Related papers: Simultaneous Estimation of Elliptic Flow Coefficie…
We investigate how the initial geometry of a heavy-ion collision is transformed into final flow observables by solving event-by-event ideal hydrodynamics with realistic fluctuating initial conditions. We study quantitatively to what extent…
This paper establishes a data-driven modeling framework for lean Hydrogen (H2)-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particularly challenging since H2 molecules diffuse much faster than…
Recent data from the NA49 experiment on directed and elliptic flow for Pb+Pb reactions at CERN-SPS are compared to calculations with a hadron-string transport model, the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) model. The…
The choice of optimal event variables is crucial for achieving the maximal sensitivity of experimental analyses. Over time, physicists have derived suitable kinematic variables for many typical event topologies in collider physics. Here we…
The vast quantity of strong galaxy-galaxy gravitational lenses expected by future large-scale surveys necessitates the development of automated methods to efficiently model their mass profiles. For this purpose, we train an approximate…
This paper presents a novel parameter calibration approach for power system stability models using automatic data generation and advanced deep learning technology. A PMU-measurement-based event playback approach is used to identify…
Lightning plays a crucial role in the Earth's climate system, yet existing parameterizations for use in forecasting and earth system models show room for improvement in capturing spatial and temporal variations in its frequency. This study…
We introduce a parameter sharing scheme, in which different layers of a convolutional neural network (CNN) are defined by a learned linear combination of parameter tensors from a global bank of templates. Restricting the number of templates…
We predict the elliptic flow parameter v_2 in U+U collisions at sqrt{s_{NN}}=200 GeV and in Pb+Pb collisions at sqrt{s_{NN}} = 2.76 TeV using a hybrid model in which the evolution of the quark gluon plasma is described by ideal…
Electrical Impedance Tomography (EIT) is a highly ill-posed inverse problem, with the challenge of reconstructing internal conductivities using only boundary voltage measurements. Although Physics-Informed Neural Networks (PINNs) have shown…
Voigt profile (VP) decomposition of quasar absorption lines is key to studying intergalactic gas and the baryon cycle governing the formation and evolution of galaxies. The VP velocities, column densities, and Doppler $b$ parameters inform…
We report the elliptic flow of charged and identified particles at mid-rapidity in Au+Au collisions at $\sqrt{s_{_{NN}}}=130$ GeV using the STAR TPC at RHIC. The integrated elliptic flow signal, $v_2$, for charged particles reaches values…
The proton elliptic flow in collisions of Ca on Ca at energies from 30 to 100 MeV/nucleon is studied in an isospin-dependent transport model. With increasing incident energy, the elliptic flow shows a transition from positive to negative…
Machine Learning (ML) algorithms have been demonstrated to be capable of predicting impact parameter in heavy-ion collisions from transport model simulation events with perfect detector response. We extend the scope of ML application to…
Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we…
In this paper we propose to thoroughly investigate asymmetric nuclear collisions both in the fixed target mode at the laboratory energy below 5 GeV per nucleon and in the collider mode with a center of mass energy below 11 GeV per nucleon.…
Electroencephalography (EEG) classification plays a key role in brain-computer interface (BCI) systems, yet it remains challenging due to the low signal-to-noise ratio, temporal variability of neural responses, and limited data…
This paper reports results for directed flow $v_{1}$ and elliptic flow $v_{2}$ of charged particles in Cu+Cu collisions at $\sqrt{s_{NN}}=$ 22.4 GeV at the Relativistic Heavy Ion Collider. The measurements are for the 0-60% most central…
Ultra-Relativistic Heavy Ion Collisions at an energy $\sqrt{s_{NN}} = 65 {\rm GeV}$ are studied in a three-dimensional Fluid Dynamical model. The results of a hydrodynamical evolution using the PIC-method are shown. The importance and…
Detecting Beyond Standard Model (BSM) signals in high-energy particle collisions presents significant challenges due to complex data and the need to differentiate rare signal events from Standard Model (SM) backgrounds. This study…