5 research outputs found
Nucleosynthesis in outflows of compact objects and detection prospects of associated kilonovae
We perform a comparative analysis of nucleosynthesis yields from binary
neutron star (BNS) mergers, black hole-neutron star (BHNS) mergers, and
core-collapse supernovae (CCSNe) with the goal of determining which are the
most dominant sources of r-process enrichment observed in stars. We find that
BNS and BHNS binaries may eject similar mass distributions of robust r-process
nuclei post merger (up to 3rd peak and actinides, ), after
accounting for the volumetric event rates. Magnetorotational (MR) CCSNe likely
undergo a weak r-process (up to ) and contribute to the production of
light element primary process (LEPP) nuclei, whereas typical thermal,
neutrino-driven CCSNe only synthesize up to 1st r-process peak nuclei
(). We also find that the upper limit to the rate of MR CCSNe is
the rate of typical thermal CCSNe; if the rate was higher, then
weak r-process nuclei would be overproduced. Although the largest uncertainty
is from the volumetric event rate, the prospects are encouraging for confirming
these rates in the next few years with upcoming surveys. Using a simple model
to estimate the resulting kilonova light curve from mergers and our set of
fiducial merger parameters, we predict that BNS and BHNS events
will be detectable per year by the Vera C. Rubin Observatory (LSST), with prior
gravitational wave (GW) triggers.Comment: 14 pages, 5+3 figures, 1 table. Comments welcom
Diffuse neutrino background from past core-collapse supernovae
Core-collapse supernovae are among the most powerful explosions in the
universe, emitting thermal neutrinos that carry away the majority of the
gravitational binding energy released. These neutrinos create a diffuse
supernova neutrino background (DSNB), one of the largest energy budgets among
all radiation backgrounds. Detecting the DSNB is a crucial goal of modern
high-energy astrophysics and particle physics, providing valuable insights in
both core-collapse modeling, neutrino physics, and cosmic supernova rate
history. In this review, we discuss the key ingredients of DSNB calculation and
what we can learn from future detections, including black-hole formation and
non-standard neutrino interactions. Additionally, we provide an overview of the
latest updates in neutrino experiments, which could lead to the detection of
the DSNB in the next decade. With the promise of this breakthrough discovery on
the horizon, the study of DSNB holds enormous potential for advancing our
understanding of the Universe.Comment: 21 pages, 8 figures. Invited review article submitted to Proceedings
of the Japan Academy, Series B. Figures are made using the numerical codes
that accompany this paper; see
https://github.com/shinichiroando/PyDSNB/tree/mai
Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations
The sensitivity of current and future neutrino detectors like
Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to
allow for the detection of the diffuse supernova neutrino background (DSNB).
However, the DSNB model ingredients like the core-collapse supernova (CCSN)
rate, neutrino emission spectra, and the fraction of failed supernovae are not
precisely known. We quantify the uncertainty on each of these ingredients by
(i) compiling a large database of recent star formation rate density
measurements, (ii) combining neutrino emission from long-term axisymmetric
CCSNe simulations and strategies for estimating the emission from the
protoneutron star cooling phase, and (iii) assuming different models of failed
supernovae. Finally, we calculate the fluxes and event rates at multiple
experiments and perform a simplified statistical estimate of the time required
to significantly detect the DSNB at SK with the gadolinium upgrade and JUNO.
Our fiducial model predicts a flux of at SK employing Gd-tagging, or
events per year, where the errors represent our uncertainty from star formation
rate density measurements, uncertainty in neutrino emission, and uncertainty in
the failed-supernova scenario. In this fiducial calculation, we could see a
detection by with SK-Gd and a detection by
with a joint SK-Gd/JUNO analysis, but background reduction remains
crucial.Comment: 19 pages, 9 figures, 3+2 tables. Comments welcom
Impact of late-time neutrino emission on the Diffuse Supernova Neutrino Background
In the absence of high-statistics supernova neutrino measurements, estimates
of the diffuse supernova neutrino background (DSNB) hinge on the precision of
simulations of core-collapse supernovae (CCSNe). Understanding the cooling
phase of protoneutron star (PNS) evolution ( after core
bounce) is crucial, since approximately 50% of the energy liberated by
neutrinos is emitted during the cooling phase. We model the cooling phase with
a hybrid method, by combining the neutrino emission predicted by 3D
hydrodynamic simulations with several cooling phase estimates, including a
novel two-parameter correlation depending on the final baryonic PNS mass and
the time of shock revival. We find that the predicted DSNB event rate at
Super-Kamiokande can vary by a factor of depending on the cooling
phase treatment. We also find that except for one cooling estimate, the range
in predicted DSNB events is largely driven by the uncertainty in the neutrino
mean energy. With a good understanding of the late time neutrino emission, more
precise DSNB estimates can be made for the next generation of DSNB searches.Comment: 13 pages, 6+4 figures, 5 tables. Comments welcom