Neelkamal Mallick

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• Doctor of Philosophy
• PostDoc Position at University of Jyväskylä

RHIC and LHC plan to inject $^{16}\rm O$ nuclei with a focus to investigate collectivity and the origin of quark-gluon plasma signatures in small collision systems. $^{16}\rm O$ nuclei is known to possess clusters of $\alpha$-particles ($^{4}\rm He$) inside the nucleus. In this paper, we study the anisotropic flow coefficients such as elliptic flow...

Studies of heavy-quark (charm and beauty) production in hadronic and nuclear collisions provide excellent testing grounds for the theory of strong interaction, quantum chromodynamics. Heavy-quarks are produced predominantly in the initial hard partonic interactions, allowing them to witness the entire evolution process. The charm hadrons are produc...

Studying heavy-flavor jets in pp collision is important since they can test pQCD calculations and be used as a reference for heavy-ion collisions. Jets in this analysis are reconstructed from charged particles using the anti-$k_{\mathrm{T}}$ algorithm with a resolution parameter $R=$ 0.4 and with pseudorapidity $|\eta|<$ 0.5. Beauty jets are tagged...

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/$\psi$, 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...

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 $\alpha$-clustered nuclear struc...

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 ( p p ) collisions, which are taken as baseline. This observation is known as strangeness enhancement in heavy-ion collisions and is con...

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 s...

We developed a deep learning feed-forward network for estimating elliptic flow (v2) coefficients in heavy-ion collisions from RHIC to LHC energies. The success of our model is mainly the estimation of v2 from final state particle kinematic information and learning the centrality and the transverse momentum (pT) dependence of v2 in wide pT regime. T...

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...

In relativistic heavy-ion collisions, the formation of a deconfined and thermalized state of partons, known as quark-gluon plasma, 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 o...

In 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 u ¯ ), can ori...

Nuclei having $4n$ number of nucleons are theorized to possess clusters of $\alpha$ particles ($^4$He nucleus). The Oxygen nucleus ($^{16}$O) is a doubly magic nucleus, where the presence of an $\alpha$-clustered nuclear structure grants additional nuclear stability. In this study, we exploit the anisotropic flow coefficients to discern the effects...

Long-range multi-particle correlations in heavy-ion collisions have shown conclusive evidence of the hydrodynamic behavior of strongly interacting matter, and are associated with the final-state azimuthal momentum anisotropy. In small collision systems, azimuthal anisotropy can be influenced by the hadronization mechanism and residual jet-like corr...

Studies related to J / ψ meson, a bound state of charm and anticharm quarks ( c c ¯ ), in heavy-ion collisions, provide genuine testing grounds for the theory of strong interaction, quantum chromodynamics. To better understand the underlying production mechanism, cold nuclear matter effects, and influence from the quark-gluon plasma, baseline measu...

To understand the true origin of flowlike signatures and applicability of hydrodynamics in small collision systems, effects of soft QCD dynamics, the sensitivity of jetlike correlations, and nonequilibrium effects, efforts are being made to perform p-O and O-O collisions at the LHC and RHIC energies. It is equally interesting to look into the possi...

Studies related to $\rm{J}/\psi$ meson, a bound state of charm and anti-charm quarks ($c\bar{c}$), in heavy-ion collisions, provide genuine testing grounds for the theory of strong interaction, quantum chromodynamics (QCD). To better understand the underlying production mechanism, cold nuclear matter effects, and influence from the quark-gluon plas...

Recent developments of a deep learning feed-forward network for estimating elliptic flow (v2) coefficients in heavy-ion collisions have shown the prediction power of this technique. The success of the model is mainly the estimation of v2 from final-state particle kinematic information and learning the centrality and transverse momentum (pT) depende...

To understand the true origin of flow-like signatures and applicability of hydrodynamics in small collision systems, effects of soft QCD dynamics, the sensitivity of jet-like correlations, and non-equilibrium effects, efforts are being made to perform \textit{p}--O and O--O collisions at the LHC and RHIC energies. It is equally interesting to look...

