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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Coupling neutrino oscillations and simulations of core-collapse supernovae

At the present time even the most sophisticated, multidimensional simulations of core-collapse supernovae do not (self-consistently) include neutrino flavor transformation. This physics is missing despite the importance of neutrinos in the core-collapse explosion paradigm. Because of this dependence, any flavor transformation that occurs in the region between the protoneutron star and the shock could result in major effects upon the dynamics of the explosion. Here, we present the first hydrodynamic core-collapse supernova simulation which simultaneously includes flavor transformation of the free-streaming neutrinos in the neutrino transport. These oscillation calculations are dynamically updated and evolve self-consistently alongside the hydrodynamics. Using a M = 20 M ⊙ progenitor, we find that while the oscillations have an effect on the neutrino emission and the heating rates, flavor transformation alone does not lead to a successful explosion of this progenitor in spherical symmetry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Impact of binary interactions on the diffuse supernova neutrino background

Binary interactions, especially mass transfer and mergers, can strongly influence the evolution of massive stars and change their final properties and the occurrence of supernovae. Here, we investigate how binary interactions affect predictions of the diffuse flux of neutrinos. By performing stellar population syntheses including prescriptions for binary interactions, we show that the resulting detection rates of the diffuse supernova neutrino background is enhanced by 15%–20% compared to estimates without binary considerations. A source of significant uncertainty arises due to the presently sparse knowledge of the evolution of rapidly rotating carbon-oxygen cores, especially those created as a result of mergers near the white dwarf to core collapse boundary. As a result, the enhancement effect may be as small as a few percent if the effects of rotation in postmerger systems are neglected, or as large as 75% if trends are extrapolated. Our estimates serve to highlight that binary effects can be important.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Time dependent signatures of core-collapse supernova neutrinos at HALO

In this work, we calculate the response of a lead-based detector, such as the Helium and Lead Observatory (HALO) or its planned upgrade HALO-1kt to a Galactic core-collapse supernova. We pay particular attention to the time dependence of the reaction rates. All reaction rates decrease as the neutrino luminosity exponentially drops during the cooling period, but the ratio of one-neutron (1n) to two-neutron (2n) event rates in HALO is independent of this overall decrease. Nevertheless, we find that this ratio still changes with time due to the changing character of neutrino flavor transformations with the evolving conditions in the supernova. In the case of inverted hierarchy, this is caused by the fact that the spectral splits become less and less sharp with the decreasing luminosity. In the case of normal hierarchy, it is caused by the passage of the shock wave through the Mikheyev-Smirnov-Wolfenstein resonance region. However, in both cases, we find that the change in the ratio of 1n to 2n event rates is limited to a few percent.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Inference of bipolar neutrino flavor oscillations near a core-collapse supernova based on multiple measurements at Earth

Neutrinos in compact-object environments, such as core-collapse supernovae, can experience various kinds of collective effects in flavor space, engendered by neutrino-neutrino interactions. These include “bipolar” collective oscillations, which are exhibited by neutrino ensembles where different flavors dominate at different energies. Considering the importance of neutrinos in the dynamics and nucleosynthesis in these environments, it is desirable to ascertain whether an Earth-based detection could contain signatures of bipolar oscillations that occurred within a supernova envelope. To that end, we, in this study, continue examining a cost-function formulation of statistical data assimilation (SDA) to infer solutions to a small-scale model of neutrino flavor transformation. SDA is an inference paradigm designed to optimize a model with sparse data. Our model consists of two monoenergetic neutrino beams with different energies emanating from a source and coherently interacting with each other and with a matter background, with radially varying interaction strengths. We attempt to infer flavor transformation histories of these beams using simulated measurements of the flavor content at locations “in vacuum” (that is, far from the source), which could in principle correspond to Earth-based detectors. Within the scope of this small-scale model, we found that: (i) based on such measurements, the SDA procedure is able to infer whether bipolar oscillations had occurred within the protoneutron star envelope, and (ii) if the measurements sample the full amplitude of the neutrino oscillations in vacuum, then the amplitude of the prior bipolar oscillations is well predicted. This result intimates that the inference paradigm can well complement numerical integration codes, via its ability to infer flavor evolution at physically inaccessible locations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine Learning-Based Extreme Data Reduction for Prompt Supernova Pointing at DUNE

