Detecting Hyperons in neutron stars -- a machine learning approach
arXiv:2409.12684 · doi:10.1103/PhysRevD.110.123016
Abstract
We present a neural network classification model for detecting the presence of hyperonic degrees of freedom in neutron stars. The models take radii and/or tidal deformabilities as input and give the probability for the presence of hyperons in the neutron star composition. Different numbers of observations and different levels of uncertainty in the neutron star properties are tested. The models have been trained on a dataset of well-calibrated microscopic equations of state of neutron star matter based on a relativistic mean-field formalism. Real data and data generated from a different description of hyperonic matter are used to test the performance of the models.
15 pages, 8 figures, published version
References in corpus (73)
- Shapiro delay measurement of a two solar mass neutron star
- A Massive Pulsar in a Compact Relativistic Binary
- GW190814: Gravitational Waves from the Coalescence of a 23 M Black Hole with a 2.6 M Compact Object
- PSR J0030+0451 Mass and Radius from NICER Data and Implications for the Properties of Neutron Star Matter
- A NICER View of PSR J0030+0451: Millisecond Pulsar Parameter Estimation
- Tidal Love numbers of neutron stars
- Properties of the binary neutron star merger GW170817
- A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy
- Gravitational-wave constraints on the neutron-star-matter Equation of State
- Refined Mass and Geometric Measurements of the High-Mass PSR J0740+6620
- Composition and thermodynamics of nuclear matter with light clusters
- Equation of state and neutron star properties constrained by nuclear physics and observation
- Neutron-Rich Nuclei in Heaven and Earth
- Evidence for quark-matter cores in massive neutron stars
- The NANOGrav Nine-year Data Set: Mass and Geometric Measurements of Binary Millisecond Pulsars
- The NANOGrav 11-year Data Set: High-precision timing of 45 Millisecond Pulsars
- Cold Quark Matter
- Relativistic Mean-Field Hadronic Models under Nuclear Matter Constraints
- Chiral interactions up to next-to-next-to-next-to-leading order and nuclear saturation
- Hyperon Puzzle: Hints from Quantum Monte Carlo Calculations
- A critical examination of constraints on the equation of state of dense matter obtained from GW170817
- The enhanced X-ray Timing and Polarimetry mission - eXTP
- Constraining Neutron-Star Matter with Microscopic and Macroscopic Collisions
- Hyperons and massive neutron stars: the role of hyperon potentials
- Building relativistic mean field models for finite nuclei and neutron stars
- A NICER View of the Nearest and Brightest Millisecond Pulsar: PSR J0437$\unicode{x2013}$4715
- Neutron Stars and the Nuclear Equation of State
- Do hyperons exist in the interior of neutron stars ?
- Constraining neutron star matter with QCD
- Strangeness in Nuclei and Neutron Stars
- Hyperons in neutron-star cores and two-solar-mass pulsar
- On the Sound Speed in Neutron Stars
- Non-parametric inference of the neutron star equation of state from gravitational wave observations
- Nonparametric Inference of Neutron Star Composition, Equation of State, and Maximum Mass with GW170817
- GW190814: Impact of a 2.6 solar mass neutron star on nucleonic equations of state
- Estimation of the effect of hyperonic three-body forces on the maximum mass of neutron stars
- Perturbative Thermal QCD: Formalism and Applications
- Dense matter with eXTP
- (No) neutron star maximum mass constraint from hypernuclei
- PSR J1810+1744: Companion Darkening and a Precise High Neutron Star Mass
- Ab-initio QCD calculations impact the inference of the neutron-star-matter equation of state
- Mapping neutron star data to the equation of state using the deep neural network
- The Equation of State for the Nucleonic and Hyperonic Core of Neutron Stars
- Accurate determination of the interaction between hyperons and nucleons from auxiliary field diffusion Monte Carlo calculations
- A Detailed Examination of Astrophysical Constraints on the Symmetry Energy and the Neutron Skin of Pb with Minimal Modeling Assumptions
- Neutron stars with hyperon cores: stellar radii and EOS near nuclear density
- Relativistic description of dense matter equation of state and compatibility with neutron star observables: a Bayesian approach
- Exploring QCD matter in extreme conditions with Machine Learning
- Methodology study of machine learning for the neutron star equation of state
- Hyperonic stars and the symmetry energy
- Relativistic hypernuclear compact stars with calibrated equations of state
- The neutron star mass, distance, and inclination from precision timing of the brilliant millisecond pulsar J04374715
- Investigating Signatures of Phase Transitions in Neutron-Star Cores
- Neural networks reconstruction of the dense-matter equation of state from neutron-star parameters
- Extensive Studies of the Neutron Star Equation of State from the Deep Learning Inference with the Observational Data Augmentation
- Spanning the full range of neutron star properties within a microscopic description
- Imprint of the symmetry energy on the inner crust and strangeness content of neutron stars
- A Hybrid Ensemble Learning Approach to Star-Galaxy Classification
- Neural network reconstruction of the dense matter equation of state from neutron star observables
- Reconstructing the neutron star equation of state from observational data via automatic differentiation
- Bayesian nonparametric inference of neutron star equation of state via neural network
- Unveiling the nuclear matter EoS from neutron star properties: a supervised machine learning approach
- Astrophysical implications on hyperon couplings and hyperon star properties with relativistic equations of states
- Nucleonic metamodelling in light of multimessenger, PREX-II and CREX data
- Bayesian inference of signatures of hyperons inside neutron stars
- Translating neutron star observations to nuclear symmetry energy via artificial neural networks
- Extracting nuclear matter properties from the neutron star matter equation of state using deep neural networks
- Structure of Quark Star: A Comparative Analysis of Bayesian Inference and Neural Network Based Modeling
- Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks
- From NS observations to nuclear matter properties: a machine learning approach
- Neural Simulation-Based Inference of the Neutron Star Equation of State directly from Telescope Spectra
- Detecting dense-matter phase transition signatures in neutron star mass-radius measurements as data anomalies using normalising flows
- Detecting the third family of compact stars with normalizing flows