Anisotropic flow is accredited to have effects from the initial state geometry and fluctuations in the nuclear overlap region. The elliptic flow (v2) and triangular flow (v3) coefficients of the final state particles are expected to have influenced by eccentricity (ϵ2) and triangularity (ϵ3) of the participants, respectively. In this work, we study...

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...

The discovery of hot and dense quantum chromodynamics (QCD) matter, known as Quark–Gluon Plasma (QGP), is an essential milestone in understanding the finite temperature QCD medium. Experimentalists around the world collect an unprecedented amount of data in heavy ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Labo...

Oxygen ( $$^{16}$$ 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 $$\sqrt{s_\mathrm{{NN}}}$$ s 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 s...

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, a...

Anisotropic flow is accredited to have effects from the initial state geometry and fluctuations in the nuclear overlap region. The elliptic flow ($v_2$) and triangular flow ($v_3$) coefficients of the final state particles are expected to have influenced by eccentricity ($\varepsilon_2$) and triangularity ($\varepsilon_3$) of the nucleons, respecti...

Machine learning techniques have been employed for the high energy physics 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 (v2) in heavy-ion collisions at the RHIC and LHC energies. A novel method is developed to process the input o...

Transverse spherocity is an event shape observable, which separates the events based on their geometrical shapes. In this work, we use transverse spherocity to study the identified light flavor production in heavy-ion collisions using A Multi-Phase Transport (AMPT) model. We obtain the elliptic flow coefficients for pions, kaons and protons in Pb+P...

Particle production and event topology are very strongly correlated in high-energy hadronic and nuclear collisions. Event topology is decided by the underlying particle production dynamics and medium effects. Transverse spherocity is an event shape observable, which has been used in pp and heavy-ion collisions to separate the events based on their...

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 proce...

Particle production and event topology are very strongly correlated in high-energy hadronic and nuclear collisions. Event topology is decided by the underlying particle production dynamics and medium effects. Transverse spherocity is an event shape observable, which has been used in pp and heavy-ion collisions to separate the events based on their...

Background: Recent work showed that the temporal growth of the novel coronavirus disease (COVID-19) follows a sub-exponential power-law scaling whenever effective control interventions are in place. Taking this into consideration, we present a new phenomenological logistic model that is well-suited for such power-law epidemic growth. Methods: We em...

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 f...

One of the event shape observables, the transverse spherocity ($S_0$), has been studied successfully in small collision systems such as proton-proton collisions at the LHC as a tool to separate jetty and isotropic events. It has a unique capability to distinguish events based on their geometrical shapes. In this work, we report the first implementa...

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 is in between those produced in pp and p+Pb collisions, the study of global properties in O+O collisions may provide a...

Background Recent work showed that the temporal growth of the novel coronavirus disease (COVID-19) follows a sub-exponential power-law scaling whenever effective control interventions are in place. Taking this into consideration, we present a new phenomenological logistic model that is well-suited for such power-law epidemic growth. Methods We emp...

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 that has a significant impact on the final state particle production. However, the calculation of such a quantity is n...

Transverse spherocity is an event shape observable, which has got a unique capability to separate the events based on their geometrical shapes. In this work, we use transverse spherocity to study the identified light flavor production in heavy-ion collisions using A Multi-Phase Transport (AMPT) model. We obtain the elliptic flow coefficients for pi...

Transverse spherocity is an event shape observable having a unique capability to separate the events based on their geometrical shapes. Recent results from experiments at the LHC suggest that transverse spherocity is an important event classifier in small collision systems. In this work, we use transverse spherocity for the first time in heavy-ion...

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 near...

Transverse spherocity is an event shape observable having a very unique capability to separate the events based on their geometrical shapes. Recent results from experiments at the LHC suggest that transverse spherocity is an important event classifier in small collision systems. In this work, we use transverse spherocity for the first time in heavy...

Transverse spherocity, an event shape observable, has a very unique capability to separate the events based on their geometrical shape, i.e. jetty and isotropic. In this work, we use transverse spherocity for the first time in heavy-ion collisions using A Multi-Phase Transport Model (AMPT). We obtain the transverse momentum spectra, integrated yiel...