arXiv subjects

Satyajit Jena

Publications and source records attributed to Satyajit Jena.

At least 19 recordsLinked to original sources

arXiv2026

A Cosmic Muon Tomography System with Machine Learning based Momentum Measurement for Multi-Object Reconstruction and Material Characterization

Cosmic muon tomography is a powerful non-destructive imaging technique for inspecting dense and shielded materials through multiple Coulomb scattering. In this work, we present the design, simulation, and performance evaluation of a complete muon tomography system comprising six scintillator-strip tracking stations for trajectory reconstruction and a four-station magnetic spectrometer for muon momentum estimation. The detector geometry is implemented in the GEANT4 framework and optimized for object localization and material characterization. The reconstructed momentum is combined with the scattering angle to define the scattering density $ρ_s = {(θp)^2}/{L_{\mathrm{eff}}}$, which enhances sensitivity to material-dependent scattering. Point-of-Closest-Approach (PoCA) reconstruction is used to estimate scattering locations within the imaging volume. To detect and separate multiple unknown objects, Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) is applied to the reconstructed PoCA cloud. Cluster-level scattering and geometric features are then extracted for object characterization. The proposed framework enables object detection, localization, volume estimation, shape reconstruction, and material ranking within a unified analysis pipeline. Simulation studies with multiple objects of different compositions demonstrate accurate reconstruction of object positions and geometries, while providing reliable material discrimination based on scattering density. The developed system offers a scalable approach for next-generation cosmic muon tomography applications in security screening, nuclear waste characterization, and non-destructive inspection.

physics.ins-det↗

arXiv2025

A comparative study of hadron-hadron and heavy-ion collision using the $q$-Weibull distribution function

Recent results on multiplicity dependent transverse momentum spectra data in different high multiplicity $pp$ collision have opened a window to search for QGP like medium in hadron-hadron collision. In this work we have performed a comparative study of charged hadron spectra in $pp$, $pPb$ and $PbPb$ collision using the $q$ parameter obtained from the $q$-Weibull distribution function. We observed a disparity in the trend of $q$ parameter in high $p_T$ range.

hep-ph↗

arXiv2025

Probing Planck scale effects on absolute mass limit in neutrino flavor evolution

This work explores how the generalized uncertainty principle, a theoretical modification of the Heisenberg uncertainty principle inspired by quantum gravity, affects neutrino flavor oscillations. By extending the standard two-flavor neutrino model, we show that the oscillation probability acquires an additional phase term that depends on the {square roots of the individual neutrino masses}, introducing new features beyond the conventional mass-squared differences. To account for the non-Hermitian nature of the resulting dynamics, we employ parity-time ($PT$) symmetric quantum mechanics, which allows for consistent descriptions of systems with {balanced gain and loss mechanisms}. We analyze the feasibility of observing these effects in current and future neutrino experiments, such as DUNE, JUNO, IceCube, ORCA--KM3NeT, MINOS, Daya Bay, Hyper-Kamiokande, and KATRIN, and find that the predicted modifications could fall within the sensitivity of current experiments. Moreover, we propose that analog quantum simulation platforms, such as cold atoms, trapped ions, and photonic systems, offer a promising route to test these predictions under controlled conditions. Our findings suggest that neutrino oscillations may serve as an effective probe of quantum gravity effects, providing a novel connection between fundamental theory and experimental observables.

hep-ph↗

arXiv2024

Comparative Study of tau neutrinos event numbers in INO and JUNO detectors from Bartol Flux

