arXiv subjects

Raghunath Sahoo

Publications and source records attributed to Raghunath Sahoo.

At least 55 records · Page 3Linked to original sources

arXiv2025

Thermoelectric effects of an interacting hadron gas in the presence of an external magnetic field

The hot and dense hadronic medium formed during the heavy-ion collisions at the Relativistic Heavy Ion Collider and Large Hadron Collider energies can show thermoelectric effects in the presence of temperature gradients and nonzero baryon chemical potential. In this article, we study the thermoelectric coefficients of an interacting hot and dense hadron gas using the relativistic Boltzmann transport equation under the relaxation time approximation. We discuss the thermoelectric properties within different frameworks of hardon resonance gas models. In the presence of an external magnetic field, the thermoelectric coefficients become anisotropic, which leads to Hall-like thermoelectric coefficients, namely Nernst coefficients, along with the magneto-Seebeck coefficients. For the first time, we also estimate the Thomson coefficient of the medium, which comes into the picture due to the temperature dependence of the Seebeck coefficient of the medium. In the context of studying the thermoelectric generator performance, we calculate the values of the thermoelectric figure of merit of the medium.

hep-ph↗

arXiv2025

Applicability of Hydrodynamics in Hadronic Phase of Heavy-Ion Collisions

The hadronic phase and its dynamics in relativistic heavy-ion collisions are topics of immense discussion. The hadronic phase contains various massive hadrons with an abundance of the lightest hadron, i.e., $π$-mesons (pions). In this paper, we consider that pions are in thermal equilibrium in the hadronic phase and use second-order viscous hydrodynamics for a medium of massive pions to obtain its expansion to the boundary of the kinetic freeze-out. We achieve the kinetic freeze-out boundary with the Knudsen number $Kn>1$ limit. When this condition is met, hydrodynamics expansion breaks down, and the mean free path becomes sufficiently large in comparison with the system size so that the particle yields are preserved. Further, we investigate the effect of the massive fluid on the resonance particle yields, including re-scattering and regeneration, along with the natural decay widths of the resonances. The resonances can play an essential role in determining the characteristics of the hadronic phase as they have sufficiently small lifetimes, which may be comparable to the hadronic phase lifetime. In the current study, we predict the hadronic phase lifetime, which is further used to determine the $K^*(892)^0/K$, $ϕ(1020)/K$, and $ρ(770)^0/π$ yield ratios at the kinetic freeze-out. We calculate these ratios as a function of charged particle multiplicity and transverse momentum and compare the findings with experimental data. Our calculations qualitatively agree with the experimental data, indicating a possible hydrodynamical evolution of the hadronic phase.

hep-ph↗

arXiv2025

Prompt and non-prompt production of charm hadrons in proton-proton collisions at the Large Hadron Collider using machine learning

In this contribution, we use machine learning (ML) based models to separate the prompt and non-prompt production of heavy flavour hadrons, such as $D^0$ and J/$ψ$, in proton-proton collisions at LHC energies. For this purpose, we use PYTHIA~8 to generate events, which provides a good qualitative agreement with experimental measurements of charm hadron production. The input features for the ML models are experimentally measurable. The prediction accuracy of the ML models used in this study reaches up to 99\%. The ML models can be useful in providing precise track-level identification, which is not possible in experiments with traditional methods. The contribution also discusses future applications of the ML models to understand the production of prompt and non-prompt heavy quark hadrons.

hep-ph↗

arXiv2025

Exploring the effects of $α$-clustered structure of $^{16}O$ nuclei in anisotropic flow fluctuations in $^{16}O$-$^{16}O$ collisions at the LHC within a CGC+Hydro framework

In this paper, we explore the effects of the presence of clustered nuclear structure of $^{16}O$ in the final state elliptic flow fluctuations through $^{16}O$-$^{16}O$ collisions at $\sqrt{s_{\rm NN}}=7$ TeV within a hybrid model, IPGlasma+MUSIC+iSS+ UrQMD. We compare the results of elliptic flow fluctuations using $α$-clustered nuclear structure to the Woods-Saxon nuclear profile having no clustered structure. We observe a significant difference in the elliptic flow fluctuations, which arise due to the consideration of a clustered nuclear structure of $^{16}O$.

hep-ph↗

arXiv2025

Design and development of advanced Al-Ti-V alloys for beampipe applications in particle accelerators

