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Register a new userDeep learning for multimessenger core-collapse supernova detection
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The detection of gravitational waves from core-collapse supernova (CCSN) explosions is a challenging task, yet to be achieved, in which it is key the connection between multiple messengers, including neutrinos and electromagnetic signals. In this work, we present a method for detecting these kind of signals based on machine learning techniques. We tested its robustness by injecting signals in the real noise data taken by the Advanced LIGO-Virgo network during the second observation run, O2. We trained a newly developed Mini-Inception Resnet neural network using time-frequency images corresponding to injections of simulated phenomenological signals, which mimic the waveforms obtained in 3D numerical simulations of CCSNe. With this algorithm we were able to identify signals from both our phenomenological template bank and from actual numerical 3D simulations of CCSNe. We computed the detection efficiency versus the source distance, obtaining that, for signal to noise ratio higher than 15, the detection efficiency is 70 % at a false alarm rate lower than 5%. We notice also that, in the case of O2 run, it would have been possible to detect signals emitted at 1 kpc of distance, whilst lowering down the efficiency to 60%, the event distance reaches values up to 14 kpc.
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We investigate correlated gravitational wave and neutrino signals from rotating core-collapse supernovae with simulations. Using an improved mode identification procedure based on mode function matching, we show that a linear quadrupolar mode of the core produces a dual imprint on gravitational waves and neutrinos in the early post-bounce phase of the supernova. The angular harmonics of the neutrino emission are consistent with the mode energy around the neutrinospheres, which points to a mechanism for the imprint on neutrinos. Thus, neutrinos carry information about the mode amplitude in the outer region of the core, whereas gravitational waves probe deeper in. We also find that the best-fit mode function has a frequency bounded above by $sim 420$ Hz, and yet the modes frequency in our simulations is $sim 15%$ higher, due to the use of Newtonian hydrodynamics and a widely used pseudo-Newtonian gravity approximation. This overestimation is particularly important for the analysis of gravitational wave detectability and asteroseismology, pointing to limitations of pseudo-Newtonian approaches for these purposes, possibly even resulting in excitation of incorrect modes. In addition, mode frequency matching (as opposed to mode function matching) could be resulting in mode misidentification in recent work. Lastly, we evaluate the prospects of a multimessenger detection of the mode using current technology. The detection of the imprint on neutrinos is most challenging, with a maximum detection distance of $sim!1$ kpc using the IceCube Neutrino Observatory. The maximum distance for detecting the complementary gravitational wave imprint is $sim!5$ kpc using Advanced LIGO at design sensitivity.
RES-NOVA is a new proposed experiment for the investigation of astrophysical neutrino sources with archaeological Pb-based cryogenic detectors. RES-NOVA will exploit Coherent Elastic neutrino-Nucleus Scattering (CE$ u$NS) as detection channel, thus it will be equally sensitive to all neutrino flavors produced by Supernovae (SNe). RES-NOVA with only a total active volume of (60 cm)$^3$ and an energy threshold of 1 keV will probe the entire Milky Way Galaxy for (failed) core-collapse SNe with $> 3 sigma$ detection significance. The high detector modularity makes RES-NOVA ideal also for reconstructing the main parameters (e.g. average neutrino energy, star binding energy) of SNe occurring in our vicinity, without deterioration of the detector performance caused by the high neutrino interaction rate. For the first time, distances $<3$ kpc can be surveyed, similarly to the ones where all known past galactic SNe happened. We discuss the RES-NOVA potential, accounting for a realistic setup, considering the detector geometry, modularity and background level in the region of interest. We report on the RES-NOVA background model and on the sensitivity to SN neutrinos as a function of the distance travelled by neutrinos.
We trained deep neural networks (DNNs) as a function of the neutrino energy density, flux, and the fluid velocity to reproduce the Eddington tensor for neutrinos obtained in our first-principles core-collapse supernova (CCSN) simulations. Although the moment method, which is one of the most popular approximations for neutrino transport, requires a closure relation, none of the analytical closure relations commonly employed in the literature captures all aspects of the neutrino angular distribution in momentum space. In this paper, we developed a closure relation by using the DNN that takes the neutrino energy density, flux, and the fluid velocity as the input and the Eddington tensor as the output. We consider two kinds of DNNs: a conventional DNN named a component-wise neural network (CWNN) and a tensor-basis neural network (TBNN). We found that the diagonal component of the Eddington tensor is reproduced better by the DNNs than the M1-closure relation especially for low to intermediate energies. For the off-diagonal component, the DNNs agree better with the Boltzmann solver than the M1 closure at large radii. In the comparison between the two DNNs, the TBNN has slightly better performance than the CWNN. With the new closure relations at hand based on the DNNs that well reproduce the Eddington tensor with much smaller costs, we opened up a new possibility for the moment method.
We provide a detailed description of the Chimera code, a code developed to model core collapse supernovae in multiple spatial dimensions. The core collapse supernova explosion mechanism remains the subject of intense research. Progress to date demonstrates that it involves a complex interplay of neutrino production, transport, and interaction in the stellar core, three-dimensional stellar core fluid dynamics and its associated instabilities, nuclear burning, and the foundational physics of the neutrino-stellar core weak interactions and the equations of state of all stellar core constituents -particularly, the nuclear equation of state associated with nucleons, both free and bound in nuclei. Chimera, by incorporating detailed neutrino transport, realistic neutrino-matter interactions, three-dimensional hydrodynamics, realistic nuclear, leptonic, and photonic equations of state, and a nuclear reaction network, along with other refinements, can be used to study the role of neutrino radiation, hydrodynamic instabilities, and a variety of input physics in the explosion mechanism itself. It can also be used to compute observables such as neutrino signatures, gravitational radiation, and the products of nucleosynthesis associated with core collapse supernovae. The code contains modules for neutrino transport, multidimensional compressible hydrodynamics, nuclear reactions, a variety of neutrino interactions, equations of state, and modules to provide data for post-processing observables such as the products of nucleosynthesis, and gravitational radiation. Chimera is an evolving code, being updated periodically with improved input physics and numerical refinements. We detail here the current version of the code, from which future improvements will stem, which can in turn be described as needed in future publications.
Most supernova explosions accompany the death of a massive star. These explosions give birth to neutron stars and black holes and eject solar masses of heavy elements. However, determining the mechanism of explosion has been a half-century journey of great complexity. In this paper, we present our perspective of the status of this theoretical quest and the physics and astrophysics upon which its resolution seems to depend. The delayed neutrino-heating mechanism is emerging as a robust solution, but there remain many issues to address, not the least of which involves the chaos of the dynamics, before victory can unambiguously be declared. It is impossible to review in detail all aspects of this multi-faceted, more-than-half-century-long theoretical quest. Rather, we here map out the major ingredients of explosion and the emerging systematics of the observables with progenitor mass, as we currently see them. Our discussion will of necessity be speculative in parts, and many of the ideas may not survive future scrutiny. Some statements may be viewed as informed predictions concerning the numerous observables that rightly exercise astronomers witnessing and diagnosing the supernova Universe. Importantly, the same explosion in the inside, by the same mechanism, can look very different in photons, depending upon the mass and radius of the star upon explosion. A 10$^{51}$-erg (one Bethe) explosion of a red supergiant with a massive hydrogen-rich envelope, a diminished hydrogen envelope, no hydrogen envelope, and, perhaps, no hydrogen envelope or helium shell all look very different, yet might have the same core and explosion evolution.
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