To expand our understanding of neutrino physics, scientific researchers of astroparticle Physics directs their goal of detecting atmospheric tau neutrinos in the GeV range. The effort will fundamentally unlock the nature of these elusive particles while also investigating muon neutrinos and tau neutrino oscillations. The Jiangmen Underground Neutrino Observatory (JUNO), which has already started its operations in 2024, and the India-based Neutrino Observatory (INO), which is not active right now but has future objectives in conducting research, have both emerged as key players in this field. These experiments used theoretical and experimental methodologies to understand the properties and behaviour of atmospheric tau neutrinos. The JUNO experiment, which has an estimated ability to detect around 50 events per year, and the INO, which used an impressive 50,000-ton iron slab as a detector, will contribute significantly in this domain. The detection of all tau neutrinos charged-current (CC) interactions with the detection material, which is divided into former and later events based on the timeline corresponding to scattering and capture in the detector; moreover, the KamLAND experiment is also capable of detecting these tau neutrinos decays, however, in smaller proportions, which could be possibly confused with background signals emerging from oscillations. This has been studied for both experiments for tau neutrinos nuclei cross-sections, and its standard value is taken as a base for calculations. Both INO and JUNO have 5 sigma sensitivity, which was exposed for 5 to 10 years.

hep-ph↗

arXiv2023

Study of Isothermal Compressibility and Speed of Sound in the Hadronic Matter Formed in Heavy-Ion Collision using Unified Formalism

The thermodynamical quantities and response functions are useful to describe the particle production in heavy-ion collisions as they reveal crucial information about the produced system. While the study of isothermal compressibility provides an inference about the viscosity of the medium, speed of sound helps in understanding the equation of state. With an aim towards understanding the system produced in the heavy-ion collision, we have made an attempt to study isothermal compressibility and speed of sound as function of charged particle multiplicity in heavy-ion collisions at $\sqrt{s_{NN}}$ = $2.76$ TeV, $5.02$ TeV, and $5.44$ TeV using unified formalism.

hep-ph↗

arXiv2023

Study of density independent scattering angle and energy loss for low- to high-Z material using Muon Tomography

Cosmic ray muon, as they pass through a material, undergoes Multiple Coulomb Scattering (MCS). The analysis of muon scattering angle in a material provides us with an opportunity to study the characteristics of material and its internal 3D structure as the scattering angle depends on the atomic number, the density of the material, and the thickness of the medium at a given energy. We have used the GEANT4 toolkit to study the scattering angle and utilize this information to identify the material. We have analyzed the density dependent $\&$ density independent scattering angle and observed various patterns for distinct periods in the periodic table.

hep-ex↗

arXiv2023

A unified statistical approach to explain the transverse momentum spectra in hadron-hadron collision

Thermodynamical description of the system created during high energy collision requires a proper thermodynamical framework to study the distribution of particles. In this work, we have attempted to explain the transverse momentum spectra of charged hadrons formed in $pp$ collision at different energies using the Pearson statistical framework. This formalism has been proved to nicely explain the spectra of particles produced in soft processes as well hard scattering processes in a consistent manner. For this analysis, we have used the highest available range of $p_T$ published by experiments to verify the applicability of Pearson statistical framework at large $p_T$.

hep-ph↗

arXiv2023

The theoretical description of the transverse momentum spectra: a unified model

Analysis of transverse momentum distributions is a useful tool to understand the dynamics of relativistic particles produced in high energy collision. Finding a proper distribution function to approximate the spectra is a vastly developing area of research in particle physics. In this work, we have provided a detailed theoretical description of the unified statistical framework in high energy physics. We have tested the applicability of this framework on experimental data by analysing the transverse momentum spectra of pion produced in heavy-ion collision at RHIC and LHC. We have also attempted to explain the transverse momentum spectra of charged hadrons formed in pp collision at different energies using the unified statistical framework. This formalism has been proved to nicely explain the spectra of particles produced in soft processes as well hard scattering processes in a consistent manner.