The present investigation reports the design and development of an advanced material with a high figure of merit (FoM) for beampipe applications in particle accelerators by bringing synergy between computational and experimental approaches. Machine learning algorithms have been used to predict the phase(s), low density, and high radiation length of the designed Al-Ti-V alloys. Al-Ti-V alloys with various compositions for single-phase and dual-phase mixtures, liquidus temperature, and density values are obtained using the Latin hypercube sampling method in TC Python Thermo-Calc software. The obtained dataset is utilized to train the machine-learning algorithms. Classification algorithms such as XGBoost and regression models such as Linear Regression and Random Forest regressor have been used to compute the number of phases, radiation length, and density respectively. The XGBoost algorithms show an accuracy of $98\%$, the Linear regression model shows an accuracy of $94\%$, and the Random Forest regressor model is accurate up to $99\%$. The developed Al-Ti-V alloys exhibit high radiation length as well as a good combination of high elastic modulus and toughness due to the synergistic effect of the presence of hard $Al_3Ti$ phase along with a minor volume fraction of FCC $(Al)_{ss}$ solid solution phase mixture. The comparison of our alloys, alloy-1 ($Al_{75.2}Ti_{22.8}V_{2}$) and alloy-2 ($Al_{89}Ti_{10}V_{1}$) shows an increase in the radiation length by seven-times and a decrease in the density by two to three times as compared to stainless steel 304, the preferred material for constructing beampipes in low-energy particle accelerators. Further, we experimentally verify the elastic modulus of the alloy-1 and compute the FoM equal to 0.416, which is better than other existing materials for beampipes in low-energy experiments.

physics.acc-ph↗

arXiv2025

Probing strangeness with event topology classifiers in pp collisions at energies available at the CERN Large Hadron Collider with the rope hadronization mechanism in PYTHIA

In relativistic heavy-ion collisions, the formation of a deconfined and thermalized state of partons, known as quark-gluon plasma (QGP), leads to enhanced production of strange hadrons in contrast to proton-proton (pp) collisions, which are taken as baseline. This observation is known as strangeness enhancement in heavy-ion collisions and is considered one of the important signatures that can signify the formation of QGP. However, in addition to strangeness enhancement, recent measurements hint at observing several heavy-ion-like features in high multiplicity pp collisions at energies available at the CERN Large Hadron Collider. Alternatively, event shape observables, such as transverse spherocity, transverse sphericity, charged particle flattenicity, and relative transverse activity classifiers, can fundamentally separate hard interaction-dominated jetty events from soft isotropic events. These features of event shape observables can probe the observed heavy-ion-like features in pp collisions with significantly reduced selection bias and can bring all collision systems on equal footing. In this article, we present an extensive summary of the strange particle ratios to pions as a function of different event classifiers using the PYTHIA~8 model with color reconnection and rope hadronization mechanisms to understand the microscopic origin of strangeness enhancement in pp collisions and also prescribe the applicability of these event classifiers in the context of strangeness enhancement. Charged particle flattenicity is found to be most suited for the study of strangeness enhancement, and it shows a quantitative enhancement similar to that seen for the analysis based on the number of multi-parton interactions.

hep-ph↗

arXiv2025

Investigating radial flow-like effects via pseudorapidity and transverse spherocity dependence of particle production in pp collisions at the LHC

Recent observations of quark-gluon plasma (QGP) like signatures in high multiplicity proton-proton (pp) collisions, have compelled the heavy-ion physics community to re-examine small collision systems for proper baseline studies. Event-shape-based studies in pp collisions have succeeded to a certain extent in identifying the rare events mimicking such heavy-ion-like behaviour. In this study, we incorporate PYTHIA8 and AMPT to study radial flow-like signatures in pp collisions at $\sqrt{s} = 13$ TeV as a function of transverse spherocity and pseudorapidity. The selection of softer events possibly carrying heavy-ion-like features is performed using the transverse spherocity event-shape observable. As the particle production mechanism in midrapidity differs greatly from the forward rapidity, a pseudorapidity-dependent study is meaningful. Keeping ALICE 3 upgrades at the LHC in mind, this study aims to demonstrate the transverse spherocity and pseudorapidity dependence of the mean transverse momentum, particle ratios, and kinetic freezeout parameters in pp collisions at $\sqrt{s}$ = 13 TeV using PYTHIA8. We observe that the isotropic events show enhanced radial-flow effects in all multiplicity classes, however, the jetty events show signatures of the radial flow-like effects only in high-multiplicity events. For the first time, we show the transverse spherocity and pseudorapidity dependence of partonic modification factor in pp collisions, which clearly shows that by choosing transverse spherocity, one can directly probe the radial flow-like effects in pp collisions at the LHC.

hep-ph↗

arXiv2025

Can charm fluctuation be a better probe to study QCD critical point?

