidity density of charged particles measured in heavy-ion collisions at the collision energy of about 20 GeV at RHIC to the highest LHC energy of 5 TeV is investigated within the recently proposed effective-energy approach. This approach relates multihadron production in different types of collisions by combining, under the proper scaling of the collision energy, the constituent quark picture with Landau relativistic hydrodynamics. The measurements are shown to be well described based on the similarity of multihadron production process in (anti)proton-proton interactions and heavy-ion collisions driven by the centrality-dependent effective energy of participants.

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