Related papers: Kilonova modelling and parameter inference: Unders…
To accurately reproduce measurements from the real world, simulators need to have an adequate model of the physical system and require the parameters of the model be identified. We address the latter problem of estimating parameters through…
In the new era of gravitational wave (GW) and multi-messenger astrophysics, the detection of a GW signal from the coalescence of a black hole - neutron star (BHNS) binary remains a highly anticipated discovery. This kind of system is…
Mergers of binary neutron stars are multimessenger sources of gravitational waves that have an optical luminous counterpart, commonly referred to as 'kilonova'. Inspired by the detection of GW170817, intensive searches have been conducted…
The combined detection of a binary neutron-star merger in both gravitational waves (GWs) and electromagnetic (EM) radiation spanning the entire spectrum -- GW170817 / AT2017gfo / GRB170817A -- marks a breakthrough in the field of…
Machine learning (ML) and deep learning models are extensively used for parameter optimization and regression problems. However, not all inverse problems in ML are ``identifiable,'' indicating that model parameters may not be uniquely…
Bayesian parameter estimation provides a systematic approach to compare heavy ion collision models with measurements, leading to constraints on the properties of nuclear matter with proper accounting of experimental and theoretical…
Multi-messenger observation of binary neutron-star mergers can provide valuable information on the nuclear equation of state (EoS). Here, we investigate to which extent electromagnetic observations of the associated kilonovae allow us to…
Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for…
Kilonovae are approximately thermal transients, produced by mergers of binary neutron stars (BNSs) and NS-black hole binaries. As the optical counterpart of the gravitational wave event GW170817, AT2017gfo is the first kilonova detected…
Using observation data to estimate unknown parameters in computational models is broadly important. This task is often challenging because solutions are non-unique due to the complexity of the model and limited observation data. However,…
The discovery of a kilonova (KN) associated with the Advanced LIGO (aLIGO)/Virgo event GW170817 opens up new avenues of multi-messenger astrophysics. Here, using realistic simulations, we provide estimates of the number of KNe that could be…
The complex nature of inertial confinement fusion (ICF) experiments results in a very large number of experimental parameters that are only known with limited reliability. These parameters, combined with the myriad physical models that…
Inferring parameters of macro-kinetic growth models, typically represented by Ordinary Differential Equations (ODE), from the experimental data is a crucial step in bioprocess engineering. Conventionally, estimates of the parameters are…
The first binary neutron star merger, GW170817, was accompanied by a radioactivity-powered optical/infrared transient called a kilonova. To date, no compelling kilonova has been found during optical surveys of the sky, independent of…
Because of the electromagnetic radiation produced during the merger, compact binary coalescences with neutron stars may result in multi-messenger observations. In order to follow up on the gravitational-wave signal with electromagnetic…
The observations of optical and near-infrared counterparts of binary neutron star mergers not only enrich our knowledge about the abundance of heavy elements in the Universe, or help reveal the remnant object just after the merger as…
Binary neutron star mergers have been recently confirmed to be the progenitors of the optical transients kilonovae (KNe). KNe are powered by the radioactive decay of neutron-rich elements (r-process elements) which are believed to be the…
The discovery of the optical counterpart, along with the gravitational waves from GW170817, of the first binary neutron star merger, opened up a new era for multi-messenger astrophysics. Combining the GW data with the optical counterpart,…
A substantial fraction of systematic uncertainties in neutrino oscillation experiments stem from the lack of precision in modeling the nuclear target in neutrino-nucleus interactions. Whilst this has driven significant progress in the…
Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using a…