SearcharxivSearch

arXiv subjects

Rabia Bashir

Publications and source records attributed to Rabia Bashir.

3 recordsLinked to original sources

Predictions for Identified Hadron ($\pi^\pm$, $K^\pm$ and $p(\overline{p})$) Production and Collective Dynamics in Oxygen-Oxygen Collisions at $\sqrt{s_{NN}}$= 7 TeV with EPOS4, AMPT-SM, and Angantyr in Pythia 8

We study the dynamics of identified hadrons ($\pi^\pm$, $K^\pm$ and $p(\overline{p})$) production in $O+O$ collisions at $\sqrt{s_{\mathrm{NN}}} = 7$TeV using recently updated version of EPOS4, string melting version of A Multi-Phase Transport Model (AMPT-SM) and Angantyr model, incorporated within Pythia 8. We examine the interplay between different mechanisms implemented in these models. Predictions for charged particle multiplicity ($dN_{ch}/d\eta$), transverse momentum ($p_T$) spectra of identified hadrons, particle yield ($dN/dy$) and mean transverse mass ($\langle m_T \rangle$) are presented. To probe the collective behavior of the produced particles, the $p_T$-differential kaons-to-pion and proton-to-pion ratios are studied. While AMPT incorporates some flow effects, EPOS4's implementation of full hydrodynamic flow proves significantly more effective. In contrast, the flow effects in Pythia 8 are substantially weaker compared to the other models. The upcoming $O+O$ data from the LHC will help constrain the parameters of these models.

hep-ph

Testing of Pythia modes to study identified particle production in high-multiplicity pp collisions at $\mathbf{\sqrt{s}}$ = 7 TeV

This study presents a comprehensive analysis of particle production in proton-proton ($pp$) collisions at $\sqrt{s}$ = 7 TeV using Pythia~8 event generator. We investigate the transverse momentum $p_T$ spectra of light charged hadrons ($π^\pm$, $K^\pm$ and $p(\bar p)$), their yield ratios ($π^-/π^+$, $K^-/K^+$ and $\bar{p}/p$), and $p_T$-differential ratios ($(K^++K^-)/(π^++π^-)$, $(\overline{p}+p)/(π^++π^-)$) and mean transverse momentum ($\langle p_\mathrm{T} \rangle$). Our analysis employs various Pythia~8 tunes (Simple, Vincia, and Dire) to explore the impact of different model configurations on particle production. We optimize a key parameter ($p_\mathrm{T}HatMin$) within each tune to achieve the best agreement between the simulated \ppt spectra and those measured by the CMS collaboration. Interestingly, we find that the optimal values for $p_\mathrm{T}HatMin$ differ between hadron species, potentially reflecting the influence of particle mass on production mechanisms. It is not possible to simultaneously and qualitatively describe both, the strangeness enhancement and collectivity in $pp$ collisions from \pythia~8. Further investigation such as final-state effects such as color ropes or junctions may require to explain these effects. These types of studies help us identify limitations in current models and refine their parameters to better explain experimental observations.

hep-ph

A shared latent space matrix factorisation method for recommending new trial evidence for systematic review updates

Clinical trial registries can be used to monitor the production of trial evidence and signal when systematic reviews become out of date. However, this use has been limited to date due to the extensive manual review required to search for and screen relevant trial registrations. Our aim was to evaluate a new method that could partially automate the identification of trial registrations that may be relevant for systematic review updates. We identified 179 systematic reviews of drug interventions for type 2 diabetes, which included 537 clinical trials that had registrations in ClinicalTrials.gov. We tested a matrix factorisation approach that uses a shared latent space to learn how to rank relevant trial registrations for each systematic review, comparing the performance to document similarity to rank relevant trial registrations. The two approaches were tested on a holdout set of the newest trials from the set of type 2 diabetes systematic reviews and an unseen set of 141 clinical trial registrations from 17 updated systematic reviews published in the Cochrane Database of Systematic Reviews. The matrix factorisation approach outperformed the document similarity approach with a median rank of 59 and recall@100 of 60.9%, compared to a median rank of 138 and recall@100 of 42.8% in the document similarity baseline. In the second set of systematic reviews and their updates, the highest performing approach used document similarity and gave a median rank of 67 (recall@100 of 62.9%). The proposed method was useful for ranking trial registrations to reduce the manual workload associated with finding relevant trials for systematic review updates. The results suggest that the approach could be used as part of a semi-automated pipeline for monitoring potentially new evidence for inclusion in a review update.

cs.IR