Searcharxiv⌕ Search

arXiv subjects

Raj Kishore

Publications and source records attributed to Raj Kishore.

At least 19 recordsLinked to original sources
arXiv2025

Modeling the TMD shape function in $J/\psi$ electroproduction

The next-to-leading order hard function for quarkonium electroproduction is calculated within the framework of transverse-momentum-dependent (TMD) factorization in the low-transverse-momentum regime. The structure of the TMD shape function in quarkonium leptoproduction is analyzed through its operator-level definition. Particular attention is given to the convolution of the unpolarized TMD gluon distribution with the TMD shape function, thereby illustrating the latter's phenomenological role. Building on this framework, we provide predictions for the unpolarized differential cross-section of $J/\psi$ electroproduction at the future Electron-Ion Collider in the region of small transverse momentum.

hep-ph↗
arXiv2024

TMD evolution effect on $\cos2\phi$ azimuthal asymmetry in a back-to-back production of $J/\psi$ and jet at the EIC

A back-to-back semi-inclusive $J/\psi + jet$ production is a promising process to study gluon transverse momentum distribution (TMDs) at the future electron-ion collider (EIC). A back-to-back configuration allows a higher transverse momentum for $J/\psi$. We present an extension of a previous work where we studied $\cos2\phi$ azimuthal asymmetry within the TMD factorization framework for this process. We present and compare the effect of TMD evolution on the asymmetry, in two approaches that differ in the parameterization of the perturbative tails of the TMDs and the non-perturbative factors. We show that the asymmetry depends on the parameterizations of the non-perturbative Sudakov factors in the larger $b_T$ region and on the perturbative part of the evolution kernel. We use NRQCD to estimate the $J/\psi$ production and show the effect of using different long-distance matrix element (LDME) sets. Overall, the asymmetry after incorporating TMD evolution is small, but increases with the transverse momentum imbalance of the $J/\psi$-jet pair.

hep-ph↗
arXiv2023

Gluon distributions in the proton in a light-front spectator model

We formulate a light-front spectator model for the proton incorporating the gluonic degree of freedom. In this model, at high energy scattering of the proton, the active parton is a gluon and the rest is viewed as a spin-$\frac{1}{2}$ spectator with an effective mass. The light front wave functions of the proton are constructed using a soft wall AdS/QCD prediction and parameterized by fitting the unpolarized gluon distribution function to the NNPDF3.0nlo data set. We investigate the helicity distribution of gluon in this model. We find that our prediction for the gluon helicity asymmetry agrees well with existing experimental data and satisfies the perturbative QCD constraints at small and large longitudinal momentum regions. We also present the transverse momentum dependent distributions (TMDs) for gluon in this model. We further show that the model-independent Mulders-Rodrigues inequalities are obeyed by the TMDs computed in our model.

hep-ph↗
arXiv2022

Azimuthal asymmetries in $J/ψ$-photon production at the EIC

We calculate azimuthal asymmetries in back-to-back production of $J/ψ$ and a photon in electron-proton scattering process at the future electron-ion collider (EIC) using TMD factorization framework. We consider the cases where the proton is unpolarized or transversely polarized. For the formation of $J/ψ$, non-relativistic QCD (NRQCD) is used. We find that the cross-section gets contribution from only one color octet state, as a result, the azimuthal modulations become independent of the long-distance matrix elements (LDMEs), and thus can be used to probe, in particular the gluon TMDs which are dominant in this kinematics. We show estimates of the upper bounds of different azimuthal asymmetries using the positivity bounds on TMDs. In addition, we show estimate of asymmetries using the Gaussian parametrization of the TMDs.

hep-ph↗
arXiv2022

$\cos2ϕ_t$ azimuthal asymmetry in back-to-back $J/ψ$-jet production in $e~p\rightarrow e~J/ψ~Jet~ X$ at the EIC

In this article, we investigate the $\cos2ϕ_t$ azimuthal asymmetry in $e ~p\rightarrow e ~J/ψ~Jet~ X$, where the $J/ψ$-jet pair is almost back-to-back in the transverse plane, within the framework of the generalized parton model(GPM). We use non-relativistic QCD(NRQCD) to calculate the $J/ψ$ production amplitude and incorporate both color singlet(CS) and color octet(CO) contributions to the asymmetry. We estimate the asymmetry using different parameterizations of the gluon TMDs in the kinematics that can be accessed at the future electron-ion collider (EIC) and also investigate the impact of transverse momentum dependent (TMD) evolution on the asymmetry. We present the contributions coming from different states to the asymmetry in NRQCD.

hep-ph↗
arXiv2021

A new method to extract the valence transversity distributions

A new method is suggested for the extraction of $u$-quark and $d$-quark transversity distributions, using single spin asymmetry (SSA) data in semi-inclusive deep inelastic scattering (SIDIS) processes, where they couple to the Collins or the di-hadron fragmentation functions. We discuss a recent suggestion to extract the transversity distribution using the concept of difference asymmetries and their ratios, which avoids the requirement of Collins function. We suggest new measurements, involving ratios of polarized cross-sections, that would directly probe the ratio $h_1^{d_v}/h_1^{u_v}$. We also show some numerical estimates.