We study the diffusion properties of an interacting hadron gas and evaluate the diffusion coefficient matrix for the baryon, strange, electric, and charm quantum numbers. For the first time, this study sheds light on the charm current and estimates the diffusion matrix coefficient for the charmed states by treating them as a part of the quasi-thermalized medium. We explore the diffusion matrix coefficient as a function of temperature and center-of-mass energy. A van der Waals-like interaction is assumed between the hadrons, including attractive and repulsive interactions. The calculation of diffusion coefficients is based on relaxation time approximation to the Boltzmann transport equation. A good agreement with available model calculations is observed in the hadronic limit. To conclude the study, we discuss, with a detailed explanation, that charm fluctuation is expected to be a better tool for probing the QCD critical point.

hep-ph↗

arXiv2024

Electric field induction in quark-gluon plasma due to thermoelectric effects

Relativistic heavy-ion collisions produce quark-gluon plasma (QGP), which is locally thermalized. Due to electrically charged particles (quarks), QGP exhibits interesting thermoelectric phenomena during its evolution, resulting in an electromagnetic (EM) field in the medium. In this study, for the first time, we estimate the induced electric field in QGP due to the thermoelectric effect. This phenomenon can induce an EM field even in QGP produced by the head-on heavy-ion collision. In peripheral heavy-ion collisions, the presence of a spectator current generates a transient magnetic field at the early stage, which disrupts the isotropy of the induced electric field. For the numerical estimation, we use a quasiparticle-based model that incorporates the lattice quantum chromodynamics equation of state for QGP. The induced electric field is estimated with cooling rates derived from Gubser hydrodynamic flow. Thermoelectric coefficients such as Seebeck, magneto-Seebeck, and Nernst coefficients play a crucial role in determining the induced field. Additionally, we account for the temperature evolution of QGP using different hydrodynamic cooling rates to calculate the transport coefficients. We also estimate the transport coefficients and the induced electric field in the presence of an external time-varying magnetic field, including the quantum effect of Landau quantization, and explore the effects of the intensity and decay parameter of the magnetic field on the induced electric field. Our findings reveal that the space-time profile of the induced electric field is zero at the center and increases as we go away from the center. During the early stages of evolution, the electric field can reach a maximum value of $eE \approx 1~m_π^2$, decreasing in strength over time.

hep-ph↗

arXiv2024

Dynamics of Hot QCD Matter 2024 -- Hard Probes

The hot and dense QCD matter, known as the Quark-Gluon Plasma (QGP), is explored through heavy-ion collision experiments at the LHC and RHIC. Jets and heavy flavors, produced from the initial hard scattering, are used as hard probes to study the properties of the QGP. Recent experimental observations on jet quenching and heavy-flavor suppression have strengthened our understanding, allowing for fine-tuning of theoretical models in hard probes. The second conference, HOT QCD Matter 2024, was organized to bring the community together for discussions on key topics in the field. This article comprises 15 sections, each addressing various aspects of hard probes in relativistic heavy-ion collisions, offering a snapshot of current experimental observations and theoretical advancements. The article begins with a discussion on memory effects in the quantum evolution of quarkonia in the quark-gluon plasma, followed by an experimental review, new insights on jet quenching at RHIC and LHC, and concludes with a machine learning approach to heavy flavor production at the Large Hadron Collider.

nucl-ex↗

arXiv2024

Dynamics of Hot QCD Matter 2024 -- Bulk Properties

The second Hot QCD Matter 2024 conference at IIT Mandi focused on various ongoing topics in high-energy heavy-ion collisions, encompassing theoretical and experimental perspectives. This proceedings volume includes 19 contributions that collectively explore diverse aspects of the bulk properties of hot QCD matter. The topics encompass the dynamics of electromagnetic fields, transport properties, hadronic matter, spin hydrodynamics, and the role of conserved charges in high-energy environments. These studies significantly enhance our understanding of the complex dynamics of hot QCD matter, the quark-gluon plasma (QGP) formed in high-energy nuclear collisions. Advances in theoretical frameworks, including hydrodynamics, spin dynamics, and fluctuation studies, aim to improve theoretical calculations and refine our knowledge of the thermodynamic properties of strongly interacting matter. Experimental efforts, such as those conducted by the ALICE and STAR collaborations, play a vital role in validating these theoretical predictions and deepening our insight into the QCD phase diagram, collectivity in small systems, and the early-stage behavior of strongly interacting matter. Combining theoretical models with experimental observations offers a comprehensive understanding of the extreme conditions encountered in relativistic heavy-ion and proton-proton collisions.