One of the goals of the Deep Underground Neutrino Experiment (DUNE) is to use the massive underground liquid argon time projection chamber (LArTPC) detectors at its far site for multimessenger astronomy (MMA), in the detection of neutrinos from core-collapse supernovae (SNe). Its current baseline trigger strategy detects activity in the detector that is consistent with supernova (SN) neutrinos and saves the raw data for further offline analysis but provides no prompt pointing information crucial for optical follow-ups by other observatories. This approach is based on the assumption that prompt pointing determination using raw data is computationally prohibitive. In this article, we demonstrate a proof-of-concept based on applying extreme data reduction on the buffered SN data in the DUNE data acquisition (DAQ) system’s front-end computers using a machine learning (ML) workflow. This reduces the data by ~5 orders of magnitude, allowing a full track reconstruction to be carried out quickly on a single server. The total time to perform the ML-based data reduction and the full track reconstruction is less than the time to transfer the SN data back to Fermilab or a high-performance computing (HPC) center. This shows that prompt processing of raw SN data is possible and, in fact, trivial once the data have been reduced to reject radiological backgrounds, paving the way to a high-quality SN pointing trigger that is based on fully reconstructed data instead of trigger primitives (TPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

The Core-collapse Supernova Sensitivity Machine (Final Technical Report)

Core-collapse supernovae are vital phenomena for understanding the extreme physics of stellar evolution, nuclear interactions, and the origins of elements in the universe. This project developed high-resolution 3D simulations and innovative 1D turbulence models to study the explosion mechanisms, yielding critical insights into the role of turbulence, magnetohydrodynamics, and neutrino physics. The outcomes include enhanced sensitivity analyses connecting nuclear physics inputs to observable supernovae characteristics, tools for the broader research community, and substantial contributions to the training of future scientists.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric Classification of Early-time Supernova Light Curves with SCONE

Abstract In this work, we present classification results on early supernova light curves from SCONE, a photometric classifier that uses convolutional neural networks to categorize supernovae (SNe) by type using light-curve data. SCONE is able to identify SN types from light curves at any stage, from the night of initial alert to the end of their lifetimes. Simulated LSST SNe light curves were truncated at 0, 5, 15, 25, and 50 days after the trigger date and used to train Gaussian processes in wavelength and time space to produce wavelength–time heatmaps. SCONE uses these heatmaps to perform six-way classification between SN types Ia, II, Ibc, Ia-91bg, Iax, and SLSN-I. SCONE is able to perform classification with or without redshift, but we show that incorporating redshift information improves performance at each epoch. SCONE achieved 75% overall accuracy at the date of trigger (60% without redshift), and 89% accuracy 50 days after trigger (82% without redshift). SCONE was also tested on bright subsets of SNe ( r < 20 mag) and produced 91% accuracy at the date of trigger (83% without redshift) and 95% five days after trigger (94.7% without redshift). SCONE is the first application of convolutional neural networks to the early-time photometric transient classification problem. All of the data processing and model code developed for this paper can be found in the SCONE software package 1 1 github.com/helenqu/scone located at github.com/helenqu/scone (Qu 2021).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Nucleosynthetic Yields of Core-collapse Supernovae: Prospects for the Next Generation of Gamma-Ray Astronomy

