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In this paper, we derive correlations between core-collapse supernova observables and progenitor core structures that emerge from our suite of 20 state-of-the-art 3D core-collapse supernova simulations carried to late times. This is the largest such collection of 3D supernova models ever generated and allows one to witness and derive testable patterns that might otherwise be obscured when studying one or a few models in isolation. From this panoramic perspective, we have discovered correlations between explosion energy, neutron star gravitational birth masses,⁵⁶Ni andα-rich freezeout yields, and pulsar kicks and theoretically important correlations with the compactness parameter of progenitor structure. We find a correlation between explosion energy and progenitor mantle binding energy, suggesting that such explosions are self-regulating. We also find a testable correlation between explosion energy and measures of explosion asymmetry, such as the ejecta energy and mass dipoles. While the correlations between two observables are roughly independent of the progenitor zero-age main-sequence (ZAMS) mass, the many correlations we derive with compactness cannot unambiguously be tied to a particular progenitor ZAMS mass. This relationship depends on the compactness/ZAMS mass mapping associated with the massive star progenitor models employed. Therefore, our derived correlations between compactness and observables may be more robust than with ZAMS mass but can nevertheless be used in the future once massive star modeling has converged.

 

Using 20 long-term 3D core-collapse supernova simulations, we find that lower compactness progenitors that explode quasi-spherically due to the short delay to explosion experience smaller neutron star recoil kicks in the ∼100−200 km s⁻¹range, while higher compactness progenitors that explode later and more aspherically leave neutron stars with kicks in the ∼300−1000 km s⁻¹range. In addition, we find that these two classes are correlated with the gravitational mass of the neutron star. This correlation suggests that the survival of binary neutron star systems may in part be due to their lower kick speeds. We also find a correlation between the kick and both the mass dipole of the ejecta and the explosion energy. Furthermore, one channel of black hole birth leaves masses of ∼10M_⊙, is not accompanied by a neutrino-driven explosion, and experiences small kicks. A second channel is through a vigorous explosion that leaves behind a black hole with a mass of ∼3.0M_⊙kicked to high speeds. We find that the induced spins of nascent neutron stars range from seconds to ∼10 ms, but do not yet see a significant spin/kick correlation for pulsars. We suggest that if an initial spin biases the explosion direction, a spin/kick correlation would be a common byproduct of the neutrino mechanism of core-collapse supernovae. Finally, the induced spin in explosive black hole formation is likely large and in the collapsar range. This new 3D model suite provides a greatly expanded perspective and appears to explain some observed pulsar properties by default.

 

We present in this paper a public data release of an unprecedentedly large set of core-collapse supernova (CCSN) neutrino emission models, comprising 100 detailed 2D axisymmetric radiation-hydrodynamic simulations evolved out to as late as ∼5 s post-bounce and spanning an extensive range of massive-star progenitors. The motivation for this paper is to provide a physically and numerically uniform benchmark data set to the broader neutrino detection community to help it characterize and optimize subsurface facilities for what is likely to be a once-in-a-lifetime galactic supernova burst event. With this release, we hope to (1) help the international experiment and modelling communities more efficiently optimize the retrieval of physical information about the next galactic CCSN, (2) facilitate the better understanding of core-collapse theory and modelling among interested experimentalists, and (3) help further integrate the broader supernova neutrino community.

 

We have simulated the collapse and evolution of the core of a solar-metallicity 40M_⊙star and find that it explodes vigorously by the neutrino mechanism, despite its very high “compactness.” Within ∼1.5 s of explosion, a black hole forms. The explosion is very asymmetrical and has a total explosion energy of ∼1.6 × 10⁵¹erg. At black hole formation, its baryon mass is ∼2.434M_⊙and gravitational mass is 2.286M_⊙. Seven seconds after black hole formation, an additional ∼0.2M_⊙is accreted, leaving a black hole baryon mass of ∼2.63M_⊙. A disk forms around the proto−neutron star, from which a pair of neutrino-driven jets emanates. These jets accelerate some of the matter up to speeds of ∼45,000 km s⁻¹and contain matter with entropies of ∼50. The large spatial asymmetry in the explosion results in a residual black hole recoil speed of ∼1000 km s⁻¹. This novel black hole formation channel now joins the other black hole formation channel between ∼12 and ∼15M_⊙discovered previously and implies that the black hole/neutron star birth ratio for solar-metallicity stars could be ∼20%. However, one channel leaves black holes in perhaps the ∼5–15M_⊙range with low kick speeds, while the other leaves black holes in perhaps the ∼2.5–3.0M_⊙mass range with high kick speeds. However, even ∼8.8 s after core bounce the newly formed black hole is still accreting at a rate of ∼2 × 10⁻²M_⊙s⁻¹, and whether the black hole eventually achieves a significantly larger mass over time is yet to be determined.

