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Physics-inspired deep learning to characterize the signal manifold of quasi-circular, spinning, non-precessing binary black hole mergers
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Deep learning ensemble for real-time gravitational wave detection of spinning binary black hole mergers
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On parallel laser beam merger in plasmas
Self-focusing instability is a well-known phenomenon of nonlinear optics, which is of great importance in the field of laser–plasma interactions. Self-focusing instability leads to beam focusing and, consequently, breakup into multiple laser filaments. The majority of applications tend to avoid a laser filamentation regime due to its detrimental role on laser spot profile and peak intensity. In our work, using nonlinear Schrödinger equation solver and particle-in-cell simulations, we address the problem of interaction of multiple parallel beams in plasmas. We consider both non-relativistic and moderately relativistic regimes and demonstrate how the physics of parallel beam interaction transitions from the familiar self- and mutual-focusing instabilities in the non-relativistic regime to a moderately relativistic regime, where an analytical description of filament interaction is not available.
Inferring Neutron Star Merger Ejecta Morphology with Kilonovae
In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.
A tale of two mergers: constraints on kilonova detection in two short GRBs at z~0.5
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Photon temporal-mode readout for inference of neutron star merger remnant gravitational waves
Gravitational waves emitted after neutron star binary coalescences and the information they carry about dense matter are a high-priority target for next-generation detectors. Even though such detectors are expected to observe millions of signals, detectable postmerger emission will remain rare. Here, in this work, we explore postmerger detectability and inference through an alternative detector readout scheme for data dominated by quantum-noise, which is the case above 1 kHz; photon-counting. In such a readout, signals and noise become quantized into discrete distributions corresponding to the detection of single photons measured in a chosen basis of modes. Through simulated data, we demonstrate that photon counting can be efficient even for weak signals. We find ∼1 in 100 signals with a postmerger signal-to-noise ratio of 0.2 can result in a single photon and thus be detected. Furthermore, after 2 ×10 4 signals—equivalent to 10 −2 to 1.5 years of observation—photon counting results in a twofold improvement in the measurement of the radius of a 1.6𝑀 ⊙ neutron star. Constraints can be further tightened if the detector classical noise is reduced. Photon counting offers a promising alternative to traditional homodyne readout techniques for extracting information from low signal-to-noise ratio postmerger signals.
Joint Electromagnetic and Gravitational Wave Inference of Binary Neutron Star Merger GW170817 Using Forward-Modeling Ejecta Predictions
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Uncertainty quantification for neutrino opacities in core-collapse supernovae and neutron star mergers
We perform an extensive study of the correlations between the neutrino-nucleon inverse mean free paths (IMFPs) and the underlying equation of states (EoSs). Strong interaction uncertainties in the neutrino mean free path are investigated in different density regimes. The nucleon effective mass, the nucleon chemical potentials, and the residual interactions in the medium play an important role in determining neutrino-nucleon interactions in a density-dependent manner. Here we study how the above quantities are constrained by an EoS consistent with (i) nuclear mass measurements, (ii) proton-proton scattering phase shifts, and (iii) neutron star observations. We then study the uncertainties of both the charged current and the neutral current neutrino-nucleon inverse mean free paths due to the variation of these quantities, using the Hartree-Fock+random phase approximation method. Finally, we calculate the Pearson correlation coefficients between (i) the EoS-based quantities and the EoS-based quantities; (ii) the EoS-based quantities and the IMFPs; (iii) the IMFPs and the IMFPs. We find a strong impact of residual interactions on neutrino opacity in the spin and spin-isospin channels, which are not well constrained by current nuclear modelings.
Anisotropy of the stochastic gravitational wave background from sub-horizon-collapsed primordial black hole mergers
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Effects of annihilation with low-energy neutrinos on high-energy neutrinos from binary neutron star mergers and rare core-collapse supernovae
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Relativistic bulk rheology: From neutron star mergers to viscous cosmology
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Revealing phase transition in dense matter with gravitational wave spectroscopy of binary neutron star mergers
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Viscous hydrodynamic evolution of neutron star merger accretion disks: A code comparison
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Using equation of state constraints to classify low-mass compact binary mergers
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Bulk viscosity of two-color superconducting quark matter in neutron star mergers
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