Executive Summary : | The pursuit of understanding fundamental particles and forces has driven physicists for centuries, namely, the fundamental constituents of matter and the forces that govern them. The most recent development towards this quest is understanding strong force and its fundamental constituents. The recent results from heavy-ion colliders have enriched the Quantum Chromodynamics (QCD) phase diagram at high temperature and low baryon density. However, the phase at low temperature and finite (mostly intermediate) baryon density remain unexplored because the current theoretical approaches, numerical models and experiments are not good enough to examine these regimes. However, theoretical QCD calculation predicts phase transition (PT) from hadronic matter (HM) to quark matter (QM) at such densities. Presently, the best labs available to probe such densities lie at the core of neutron stars (NSs). The central theme of this project is to probe such intermediate densities at NS cores with simulations and extract their gravitational & electromagnetic signatures, later to be matched/searched in existing/upcoming observational data. The simulation of binary NS mergers (BNSM) predicts the emission of gravitational waves (GWs). Depending on the equation of state, whether hadronic or quark, the GW signal differs, and it has been argued that one can infer whether QM exists at NS cores studying them. However, both the HM and QM at such high densities are parameter-dependent, and one can tweak them such that one cannot distinguish whether the matter inside the hyper-massive NS is HM or QM. The only way of distinguishing the matter content is by inspecting the signatures of PT happening at the core of the hyper-massive NS. This project aims to simulate such scenarios. A clear GW signal should be received if a shock accompanies the PT, as hypothesized from our previous calculations for cold NSs. If such a signal can be observed in astrophysical events, then we can confirm the occurrence of PT from HM to QM at high density and low-temperature regimes, which has been the quest of the scientific community for decades. Secondly, if a massive star collapses in a Supernova, resulting in the formation of a massive NS, it can harbour QM at its core from birth. The signature of PT from HM to QM will be imprinted in the GW signal in these scenarios as well. This project will also probe such simulations and analyze their observable signatures. The advent of more sensitive interferometers for detecting GW signals will require us to have more knowledge about their origins. Using machine learning (ML) techniques, we can classify whether the detected signal is from a merger of hadronic stars or quark stars. For classification, we use different ML algorithms. The algorithm which classifies the templates with the least error will help us to classify such templates in the future and will be highly beneficial for the match-filtering of actual observed GW signals. |