hep-ph↗

arXiv2022

Jet characterization in Heavy Ion Collisions by QCD-Aware Graph Neural Networks

The identification of jets and their constituents is one of the key problems and challenging task in heavy ion experiments such as experiments at RHIC and LHC. The presence of huge background of soft particles pose a curse for jet finding techniques. The inabilities or lack of efficient techniques to filter out the background lead to a fake or combinatorial jet formation which may have an errorneous interpretation. In this article, we present Graph Reduction technique (GraphRed), a novel class of physics-aware and topology-based attention graph neural network built upon jet physics in heavy ion collisions. This approach directly works with the physical observables of variable-length set of final state particles on an event-by-event basis to find most likely jet-induced particles in an event. This technique demonstrate the robustness and applicability of this method for finding jet-induced particles and show that graph architectures are more efficient than previous frameworks. This technique exhibit foremost time a classifier working on particle-level in each heavy ion event produced at the LHC. We present the applicability and integration of the model with current jet finding algorithms such as FastJet.

physics.data-an↗

arXiv2022

Model comparison of the transverse momentum spectra of charged hadrons produced in $PbPb$ collision at $\sqrt{s_{NN}} = 5.02$ TeV

Transverse Momentum, $p_T$, spectra is of prime importance in order to extract crucial information about the evolution dynamics of the system of particles produced in the collider experiments. In this work, the transverse momentum spectra of charged hadrons produced in $PbPb$ collision at $5.02$ TeV has been analyzed using different distribution functions in order to gain strong insight into the information that can be extracted from the spectra. We have also discussed the applicability of Pearson distribution on the spectra of charged hadron at $5.02$ TeV.

hep-ph↗

arXiv2021

A unified formalism to study the pseudorapidity spectra in heavy-ion collision

The pseudorapidity distribution of charged hadron over a wide $η$ range gives us crucial information about the dynamics of particle production. Constraint on the detector acceptance, particularly at forward rapidities, demands a proper distribution function to extrapolate the pseudorapidity distribution to large $η$. In this work, we have proposed a phenomenological model based on Pearson statistical framework to study the pseudorapidity distribution. We have analyzed and fit data of charged hadrons produced in $Pb-Pb$ collision at $2.76$ TeV and $Xe-Xe$ collision at $5.44$ TeV using the proposed model.

hep-ph↗

arXiv2021

Shower Identification in Calorimeter using Deep Learning

Pions constitute nearly $70\%$ of final state particles in ultra high energy collisions. They act as a probe to understand the statistical properties of Quantum Chromodynamics (QCD) matter i.e. Quark Gluon Plasma (QGP) created in such relativistic heavy ion collisions (HIC). Apart from this, direct photons are the most versatile tools to study relativistic HIC. They are produced, by various mechanisms, during the entire space-time history of the strongly interacting system. Direct photons provide measure of jet-quenching when compared with other quark or gluon jets. The $π^{0}$ decay into two photons make the identification of non-correlated gamma coming from another process cumbersome in the Electromagnetic Calorimeter. We investigate the use of deep learning architecture for reconstruction and identification of single as well as multi particles showers produced in calorimeter by particles created in high energy collisions. We utilize the data of electromagnetic shower at calorimeter cell-level to train the network and show improvements for identification and characterization. These networks are fast and computationally inexpensive for particle shower identification and reconstruction for current and future experiments at particle colliders.

physics.data-an↗

arXiv2021

A unified formalism to study $soft$ as well as $hard$ part of the transverse momentum spectra

Transverse momentum $p_T$ spectra of final state particles produced in high energy heavy-ion collision can be divided into two distinct regions based on the difference in the underlying particle production process. We have provided a unified formalism to explain both low- and high-$p_T$ regime of spectra in a consistent manner. The $p_T$ spectra of final state particles produced at RHIC and LHC energies have been analysed using unified formalism to test its applicability at different energies, and a good agreement with the data is obtained across all energies. Further, the prospect of extracting the elliptic flow coefficient directly from the transverse momentum spectra is explored.