Though the neutrino-driven convection model for the core-collapse explosion mechanism has received strong support in recent years, there are still many uncertainties in the explosion parameters—such as explosion energy, remnant mass, and end-of-life stellar abundances as initial conditions. Using a broad set of spherically symmetric core-collapse simulations we examine the effects of these key parameters on explosive nucleosynthesis and final explosion yields. The post-bounce temperature and density evolution of zero-age main-sequence 15, 20, and 25 solar mass progenitors are post-processed through the Nucleosynthesis Grid nuclear network to obtain detailed explosive yields. In particular, this study focuses on radio isotopes that are of particular interest to the next generation of gamma-ray astronomical observations: 43 K, 47 Ca, 44 Sc, 47 Sc, 48 V, 48 Cr, 51 Cr, 52 Mn, 59 Fe, 56 Co, 57 Co, and 57 Ni. Furthermore, these nuclides may be key in advancing our understanding of the inner workings of core-collapse supernovae by probing the parameters of the explosion engine. We find that the isotopes that are strong indicators of explosion energy are 43 K, 47 Ca, 44 Sc, 47 Sc, and 59 Fe, those that are dependent on the progenitor structure are 48 V, 51 Cr, and 57 Co, and those that probe neither are 48 Cr, 52 Mn, 57 Ni, and 56 Co. We discuss the prospects of observing these radionuclides in supernova remnants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Twins Embedding of Type Ia Supernovae. I. The Diversity of Spectra at Maximum Light

In this work, we study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin"SNe Ia. We call this parameterization the "Twins Embedding."Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios, or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ~0.02 mag between 6600 and 7200 Å. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar"SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results can be applied to the standardization of SNe Ia for cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Dependence of the Type Ia Supernova Host Bias on Observation or Fitting Technique

More luminous Type Ia supernovae prefer less massive hosts and regions of higher star formation. This correlation is inverted during width–color–luminosity light-curve standardization resulting in step-like biases of distance measurements with respect to host properties. Using the PMAS/PPak Integral-field Supernovahosts COmpilation (PISCO) supernova host sample and Sloan Digital Sky Survey, Galaxy Evolution Explorer, and Two Micron All Sky Survey photometry, we compare host stellar mass and specific star-formation rate (sSFR) from different observation methods, including local versus global, and fitting techniques to measure their impact on the host step biases. Mass-step measurements for all our mass samples are consistent within a 1σ significance from –0.03 ± 0.02 mag to –0.04 ± 0.02 mag. Including or excluding UV information had no effect on measured mass-step size or location. sSFR step sizes are more significant than mass-step measurements and varied from 0.05 ± 0.03 mag (Hα) and 0.06 ± 0.02 mag (UV) for a 51 host sample. The sSFR step location is influenced by the mass sample used to normalize star formation and by sSFR tracer choice. The step size is reduced to 0.04 ± 0.03 mag when using all available 73 hosts with Hα measurements. This 73 PISCO host subsample overall lacked a clear step signal, but here we are searching for whether different choices of mass or sSFR estimation can create a step signal. We find no evidence that different observation or fitting techniques choices can create a distance measurement step in either mass or sSFR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Impact of Resolution on Double-detonation Models for Type Ia Supernovae

Abstract Thermonuclear supernovae are the result of the violent unbinding of a white dwarf (WD), but the precise nature of the explosion mechanism(s) is a matter of active debate. To this end, several specific scenarios have been proposed to explain the observable traits of Type Ia supernovae. A promising pathway is the double-detonation scenario, where a WD accretes a shell of helium-rich material from a companion and a detonation in the resulting helium shell is the primary cause of the explosion. Through a set of two-dimensional grid-based simulations of this scenario we clearly distinguish three phases of evolution: external helium-rich detonation, core compressive heating, and a final core carbon burn. Though final disruption of the whole system is achieved at all resolutions, only models with minimum resolutions of 4 km and better exhibit all three phases. Particularly, core compression detonation is only observed for higher resolutions, producing qualitatively different nucleosynthetic outcomes. We identify the effect of finer spatial resolution on the mixing of hot silicon at the interface between the detonating helium layer and the underlying C/O WD as a primary driver of these dynamic differences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Parameterized Neutrino Emission Model to Study Mass Ejection in Failed Core-collapse Supernovae

Some massive stars end their lives as failed core-collapse supernovae (CCSNe) and become black holes (BHs). Although in this class of phenomena the stalled supernova (SN) shock is not revived, the outer stellar envelope can still be partially ejected. This occurs because the hydrodynamic equilibrium of the star is disrupted by the gravitational mass loss of the protoneutron star (PNS) due to neutrino emission. We develop a simple parameterized model that emulates PNS evolution and its neutrino emission and use it to simulate failed CCSNe in spherical symmetry for a wide range of progenitor stars. Our model allows us to study mass ejection of failed CCSNe where the PNS collapses into a BH within ~100 ms and up to ~10 6 s. We perform failed CCSNe simulations for 262 different pre-SN progenitors and determine how the energy and mass of the ejecta depend on progenitor properties and the equation of state (EOS) of dense matter. In the case of a future failed CCSN observation, the trends obtained in our simulations can be used to place constraints on the pre-SN progenitor characteristics, the EOS, and on PNS properties at BH formation time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning

