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Register a new userChimera: A massively parallel code for core-collapse supernova simulation
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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.
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Unraveling the mechanism for core-collapse supernova explosions is an outstanding computational challenge and the problem remains essentially unsolved despite more than four decades of effort. However, much progress in realistic modeling has occurred recently through the availability of multi-teraflop machines and the increasing sophistication of supernova codes. These improvements have led to some key insights which may clarify the picture in the not too distant future. Here we briefly review the current status of the three explosion mechanisms (acoustic, MHD, and neutrino heating) that are currently under active investigation, concentrating on the neutrino heating mechanism as the one most likely responsible for producing explosions from progenitors in the mass range ~10 to ~25 solar masses. We then briefly describe the CHIMERA code, a supernova code we have developed to simulate core-collapse supernovae in 1, 2, and 3 spatial dimensions. We finally describe the results of an ongoing suite of 2D simulations initiated from a 12, 15, 20, and 25 solar mass progenitor. These have all exhibited explosions and are currently in the expanding phase with the shock at between 5,000 and 10,000 km. We finally very briefly describe an ongoing simulation in 3 spatial dimensions initiated from the 15 solar mass progenitor.
Much progress in realistic modeling of core-collapse supernovae has occurred recently through the availability of multi-teraflop machines and the increasing sophistication of supernova codes. These improvements are enabling simulations with enough realism that the explosion mechanism, long a mystery, may soon be delineated. We briefly describe the CHIMERA code, a supernova code we have developed to simulate core-collapse supernovae in 1, 2, and 3 spatial dimensions. We then describe the results of an ongoing suite of 2D simulations initiated from a 12, 15, 20, and 25 solar mass progenitor. These have all exhibited explosions and are currently in the expanding phase with the shock at between 5,000 and 20,000 km. We also briefly describe an ongoing simulation in 3 spatial dimensions initiated from the 15 solar mass progenitor.
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.
This paper describes the design and implementation of our new multi-group, multi-dimensional radiation hydrodynamics (RHD) code Fornax and provides a suite of code tests to validate its application in a wide range of physical regimes. Instead of focusing exclusively on tests of neutrino radiation hydrodynamics relevant to the core-collapse supernova problem for which Fornax is primarily intended, we present here classical and rigorous demonstrations of code performance relevant to a broad range of multi-dimensional hydrodynamic and multi-group radiation hydrodynamic problems. Our code solves the comoving-frame radiation moment equations using the M1 closure, utilizes conservative high-order reconstruction, employs semi-explicit matter and radiation transport via a high-order time stepping scheme, and is suitable for application to a wide range of astrophysical problems. To this end, we first describe the philosophy, algorithms, and methodologies of Fornax and then perform numerous stringent code tests, that collectively and vigorously exercise the code, demonstrate the excellent numerical fidelity with which it captures the many physical effects of radiation hydrodynamics, and show excellent strong scaling well above 100k MPI tasks.
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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