Deep-Learning Classification and Parameter Inference of Rotational Core-Collapse Supernovae

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Nunes, Solange, Escrig, Gabriel, Freitas, Osvaldo G., Font, José A., Fernandes, Tiago, Onofre, Antonio, Torres-Forné, Alejandro
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms
di: Freitas, Osvaldo Gramaxo, et al.
Pubblicazione: (2024)

An autoencoder-based surrogate waveform model for quasi-circular binary-black-hole mergers
di: Theodoropoulos, Anastasios, et al.
Pubblicazione: (2026)

Classification of the equation of state of neutron stars via sparse dictionary learning
di: Llorens-Monteagudo, Miquel, et al.
Pubblicazione: (2025)

Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
di: Freitas, Osvaldo Gramaxo, et al.
Pubblicazione: (2023)

Gravitational Waves from Neutrino-Driven Core Collapse Supernovae: Predictions, Detection, and Parameter Estimation
di: Mezzacappa, Anthony, et al.
Pubblicazione: (2024)

Approximating General Relativity in Core-Collapse Supernova Simulations
di: Fromm, Steven A., et al.
Pubblicazione: (2026)

Detecting Gravitational Wave Memory in the Next Galactic Core-Collapse Supernova
di: Richardson, Colter J., et al.
Pubblicazione: (2024)

VIGILant: an automatic classification pipeline for glitches in the Virgo detector
di: Fernandes, Tiago, et al.
Pubblicazione: (2026)

Low-Frequency Gravitational Waves in Three-Dimensional Core-Collapse Supernova Models
di: Richardson, Colter J., et al.
Pubblicazione: (2025)

Rapidly Rotating Neutron Star Collapse in Massive Scalar-Tensor Theories
di: M., José Carlos Olvera, et al.
Pubblicazione: (2026)

Core Collapse Supernova Gravitational Wave Sourcing and Characterization based on Three-Dimensional Models
di: Murphy, R. Daniel, et al.
Pubblicazione: (2025)

Waveform Reconstruction of Core-Collapse Supernovae Gravitational-Waves with Ensemble Empirical Mode Decomposition
di: Yuan, Yong, et al.
Pubblicazione: (2023)

Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders
di: Bada-Nerin, Roberto, et al.
Pubblicazione: (2024)

Bayesian inference from gravitational waves in fast-rotating, core-collapse supernovae
di: Pastor-Marcos, Carlos, et al.
Pubblicazione: (2023)

Towards asteroseismology of neutron stars with physics-informed neural networks
di: Tseneklidou, Dimitra, et al.
Pubblicazione: (2025)

Dependence of the Reconstructed Core-Collapse Supernova Gravitational Wave High-Frequency Feature on the Nuclear Equation of State, in Real Interferometric Data
di: Murphy, R. Daniel, et al.
Pubblicazione: (2024)

An Optically Targeted Search for Gravitational Waves emitted by Core-Collapse Supernovae during the Third Observing Run of Advanced LIGO and Advanced Virgo
di: Szczepańczyk, Marek J., et al.
Pubblicazione: (2023)

Rapid detection of gravitational waves from binary black hole mergers using sparse dictionary learning
di: Badger, Charles, et al.
Pubblicazione: (2024)

Quantum Bayesian Inference with Renormalization for Gravitational Waves
di: Escrig, Gabriel, et al.
Pubblicazione: (2024)

Core-Collapse Supernovae and their Gravitational Wave Signals: The Status of Theory and Modeling
di: Müller, Bernhard
Pubblicazione: (2026)

Gravitational-Wave and Gravitational-Wave Memory Signatures of Core-Collapse Supernovae
di: Choi, Lyla, et al.
Pubblicazione: (2024)

Assessing Matched Filtering for Core-Collapse Supernova Gravitational-Wave Detection
di: Andresen, Haakon, et al.
Pubblicazione: (2024)

Proto-neutron star oscillations including accretion flows
di: Tseneklidou, Dimitra, et al.
Pubblicazione: (2025)

Determining the core-collapse supernova explosion mechanism with current and future gravitational-wave observatories
di: Powell, Jade, et al.
Pubblicazione: (2023)

Solving the Teukolsky equation with physics-informed neural networks
di: Luna, Raimon, et al.
Pubblicazione: (2022)

A Black-Hole Excision Scheme for General Relativistic Core-Collapse Supernova Simulations
di: Sykes, B., et al.
Pubblicazione: (2022)

Observing boson stars in binary systems: The case of Gaia BH1
di: Passos, Pedro, et al.
Pubblicazione: (2025)

Evaluating Machine Learning Models for Supernova Gravitational Wave Signal Classification
di: Abylkairov, Y. Sultan, et al.
Pubblicazione: (2024)

The Impact of Astrophysical Priors on Parameter Inference for GW230529
di: Chattopadhyay, Debatri, et al.
Pubblicazione: (2024)

Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors
di: Akhmetali, Almat, et al.
Pubblicazione: (2026)

A Black Hole is Born: 3D GRMHD Simulation of Black Hole Formation from Core-Collapse
di: Halevi, Goni, et al.
Pubblicazione: (2025)

Comparing advanced-era interferometric gravitational-wave detector network configurations: sky localization and source properties
di: Emma, Mattia, et al.
Pubblicazione: (2024)

Probing Supernovae through gravitational wave entropy
di: Sakan, Aknur, et al.
Pubblicazione: (2025)

Non-Equilibrium Relativistic Core Collapse of Self-Interacting Dark Matter Halos -- Limits On Seed Black Hole Mass
di: Gu, Hua-Peng, et al.
Pubblicazione: (2026)

Gravitational Wave Informed Inference of 21-cm Global Signal Parameters
di: Tiwari, Avinash, et al.
Pubblicazione: (2026)

Uncovering Correlations and Biases in Parameter Inference from Neutron-Star Pulse Profile Modeling
di: Zhao, Tong, et al.
Pubblicazione: (2024)

Resonant amplification of multimessenger emission in rotating stellar core collapse
di: Cusinato, Marco, et al.
Pubblicazione: (2025)

Black hole spectroscopy with ground-based atom interferometer and space-based laser interferometer gravitational wave detectors
di: Torres-Orjuela, Alejandro
Pubblicazione: (2024)

Joint gravitational wave detection by TianQin and LISA
di: Torres-Orjuela, Alejandro
Pubblicazione: (2024)

Assessing Universal Relations for Rapidly Rotating Neutron Stars: Insights from an Interpretable Deep Learning Perspective
di: Papigkiotis, Grigorios, et al.
Pubblicazione: (2025)