Abstract Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the scientific return of these observations in the absence of spectroscopic information, we must accurately extract key parameters, such as SN redshifts, with photometric information alone. We present Photo- z SNthesis, a convolutional neural network-based method for predicting full redshift probability distributions from multi-band supernova lightcurves, tested on both simulated Sloan Digital Sky Survey (SDSS) and Vera C. Rubin Legacy Survey of Space and Time data as well as observed SDSS SNe. We show major improvements over predictions from existing methods on both simulations and real observations as well as minimal redshift-dependent bias, which is a challenge due to selection effects, e.g., Malmquist bias. Specifically, we show a 61× improvement in prediction bias 〈Δ z 〉 on PLAsTiCC simulations and 5× improvement on real SDSS data compared to results from a widely used photometric redshift estimator, LCFIT+Z. The PDFs produced by this method are well constrained and will maximize the cosmological constraining power of photometric SNe Ia samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Physics-driven Explosions of Stripped High-mass Stars: Synthetic Light Curves and Spectra of Stripped-envelope Supernovae with Broad Light Curves

Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf–Rayet stars with ejecta masses ranging from 4 to 11 M ⊙ , which were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor of up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range. Spectroscopically, the He I 1.083 μm line remains prominent even in models with as little as 0.02 M ⊙ of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as the 56 Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Production of Heavy α -Elements and 44 Ti in Cas A: Comparison to Abundances from 1D Core-collapse Supernova Models and Evidence for Carbon–Oxygen Shell Mergers

The merger between the carbon (C) and oxygen (O) shells hours to days before the collapse of a massive star significantly changes its nucleosynthesis, which is reflected in the elemental ratios observed in supernova remnants (SNRs). We present a nucleosynthesis study of 44 Ti production in core-collapse supernovae (CCSNe), highlighting large silicon (Si), sulfur (S), calcium (Ca), and, most importantly, argon (Ar) to neon (Ne) ratios as diagnostics for carbon–oxygen (C–O) shell mergers. We compare yields from eight different sets of CCSNe models to observations of Cassiopeia A (Cas A), and show that C–O shell mergers are consistently the models that best match X-ray and infrared observations. These models produce high Ar/Ne ratios (≳0.1), due to 20 Ne depletion and production of 36 Ar and 38 Ar, while lower ratios are obtained from nonmerger cases. Based on the Ar/Ne diagnostic, we compare the range of expected 44 Ti produced by C–O shell mergers, which is up to ∼20%–30% of the overall 44 Ti, but expected to be located outside the reverse shock. Based on the sets of models considered, the photon flux expected from the 44 Ti synthesized in the C–O shell merger in Cas A is below the NuSTAR and COSI detection limits, compatible with current limits locating most of the 44 Ti interior to the reverse shock, but might be detectable from proposed missions like ASCENT. Finally, for the SNR of 1987A, a dominant C–O merger origin of the observed 44 Ti is unlikely based on the observed redshift in its 44 Ti line.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Gamma-Ray Bursts and Their Links with Supernovae and Cosmology

Gamma-ray bursts are the most luminous explosions in the Universe, whose origin and mechanism are the focus of intense interest. They appear connected to supernova remnants from massive stars or the merger of their remnants, and their brightness makes them temporarily detectable out to the largest distances yet explored in the universe. After pioneering breakthroughs from space and ground experiments, their study is entering a new phase with observations from the recently launched Fermi satellite, as well as the prospect of detections or limits from large neutrino and gravitational wave detectors. The interplay between such observations and theoretical models of gamma-ray bursts is reviewed, as well as their connections to supernovae and cosmology.

supernovae↗