 

We analyze the directional dependence of the gravitational wave (GW) emission from 15 3D neutrino radiation hydrodynamic simulations of core-collapse supernovae (CCSNe). Using spin weighted spherical harmonics, we develop a new analytic technique to quantify the evolution of the distribution of GW emission over all angles. We construct a physics-informed toy model that can be used to approximate GW distributions for general ellipsoid-like systems, and use it to provide closed form expressions for the distribution of GWs for different CCSN phases. Using these toy models, we approximate the protoneutron star (PNS) dynamics during multiple CCSN stages and obtain similar GW distributions to simulation outputs. When considering all viewing angles, we apply this new technique to quantify the evolution of preferred directions of GW emission. For nonrotating cases, this dominant viewing angle drifts isotropically throughout the supernova, set by the dynamical timescale of the PNS. For rotating cases, during core bounce and the following tens of milliseconds, the strongest GW signal is observed along the equator. During the accretion phase, comparable—if not stronger—GW amplitudes are generated along the axis of rotation, which can be enhanced by the lowT/∣W∣ instability. We show two dominant factors influencing the directionality of GW emission are the degree of initial rotation and explosion morphology. Lastly, looking forward, we note the sensitive interplay between GW detector site and supernova orientation, along with its effect on detecting individual polarization modes.

 

Abstract Most existing criteria derived from progenitor properties of core-collapse supernovae are not very accurate in predicting explosion outcomes. We present a novel look at identifying the explosion outcome of core-collapse supernovae using a machine-learning approach. Informed by a sample of 100 2D axisymmetric supernova simulations evolved with F ornax , we train and evaluate a random forest classifier as an explosion predictor. Furthermore, we examine physics-based feature sets including the compactness parameter, the Ertl condition, and a newly developed set that characterizes the silicon/oxygen interface. With over 1500 supernovae progenitors from 9−27 M ⊙ , we additionally train an autoencoder to extract physics-agnostic features directly from the progenitor density profiles. We find that the density profiles alone contain meaningful information regarding their explodability. Both the silicon/oxygen and autoencoder features predict the explosion outcome with ≈90% accuracy. In anticipation of much larger multidimensional simulation sets, we identify future directions in which machine-learning applications will be useful beyond the explosion outcome prediction. 

Calibrating with detailed 2D core-collapse supernova (CCSN) simulations, we derive a simple CCSN explosion condition based solely upon the terminal density profiles of state-of-the-art stellar evolution calculations of the progenitor massive stars. This condition captures the vast majority of the behaviour of the one hundred 2D state-of-the-art models we performed to gauge its usefulness. The goal is to predict, without resort to detailed simulation, the explodability of a given massive star. We find that the simple maximum fractional ram pressure jump discriminant we define works well ∼90 per cent of the time and we speculate on the origin of the few false positives and false negatives we witness. The maximum ram pressure jump generally occurs at the time of accretion of the silicon/oxygen interface, but not always. Our results depend upon the fidelity with which the current implementation of our code F ornax adheres to Nature and issues concerning the neutrino–matter interaction, the nuclear equation of state, the possible effects of neutrino oscillations, grid resolution, the possible role of rotation and magnetic fields, and the accuracy of the numerical algorithms employed remain to be resolved. Nevertheless, the explodability condition we obtain is simple to implement, shows promise that it might be further generalized while still employing data from only the unstable Chandrasekhar progenitors, and is a more credible and robust simple explosion predictor than can currently be found in the literature.

 

In this paper, we present a novel method to estimate the time evolution of the proto-neutron star (PNS) structure from the neutrino signal in a core-collapse supernova (CCSN). Employing recent results from multidimensional CCSN simulations, we delve into a relation between the total emitted neutrino energy (TONE) and PNS mass/radius, and we find that they are strongly correlated with each other. We fit the relation by simple polynomial functions connecting the TONE to the mass and radius of the PNS as a function of time. By combining another fitting function representing the correlation between the TONE and the cumulative number of events at each neutrino observatory, the PNS mass and radius can be retrieved from purely observed neutrino data. We demonstrate retrievals of PNS mass and radius from mock data of the neutrino signal, and we assess the capability of our proposed method. While underlining the limitations of the method, we also discuss the importance of the joint analysis with the gravitational wave signal. This would reduce uncertainties of parameter estimations in our method, and may narrow down the possible neutrino oscillation model. The proposed method is a very easy and inexpensive computation, which will be useful in real data analysis of the CCSN neutrino signal.