hep-ph↗

arXiv2020

Particle Track Reconstruction using Geometric Deep Learning

Muons are the most abundant charged particles arriving at sea level originating from the decay of secondary charged pions and kaons. These secondary particles are created when high-energy cosmic rays hit the atmosphere interacting with air nuclei initiating cascades of secondary particles which led to the formation of extensive air showers (EAS). They carry essential information about the extra-terrestrial events and are characterized by large flux and varying angular distribution. To account for open questions and the origin of cosmic rays, one needs to study various components of cosmic rays with energy and arriving direction. Because of the close relation between muon and neutrino production, it is the most important particle to keep track of. We propose a novel tracking algorithm based on the Geometric Deep Learning approach using graphical structure to incorporate domain knowledge to track cosmic ray muons in our 3-D scintillator detector. The detector is modeled using the GEANT4 simulation package and EAS is simulated using CORSIKA (COsmic Ray SImulations for KAscade) with a focus on muons originating from EAS. We shed some light on the performance, robustness towards noise and double hits, limitations, and application of the proposed algorithm in tracking applications with the possibility to generalize to other detectors for astrophysical and collider experiments.

physics.data-an↗

arXiv2020

A generalized approach to study low as well as high $p_T$ regime of transverse momentum spectra

A good understanding of the transverse momentum $(p_T)$ spectra is pivotal in the study of QCD matter created during the heavy-ion collision. Considering the difference in the underlying particle production mechanism, $p_T$ spectra can be divided into two distinct regions. Low-$p_T$ region corresponds to particle produced in soft-processes whereas particles produced in hard processes dominate the high-$p_T$ regime of the spectra. We will discuss a unified formalism to explain both low as well as high-$p_T$ region of the transverse momentum spectra in a consistent manner. This unified formalism is based on the generalisation of non-extensive statistical mechanics using the Pearson distribution. This generalised formalism also gives a strong insight into the study of elliptic flow in heavy-ion collision.

hep-ph↗

arXiv2020

Unified trade-off optimization of a three-level quantum refrigerator

We study the optimal performance of a three-level quantum refrigerator using a trade-off objective function, $Ω$ function, which represents a compromise between the energy benefits and the energy losses of a thermal device. First, we optimize the performance of our refrigerator by employing a two-parameter optimization scheme and show that the first two-terms in the series expansion of the obtained coefficient of performance (COP) match with those of some classical models of refrigerator. Then, in the high-temperature limit, optimizing with respect to one parameter while constraining the other one, we obtain the lower and upper bounds on the COP for both strong as well as weak (intermediate) matter-field coupling conditions. In the strong matter-field coupling regime, the obtained bounds on the COP exactly match with the bounds already known for some models of classical refrigerators. Further for weak matter-field coupling, we derive some new bounds on the the COP of the refrigerator which lie beyond the range covered by bounds obtained for strong matter-field coupling. Finally, in the parameter regime where both cooling power and $Ω$ function can be maximized, we compare the cooling power of the quantum refrigerator at maximum $Ω$ function with the maximum cooling power.

quant-ph↗

arXiv2016

Jet effects in high-multiplicity pp events

The study of the high-multiplicity pp events has become important because we need to understand the origin of the fluid-like features which have been found in such small systems. In this work we concentrate on the radial flow signatures. To this end, the role of jets in high-multiplicity pp collisions is investigated using PYTHIA 8.

hep-ph↗

arXiv2014

Test and characterization of a prototype silicon-tungsten electromagnetic calorimeter

New generation high-energy physics experiments demand high precision tracking and accurate measurements of a large number of particles produced in the collisions of lementary particles and heavy-ions. Silicon-tungsten (Si-W) calorimeters provide the most viable technological option to meet the requirements of particle detection in high multiplicity environments. We report a novel Si-W calorimeter design, which is optimized for $γ/π^0$ discrimination up to high momenta. In order to test the feasibility of the calorimeter, a prototype mini-tower was constructed using silicon pad detector arrays and tungsten layers. The performance of the mini-tower was tested using pion and electron beams at the CERN Proton Synchrotron (PS). The experimental results are compared with the results from a detailed GEANT-4 simulation. A linear relationship between the observed energy deposition and simulated response of the mini-tower has been obtained, in line with our expectations.

physics.ins-det↗