Related papers: Radio pulsar population synthesis with consistent …
Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions. Recent advances using neural density estimators in SBI algorithms have…
In recent years, there has been a remarkable development of simulation-based inference (SBI) algorithms, and they have now been applied across a wide range of astrophysical and cosmological analyses. There are a number of key advantages to…
Population-based learning paradigms, including evolutionary strategies, Population-Based Training (PBT), and recent model-merging methods, combine fast within-model optimisation with slower population-level adaptation. Despite their…
Aims. The mass discrepancy between the observed population of double neutron star binaries by radio pulsar observations and gravitational-wave observation requires an explanation. Methods. Binary population synthesis calculations are…
We performed Monte Carlo simulations of different properties of pulsar radio emission, such as: pulsar periods, pulse-widths, inclination angles and rates of occurrence of interpulse emission (IP). We used recently available large data sets…
Pulsar wind nebulae (PWNe), especially the young ones, are among the most energetic astrophysical sources in the Galaxy. It is usually believed that the spin-down energy injected from the pulsars is converted into magnetic field and…
In the last 20 years our understanding of the millisecond pulsar (MSP) population changed dramatically. Thanks to RXTE, we discovered that neutron stars in LMXBs spins at 200-750 Hz frequencies, and indirectly confirmed the recycling…
We present the description and initial results of the TRAPUM (TRAnsients And PUlsars with MeerKAT) search for pulsars associated with supernova remnants (SNRs), pulsar wind nebulae and unidentified TeV emission. The list of sources to be…
As performance of dedicated facilities continually improved, massive pulsar candidates are being received, which makes selecting valuable pulsar signals from candidates challenging. In this paper, we designed a deep convolutional neural…
Retrieving the physical parameters from spectroscopic observations of exoplanets is key to understanding their atmospheric properties. Exoplanetary atmospheric retrievals are usually based on approximate Bayesian inference and rely on…
Recently, several pulsar timing array (PTA) projects have detected evidence of the existence of a stochastic gravitational wave background (SGWB) in the nanohertz frequency band, providing confidence in detecting individual supermassive…
We present a probabilistic formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of…
While supermassive black-hole (SMBH)-binaries are not the only viable source for the low-frequency gravitational wave background (GWB) signal evidenced by the most recent pulsar timing array (PTA) data sets, they are expected to be the most…
In stellar astrophysics, the technique of population synthesis has been successfully used for several decades. For planets, it is in contrast still a young method which only became important in recent years because of the rapid increase of…
We seek to quantify the fidelity with which modern population syntheses reproduce observations in view of their use as predictive tools. We compared synthetic populations from the Generation 3 Bern Model of Planet Formation and Evolution…
The stable rotation of young pulsars is often interrupted by two non-deterministic phenomena: glitches and red timing noise. Timing noise provides insights into plasma and nuclear physics under extreme conditions. The framework leverages…
Young isolated neutron stars (INS) most commonly manifest themselves as rotationally powered pulsars (RPPs) which involve conventional radio pulsars as well as gamma-ray pulsars (GRPs) and rotating radio transients (RRATs). Some other young…
Recurrent Neural Networks (RNNs) are popular models of brain function. The typical training strategy is to adjust their input-output behavior so that it matches that of the biological circuit of interest. Even though this strategy ensures…
Gravitational waves emitted by neutron star black hole mergers encode key properties of neutron stars - such as their size, maximum mass and spins - and black holes. However, the presence of matter and the high mass ratio makes generating…
Probing properties of neutron stars from photometric observations of these objects helps us answer crucial questions at the forefront of multi-messenger astronomy, such as, what is behavior of highest density matter in extreme environments…