hep-ph↗
arXiv2021

$cos(2ϕ_h)$ asymmetry in $J/ψ$ production in unpolarized $ep$ collision in NRQCD

We present a recent calculation of the transverse momentum dependent gluon distributions inside unpolarised protons and show how the ratio of the linearly polarized and the unpolarized gluon distribution in the proton can be probed by looking at $Cos(2ϕ_h)$ asymmetry in $J/ψ$ production in unpolarized $ep$ collision. We use NRQCD for estimating $J/ψ$ production and include contributions both from color singlet and color octet states.

hep-ph↗
arXiv2021

$Cos(2ϕ_h)$ asymmetry in $J/ψ$ production in unpolarized $ep$ collision

We present a calculation of the $cos (2 ϕ_h)$ asymmetry in $J/ψ$ production in electron-proton collision at the future electron-ion collider (EIC), a useful channel to probe the gluon TMDs. We calculate the asymmetry at next-to-leading order (NLO) in $α_s$ in the framework of generalized factorization. The dominating sub-process is $γ^* +g \rightarrow J/ψ+g$. The production of $J/ψ$ is calculated in the non-relativistic QCD(NRQCD) framework with the inclusion of both color singlet and color octet contributions. Numerical estimates of the $cos(2ϕ_h)$ asymmetry are given in the kinematical region to be accessed by the future EIC. The asymmetry depends on the parameterization of the gluon TMDs, as well as on the long distance matrix elements (LDMEs). We use both Gaussian-type parameterization and McLerran-Venugopalan model for the TMDs in the kinematical region of small-$x$, where the gluons play a dominant role. We obtain sizable asymmetry, which may be useful to probe the ratio of the linearly polarized and the unpolarized gluon distribution in the proton.

hep-ph↗
arXiv2020

Analysis of COVID19 Outbreak in India using SEIR model

The prediction of spread patterns of COVID19 virus in India is very difficult due to its versatile demographic as well as meteorological data distribution. Various researchers across the globe have attempted to correlate the interdependency of these data with the spread pattern of COVID19 cases in India. But it is hard to predict the exact pattern, especially the peak in the number of active cases. In the present article we have tried to predict the number of active, recovered, death and total cases of COVID19 in India using generalized SEIR model. In our prediction, the occurrence of peak in the active cases curve has a very close match with the peak in the real data (difference of only one week). Although the number of predicted cases differs with the real number of cases (due to unlocking the movement restrictions gradually from June 2020 onwards), the close resemblance in the actual and predicted time (in the peak of active cases curve) makes this model relatively suitable for analysis of COVID19 outbreak in India.

physics.soc-ph↗
arXiv2020

A new nature inspired modularity function adapted for unsupervised learning involving spatially embedded networks: A comparative analysis

Unsupervised machine learning methods can be of great help in many traditional engineering disciplines, where huge amount of labeled data is not readily available or is extremely difficult or costly to generate. Two specific examples include the structure of granular materials and atomic structure of metallic glasses. While the former is critically important for several hundreds of billion dollars global industries, the latter is still a big puzzle in fundamental science. One thing is common in both the examples is that the particles are the elements of the ensembles that are embedded in Euclidean space and one can create a spatially embedded network to represent their key features. Some recent studies show that clustering, which generically refers to unsupervised learning, holds great promise in partitioning these networks. In many complex networks, the spatial information of nodes play very important role in determining the network properties. So understanding the structure of such networks is very crucial. We have compared the performance of our newly developed modularity function with some of the well-known modularity functions. We performed this comparison by finding the best partition in 2D and 3D granular assemblies. We show that for the class of networks considered in this article, our method produce much better results than the competing methods.

cs.LG↗
arXiv2020

A kinetic model for qualitative understanding and analysis of the effect of complete lockdown imposed by India for controlling the COVID-19 disease spread by the SARS-CoV-2 virus

The present ongoing global pandemic caused by SARS-CoV-2 virus is creating havoc across the world. The absence of any vaccine as well as any definitive drug to cure, has made the situation very grave. Therefore only few effective tools are available to contain the rapid pace of spread of this disease, named as COVID-19. On 24th March, 2020, the the Union Government of India made an announcement of unprecedented complete lockdown of the entire country effective from the next day. No exercise of similar scale and magnitude has been ever undertaken anywhere on the globe in the history of entire mankind. This study aims to scientifically analyze the implications of this decision using a kinetic model covering more than 96% of Indian territory. This model was further constrained by large sets of realistic parameters pertinent to India in order to capture the ground realities prevailing in India, such as: (i) true state wise population density distribution, (ii) accurate state wise infection distribution for the zeroth day of simulation (20th March, 2020), (iii) realistic movements of average clusters, (iv) rich diversity in movements patterns across different states, (v) migration patterns across different geographies, (vi) different migration patterns for pre- and post-COVID-19 outbreak, (vii) Indian demographic data based on the 2011 census, (viii) World Health Organization (WHO) report on demography wise infection rate and (ix) incubation period as per WHO report. This model does not attempt to make a long-term prediction about the disease spread on a standalone basis; but to compare between two different scenarios (complete lockdown vs. no lockdown). In the framework of model assumptions, our model conclusively shows significant success of the lockdown in containing the disease within a tiny fraction of the population and in the absence of it, it would have led to a very grave situation.