nucl-th↗

arXiv2024

Multiplicity, transverse momentum and pseudorapidity dependence of open-heavy flavored hadron production in proton+proton collisions at $\sqrt{s}$= 13 TeV using PYTHIA8

Recently, with the upgradation of LHC, it is realized that study of heavy-flavored hadrons, namely $Λ_{c}^{+}$ and $\rm{D}^{0}$ in hadronic collisions, could reveal the possibility of thermalization of charm quarks. With this motivation, we study the production dynamics of these hadrons using a pQCD-inspired Monte Carlo event generator called PYTHIA8 in proton+proton collisions at $\sqrt{s}$ = 13 TeV. The production dynamics of these hadrons are analyzed through charged-particle multiplicity, transverse momentum, and pseudorapidity. With the help of the established PYTHIA8 tunes to mimic the behavior of flow-like features, we investigated the variation of effective temperature and degree of non-extensivity using thermodynamically consistent non-extensive Tsallis statistics. We further attempted to establish a connection between the initial state and final state by estimating the correlation between the number of multi-partonic interactions ($\rm{n}_{MPI}$) with the Knudsen number.

hep-ph↗

arXiv2024

Anisotropic flow fluctuation as a possible signature of clustered nuclear geometry in O-O collisions at the Large Hadron Collider

Nuclei having $4n$ number of nucleons are theorized to possess clusters of $α$ particles ($^4$He nucleus). The Oxygen nucleus ($^{16}$O) is a doubly magic nucleus, where the presence of an $α$-clustered nuclear structure grants additional nuclear stability. In this study, we exploit the anisotropic flow coefficients to discern the effects of an $α$-clustered nuclear geometry with respect to a Woods-Saxon nuclear distribution in O--O collisions at $\sqrt{s_{\rm NN}}=7$ TeV using a hybrid of IP-Glasma + MUSIC + iSS + UrQMD models. In addition, we use the multi-particle cumulants method to measure anisotropic flow coefficients, such as elliptic flow ($v_{2}$) and triangular flow ($v_{3}$), as a function of multiplicity class. Anisotropic flow fluctuations, which are expected to be larger in small collision systems, are also studied for the first time in O--O collisions. It is found that an $α$-clustered nuclear distribution gives rise to an enhanced value of $v_{2}$ and $v_3$ for the low-multiplicity events. Consequently, a rise in $v_3/v_2$ is also observed for the 0--10\% multiplicity class. Further, for $α$-clustered O--O collisions, fluctuations of $v_{2}$ are larger for the highest multiplicity events, which decrease as the final-state multiplicity decreases. In contrast, for a Woods-Saxon $^{16}$O nucleus, $v_{2}$ fluctuations show an opposite behavior with decreasing multiplicity. When confronted with experimental data, this study may reveal the importance of the nuclear density profile on the discussed observables and provide physics validation for the hybrid model discussed in this work.

nucl-th↗

arXiv2024

Heavy Flavor Production at the Large Hadron Collider: A Machine Learning Approach

Charmonia suppression has been considered as a smoking gun signature of quark-gluon plasma. However, the Large Hadron Collider has observed a lower degree of suppression as compared to the Relativistic Heavy Ion Collider energies, due to regeneration effects in heavy-ion collisions. Though proton collisions are considered to be the baseline measurements to characterize a hot and dense medium formation in heavy-ion collisions, LHC proton collisions with its new physics of heavy-ion-like QGP signatures have created new challenges. To understand this, the inclusive charmonia production at the forward rapidities in the dimuon channel is compared with the corresponding measurements in the dielectron channel at the midrapidity as a function of final state charged particle multiplicity. None of the theoretical models quantitatively reproduce the experimental findings leaving out a lot of room for theory. To circumvent this and find a reasonable understanding, we use machine learning tools to separate prompt and nonprompt charmonia and open charm mesons using the decay daughter track properties and the decay topologies of the mother particles. Using PYTHIA8 data, we train the machine learning models and successfully separate prompt and nonprompt charm hadrons from the inclusive sample to study various directions of their production dynamics. This study enables a domain of using machine learning techniques, which can be used in the experimental analysis to better understand charm hadron production and build possible theoretical understanding.

