Connecting radio pulsars, magnetars, and XDINSs in a unified evolutionary framework using simulation-based inference
astro-ph.HE
Submitted: 2026-09-01
Updated: 2026-09-01
Comments: 33 pages, 16 figures, 2 tables, accepted by ApJ
Code: https://github.com/ice-csic-astroexotic/ML-Poppyns
Project page: https://ice-csic-astroexotic.github.io/code/mlpoppyns
License: http://creativecommons.org/licenses/by/4.0/
The gist: Understanding the Galactic population of isolated neutron stars within a unified framework provides key insights into their birth properties, evolutionary pathways, and the connections between
Terminology
Abstract
Understanding the Galactic population of isolated neutron stars within a unified framework provides key insights into their birth properties, evolutionary pathways, and the connections between different neutron star classes. In this work, we aim to reproduce both the observed radio and quiescent X-ray emission from isolated neutron stars, including radio pulsars, magnetars and X-ray dim isolated neutron stars (XDINSs). We develop a comprehensive population synthesis framework that models neutron star birth properties, their dynamical, rotational, and magneto-thermal evolution, as well as radio and X-ray emission, and the selection effects of corresponding surveys. To simulate realistic X-ray spectra, we account for magnetospheric resonant cyclotron scattering and interstellar absorption. Additionally, we model the observational bias introduced by magnetar outbursts, by linking the outburst rate to magnetic stresses in the stellar crust. We then employ a simulation-based inference method, namely truncated sequential neural posterior estimation, to reconstruct the birth properties, such as the initial magnetic field distribution. We find that the Galactic neutron star population can be described by a two-component log-normal distribution of birth magnetic fields with peaks at 5 times 10 12 G and 10 14 G, respectively. We further find that the Galactic neutron star birth rate is around 3-4 per century. Our results help establish the contribution of neutron stars as central engines of powerful astrophysical transient phenomena, such as fast radio bursts, super-luminous supernovae and gamma ray bursts.
Sources
- Simulation-Based Inference with Neural Posterior Estimation applied to X-ray spectral fitting: Demonstration of working principles down to the Poisson regime
- Probing neutron star interiors and the properties of cold ultra-dense matter with the SKAO
- The X-ray luminosity of rotation-powered neutron stars
- 3D-$N_{\rm H}$-tool
- Automatic Posterior Transformation for Likelihood-Free Inference
- Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
- A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
- Adam: A Method for Stochastic Optimization
- Flexible statistical inference for mechanistic models of neural dynamics
- Fast $\epsilon$-free Inference of Simulation Models with Bayesian Conditional Density Estimation
- Magnetar fraction in Core-Collapse Supernovae
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Magnetars
- Long Period Transients (LPTs): a comprehensive review
- Probing the maximum energy of fast radio bursts using thousands of sources from the Second CHIME/FRB Catalog
- A Log-Uniform Initial Magnetic Field Distribution Explains Pulsar and Magnetar Populations through Magnetic Inclination Alignment
- The ROSAT All-Sky Survey Bright Source Catalogue
- The magnetar model's energy crisis for a prolific repeating fast radio burst source
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