cs.CY↗
arXiv2020

Probing Nucleons and Nuclei in High Energy Collisions

This volume is a collection of contributions for the 7-week program "Probing Nucleons and Nuclei in High Energy Collisions" that was held at the Institute for Nuclear Theory in Seattle, WA, USA, from October 1 until November 16, 2018. The program was dedicated to the physics of the Electron Ion Collider (EIC), the world's first polarized electron-nucleon (ep) and electron-nucleus (eA) collider to be constructed in the USA. These proceedings are organized by chapters, corresponding to the weeks of the program: Week I, Generalized parton distributions; Week II, Transverse spin and TMDs; Week III, Longitudinal spin; Week IV, Symposium week; Weeks V & VI, eA collisions; Week VII, pA and AA collisions. We hope these proceedings will be useful to readers as a compilation of EIC-related science at the end of the second decade of the XXI century.

hep-ph↗
arXiv2020

Sivers Asymmetry in Photoproduction of $J/ψ$ and Jet at the EIC

We calculate the Sivers asymmetry in the photoproduction of almost back-to-back $J/ψ$-jet pair in the process $ep^\uparrow \to J/ψ+\mathrm{jet}+X$, which will be possible at the future planned electron-ion collider (EIC). We use the framework of generalized parton model (GPM), and NRQCD for calculating the $J/ψ$ production rate. We include contributions from both color singlet and color octate states in the asymmetry. We obtain sizable Sivers asymmetry that can be promising to determine the gluon Sivers function. We also investigate the effect of TMD evolution on the asymmetry.

hep-ph↗
arXiv2020

Visual Machine Learning: Insight through Eigenvectors, Chladni patterns and community detection in 2D particulate structures

Machine learning (ML) is quickly emerging as a powerful tool with diverse applications across an extremely broad spectrum of disciplines and commercial endeavors. Typically, ML is used as a black box that provides little illuminating rationalization of its output. In the current work, we aim to better understand the generic intuition underlying unsupervised ML with a focus on physical systems. The systems that are studied here as test cases comprise of six different 2-dimensional (2-D) particulate systems of different complexities. It is noted that the findings of this study are generic to any unsupervised ML problem and are not restricted to materials systems alone. Three rudimentary unsupervised ML techniques are employed on the adjacency (connectivity) matrix of the six studied systems: (i) using principal eigenvalue and eigenvectors of the adjacency matrix, (ii) spectral decomposition, and (iii) a Potts model based community detection technique in which a modularity function is maximized. We demonstrate that, while solving a completely classical problem, ML technique produces features that are distinctly connected to quantum mechanical solutions. Dissecting these features help us to understand the deep connection between the classical non-linear world and the quantum mechanical linear world through the kaleidoscope of ML technique, which might have far reaching consequences both in the arena of physical sciences and ML.

cs.LG↗
arXiv2019

The Polarising Fragmentation Function and the Lambda polarisation in e+ e- processes

The surprising polarisation of Lambdas and other hyperons measured in many unpolarised hadronic processes, p N --> Lambda X, has been a long standing challenge for QCD phenomenology. One possible explanation was suggested, related to non perturbative properties of the quark hadronisation process, and encoded in the so-called Polarising Fragmentation Function (PFF). Recent Belle data have shown a non zero Lambda polarisation also in unpolarised e+ e- processes, e+ e- --> Lambda X and e+ e- --> Lambda h X. We consider the single inclusive case and the role of the PFFs. Adopting a simplified kinematics it is shown how they can originate a polarisation P_Lambda different from 0 and give explicit expressions for it in terms of the PFFs. Although the Belle data do not allow yet, in our approach, an extraction of the PFFs, some clear predictions are given, suggesting crucial measurements, and estimates of P_Lambda are computed, in qualitative agreement with the Belle data.

hep-ph↗
arXiv2019

Accessing Linearly Polarized Gluon Distribution in $J/ψ$ Production at the Electron-Ion Collider

We calculate the $cos~2 ϕ$ asymmetry in $J/ψ$ production in electron-proton collision for the kinematics of the planned electron-ion collider (EIC). This directly probes the Weiszäcker-Williams (WW) type linearly polarized gluon distribution. Assuming generalized factorization, we calculate the asymmetry at next-to-leading-order (NLO) when the energy fraction of the $J/ψ$ satisfies $z<1$ and the dominating subprocess is $γ^* +g \rightarrow c + {\bar c}+g$. We use non-relativistic QCD based color singlet model for $J/ψ$ production. We investigate the small $x$ region which will be accessible at the EIC. We present the upper bound of the asymmetry, as well as estimate it using a (i) Gaussian type parametrization for the TMDs and (ii) McLerran-Venugopalan model at small $x$. We find small but sizable asymmetry in all the three cases.

hep-ph↗