arXiv subjects

Aditya Prasad Dash

Publications and source records attributed to Aditya Prasad Dash.

3 recordsLinked to original sources

arXiv2026

Probing Jet-Medium Interactions in Heavy-Ion Collisions Using Energy-Energy Correlators

Energy-energy correlators (EECs) provide a sensitive probe of both perturbative and nonperturbative dynamics in relativistic heavy-ion collisions. Jet-medium interactions enhance particle multiplicity within the jet cone, which must be properly accounted for when extracting the EEC of jet shower hadrons in experiments. To address this issue, we develop an augmentation method that exploits momentum conservation between the near-side and away-side regions, using $γ$-jet events with 0-10\% centrality in Pb+Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV simulated with the CoLBT-hydro model. This approach yields an experimentally reconstructed EEC that shows improved agreement with the EEC of hadrons originating primarily from jet parton splittings. Comparing EECs of jets from Pb+Pb and p+p collisions with different matching conditions can be sensitive to jet medium interaction dynamics, and provide a novel means to test the scenario of jet energy loss in the QGP, followed by fragmentations outside the QGP.

nucl-th↗

arXiv2025

From Simulations to Surveys: Domain Adaptation for Galaxy Observations

Large photometric surveys will image billions of galaxies, but we currently lack quick, reliable automated ways to infer their physical properties like morphology, stellar mass, and star formation rates. Simulations provide galaxy images with ground-truth physical labels, but domain shifts in PSF, noise, backgrounds, selection, and label priors degrade transfer to real surveys. We present a preliminary domain adaptation pipeline that trains on simulated TNG50 galaxies and evaluates on real SDSS galaxies with morphology labels (elliptical/spiral/irregular). We train three backbones (CNN, $E(2)$-steerable CNN, ResNet-18) with focal loss and effective-number class weighting, and a feature-level domain loss $L_D$ built from GeomLoss (entropic Sinkhorn OT, energy distance, Gaussian MMD, and related metrics). We show that a combination of these losses with an OT-based "top_$k$ soft matching" loss that focuses $L_D$ on the worst-matched source-target pairs can further enhance domain alignment. With Euclidean distance, scheduled alignment weights, and top-$k$ matching, target accuracy (macro F1) rises from $\sim$46% ($\sim$30%) at no adaptation to $\sim$87% ($\sim$62.6%), with a domain AUC near 0.5, indicating strong latent-space mixing.

astro-ph.GA↗

arXiv2024

Exploring Electromagnetic Field Effects and Constraining Transport Parameters of QGP using STAR BES-II data

Heavy-ion collisions undergo various stages in their evolution and it is crucial to disentangle the initial- and final-stage effects. In this work, we report measurements of two types of observables: (i) charge-dependent directed flow ($Δv_1$), which is sensitive to the initial ultra-strong electromagnetic fields, and (ii) flow correlations, such as $r_n (η)$ which is sensitive to the initial longitudinal de-correlation, and correlations among flow harmonics. These measurements contribute to constraining the initial state of the collisions, and through a comprehensive beam energy scan, we gain significant insights into the system evolution in the presence of initial spatial asymmetry and electromagnetic fields.

nucl-ex↗