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↗

arXiv2024

Impact of Medium Anisotropy on Quarkonium Dissociation and Regeneration

Quarkonium production in ultra-relativistic collisions plays a crucial role in probing the existence of hot QCD matter. This study explores quarkonia states dissociation and regeneration in the hot QCD medium while considering momentum anisotropy. The net quarkonia decay width ($Γ_{D}$) arises from two essential processes: collisional damping and gluonic dissociation. The quarkonia regeneration includes the transition from octet to singlet states within the anisotropic medium. Our study utilizes a medium-modified potential that incorporates anisotropy via particle distribution functions. This modified potential gives rise to collisional damping for quarkonia due to the surrounding medium, as well as the transition of quarkonia from singlet to octet states due to interactions with gluons. Furthermore, we employ the detailed balance approach to investigate the regeneration of quarkonia within this medium. Our comprehensive analysis spans various temperature settings, transverse momentum values, and anisotropic strengths. Notably, we find that, in addition to medium temperatures and heavy quark transverse momentum, anisotropy significantly influences the dissociation and regeneration of various quarkonia states.

hep-ph↗

arXiv2024

Thermodynamics of a rotating hadron resonance gas with van der Waals interaction

Studying the thermodynamics of the systems produced in ultra-relativistic heavy-ion collisions is crucial in understanding the QCD phase diagram. Recently, a new avenue has opened regarding the implications of large initial angular momentum and subsequent vorticity in the medium evolution in high-energy collisions. This adds a new type of chemical potential into the partonic and hadronic systems, called the rotational chemical potential. We study the thermodynamics of an interacting hadronic matter under rotation, formed in an ultra-relativistic collision. We introduce attractive and repulsive interactions through the van der Waals equation of state. Thermodynamic properties like the pressure ($P$), energy density ($\varepsilon$), entropy density ($s$), trace anomaly ($(\varepsilon - 3P)/T^{4}$), specific heat ($c_{\rm v}$) and squared speed of sound ($c_{\rm s}^{2}$) are studied as functions of temperature ($T$) for zero and finite rotation chemical potential. The conserved charge fluctuations, which can be quantified by their respective susceptibilities, are also studied. The rotational (spin) density corresponding to the rotational chemical potential is explored. In addition, we explore the possible liquid-gas phase transition in the hadron gas with van der Waals interaction in the $T$ -- $ω$ phase space.

hep-ph↗

arXiv2024

A machine learning-based study of open-charm hadrons in proton-proton collisions at the Large Hadron Collider

n proton-proton and heavy-ion collisions, the study of charm hadrons plays a pivotal role in understanding the QCD medium and provides an undisputed testing ground for the theory of strong interaction, as they are mostly produced in the early stages of collisions via hard partonic interactions. The lightest open-charm, $D^{0}$ meson ($c\Bar{u}$), can originate from two separate sources. The prompt $D^{0}$ originates from either direct charm production or the decay of excited open charm states, while the nonprompt stems from the decay of beauty hadrons. In this paper, using different machine learning (ML) algorithms such as XGBoost, CatBoost, and Random Forest, an attempt has been made to segregate the prompt and nonprompt production modes of $D^{0}$ meson signal from its background. The ML models are trained using the invariant mass through its hadronic decay channel, i.e., $D^{0}\rightarrowπ^{+} K^{-}$, pseudoproper time, pseudoproper decay length, and distance of closest approach of $D^{0}$ meson, using PYTHIA8 simulated $pp$ collisions at $\sqrt{s}=13~\rm{TeV}$. The ML models used in this analysis are found to retain the pseudorapidity, transverse momentum, and collision energy dependence. In addition, we report the ratio of nonprompt to prompt $D^{0}$ yield, the self-normalized yield of prompt and nonprompt $D^{0}$ and explore the charmonium, $J/ψ$ to open-charm, $D^{0}$ yield ratio as a function of transverse momenta and normalized multiplicity. The observables studied in this manuscript are well predicted by all the ML models compared to the simulation.

hep-ph↗