arXiv subjects

Sunny Kumar Singh

Publications and source records attributed to Sunny Kumar Singh.

7 recordsLinked to original sources

arXiv2025

Quarkonium in a QCD medium with momentum-dependent relaxation time

In this study, we explore the properties of quarkonia in a hot QCD medium using a newly proposed collision kernel that consistently incorporates the particle's momentum dependence into the relaxation time scale of the medium. The longitudinal component of the gluon self-energy, along with the Debye screening mass, is computed within the one-loop hard thermal loop framework by incorporating non-equilibrium corrections. A modified kinetic theory with an extended relaxation time approximation is employed to model the non-equilibrium dynamics of the QCD medium. The sensitivity of the heavy quarkonia potential to the momentum dependence of the relaxation time is studied. Further, we studied the binding energy and thermal width of quarkonia states within this new kinetic theory. Sizable variations in the temperature behavior of these quantities are observed in comparison with the standard relaxation time approximation method due to the particle momentum dependence on the relaxation timescale of the QCD medium. Our findings highlight that accounting for the microscopic nature of the collision timescale is crucial for understanding the quarkonium behavior in a QCD medium.

hep-ph↗

arXiv2025

Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks

Accurate macroeconomic forecasting has become harder amid geopolitical disruptions, policy reversals, and volatile financial markets. Conventional vector autoregressions (VARs) overfit in high dimensional settings, while threshold VARs struggle with time varying interdependencies and complex parameter structures. We address these limitations by extending the Sims Zha Bayesian VAR with exogenous variables (SZBVARx) to incorporate domain-informed shrinkage and four newspaper based uncertainty shocks such as economic policy uncertainty, geopolitical risk, US equity market volatility, and US monetary policy uncertainty. The framework improves structural interpretability, mitigates dimensionality, and imposes empirically guided regularization. Using G7 data, we study spillovers from uncertainty shocks to five core variables (unemployment, real broad effective exchange rates, short term rates, oil prices, and CPI inflation), combining wavelet coherence (time frequency dynamics) with nonlinear local projections (state dependent impulse responses). Out-of-sample results at 12 and 24 month horizons show that SZBVARx outperforms 14 benchmarks, including classical VARs and leading machine learning models, as confirmed by Murphy difference diagrams, multivariate Diebold Mariano tests, and Giacomini White predictability tests. Credible Bayesian prediction intervals deliver robust uncertainty quantification for scenario analysis and risk management. The proposed SZBVARx offers G7 policymakers a transparent, well calibrated tool for modern macroeconomic forecasting under pervasive uncertainty.

econ.EM↗

arXiv2025

Particle number diffusion in second-order relativistic dissipative hydrodynamics with momentum-dependent relaxation time

This article explores particle number diffusion in relativistic hydrodynamics using kinetic theory with a modified collision kernel that incorporates the momentum dependence of the particle relaxation time. Starting from the Boltzmann equation within the extended relaxation time approximation (ERTA), we derive second-order evolution equations for the dissipative number current and calculate the associated transport coefficients. The sensitivity of transport coefficients to the particle momentum dependence of the collision time scale of the microscopic interactions in the hot QCD medium is analyzed. For a conformal, number-conserving system, we compare the ERTA-modified transport coefficients for particle diffusion with exact results derived from scalar field theory. With an appropriate parameterization of the relaxation time, we demonstrate the consistency of our analysis and assess the degree of agreement of the results with the exact solutions from scalar field theory. The relaxation times for the shear and number diffusion evolution equations are seen to be distinct in general when the momentum dependence of the relaxation time is taken into consideration.

hep-ph↗

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

Forecasting CPI inflation under economic policy and geopolitical uncertainties

Forecasting consumer price index (CPI) inflation is of paramount importance for both academics and policymakers at the central banks. This study introduces a filtered ensemble wavelet neural network (FEWNet) to forecast CPI inflation, which is tested on BRIC countries. FEWNet breaks down inflation data into high and low-frequency components using wavelets and utilizes them along with other economic factors (economic policy uncertainty and geopolitical risk) to produce forecasts. All the wavelet-transformed series and filtered exogenous variables are fed into downstream autoregressive neural networks to make the final ensemble forecast. Theoretically, we show that FEWNet reduces the empirical risk compared to fully connected autoregressive neural networks. FEWNet is more accurate than other forecasting methods and can also estimate the uncertainty in its predictions due to its capacity to effectively capture non-linearities and long-range dependencies in the data through its adaptable architecture. This makes FEWNet a valuable tool for central banks to manage inflation.

econ.EM↗

arXiv2024

Revisiting shear stress tensor evolution: Non-resistive magnetohydrodynamics with momentum-dependent relaxation time

This study aims to develop second-order relativistic viscous magnetohydrodynamics (MHD) derived from kinetic theory within an extended relaxation time approximation (momentum/energy dependent) for the collision kernel. The investigation involves a detailed examination of shear stress tensor evolution equations and associated transport coefficients. The Boltzmann equation is solved using a Chapman-Enskog-like gradient expansion for a charge-conserved conformal system, incorporating a momentum-dependent relaxation time. The derived relativistic non-resistive, viscous second-order MHD equations for the shear stress tensor reveal significant modifications in the coupling with dissipative charge current and magnetic field due to the momentum dependence of the relaxation time. By utilizing a power law parametrization to quantify the momentum dependence of the relaxation time, the anisotropic magnetic field-dependent shear coefficients in the Navier-Stokes limit have been investigated. The resulting viscous coefficients are seen to be sensitive to the momentum dependence of the relaxation time.

hep-ph↗

arXiv2023

Chemical freeze-out parametrization with mean field repulsive hadron resonance gas model

We have examined the chemical freeze-out surface of the heavy-ion collision experiments within an interacting hadron resonance gas model. By considering repulsive interaction among hadrons in the mean-field level, we have suitably parameterized the freeze-out surface by fitting the yield data of mid-rapidity for the most central collision, for the collision energy available in AGS, RHIC (BES), and LHC programs. To suitably account for the repulsive interaction among mesons and (anti-) baryons, we have introduced phenomenological parameters $K_M$ and $K_B$ in the freeze-out parametrization. Although a finite value of these two parameters seem to be necessary to have an improved normalized \emph{chi-square}, the effect on the rest of the parameters like temperature and relevant chemical potentials seem to be within the standard variance.

hep-ph↗