arXiv subjects

Syed Afrid Jahan

Publications and source records attributed to Syed Afrid Jahan.

3 recordsLinked to original sources

arXiv2026

Bayesian Model Selection and Uncertainty Propagation for Beam Energy Scan Heavy-Ion Collisions

We apply the Bayesian model selection method (based on the Bayes factor) to optimize $\sqrt{s_\mathrm{NN}}$-dependence in the phenomenological parameters of the (3+1)-dimensional hybrid framework for describing relativistic heavy-ion collisions within the Beam Energy Scan program at the Relativistic Heavy-Ion Collider. The effects of various experimental measurements on the posterior distribution are investigated. We also make model predictions for longitudinal flow decorrelation, rapidity-dependent anisotropic flow and identified particle $v_0(p_\mathrm{T})$ in Au+Au collisions, as well as anisotropic flow coefficients in small systems. Systematic uncertainties in the model predictions are estimated using the variance of the simulation results with a few parameter sets sampled from the posterior distributions.

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arXiv2026

On model emulation and closure tests for 3+1D relativistic heavy-ion collisions

In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated in heavy-ion collisions. However, computational demands pose challenges, motivating using Gaussian Process emulators for efficient parameter extraction via Bayesian calibration. We conduct a comparative analysis of Gaussian Process emulators in heavy-ion physics to identify the most adept emulator for parameter extraction with minimal uncertainty. Our study contributes to advancing computational techniques in heavy-ion physics, enhancing our ability to interpret experimental data and understand QGP properties.

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arXiv2024

Bayesian analysis of (3+1)D relativistic nuclear dynamics with the RHIC beam energy scan data

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the Beam Energy Scan program at the Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)D collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the Quark-Gluon Plasma's transport properties and various aspects of (3+1)D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for $p_{\rm T}$-differential observables and estimate their systematic theory uncertainty. A sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

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