
3
butions to the HE astrophysical neutrino fluxes observed
by IceCube. We further discuss the implications of cjSNe
as the origin of HE neutrinos. We then comment on the
difference between our results and those in Ref. [51]. In
Sec. VI, we conclude our findings with a future roadmap.
II. DATA AND MODELS
A. Ten years of IceCube neutrino data
The IceCube Neutrino Observatory detects neutrinos
through the Cherenkov photons emitted by relativis-
tic charged particles produced from neutrino interac-
tions within (starting events) and outside (throughgo-
ing events) the detector [54,55]. The Cherenkov pho-
tons trigger the nearby digital optical modules and can
form two kinds of basic event topologies: elongated
tracks formed by muons, and showers, which look like
a round and big blob formed by electrons (electromag-
netic shower) or hadrons (hadronic shower). The track
events, which are dominated by throughgoing tracks,
have a much better angular resolution (as good as <1◦),
though worse energy resolution (∼200% at ∼100 TeV),
than the shower events (∼10◦–15◦and ∼15% above 100
TeV) [56]. Thus, track events are suited to searching for
point sources.
The data released by the IceCube Collaboration span
from April 2008 to July 2018 [52,53]. The same data have
been used in the ten-year time-integrated neutrino point-
source search by the IceCube collaboration [57], and in
searching for high-energy neutrino emission from radio-
bright AGN [58]. In total, there are 1,134,450 muon-track
events. The information for each track is provided, in-
cluding arrival time, angular direction, angular error, and
reconstructed energy. The arrival time is given with the
precision of 1×10−8days (8.6×10−4s). These ten years
of data are grouped into five samples corresponding to
different construction phases of IceCube and instrumen-
tal response functions, including 1) IC40, 2) IC59, 3)
IC79, 4) IC86-I, and 5) IC86-II to IC86-VII. The num-
bers in the names represent the numbers of strings in the
detector on which digital optical modules are deployed.
Distributions of these events in the sky can be found in
Figs. 1 and 2 in Ref. [58]. We use the events with dec-
lination (Dec) between −10◦and 90◦for the following
reasons: First, the events from Dec <−10◦(the south-
ern sky with respect to IceCube) have much higher back-
grounds from atmospheric muons [52]. Second, we find
that the given smearing matrices from simulations have
statistics that are too low to obtain good enough energy
PDFs for our analysis (Sec. III B).
We also process the 19 ×2 double-counted tracks in
the dataset found in Ref. [59] (listed in its Table III).
These events arise from an internal reconstruction er-
ror that identifies some single muons crossing the dust
layer as two separate muons arriving at the same time
and closely matching in direction [59]. This would affect
neutrino-source searches, especially transients, as finding
two associated events instead of one would be quite differ-
ent. Thus, we combine the 19 misreconstructed pairs into
19 single events by averaging the directions and summing
up the reconstructed energies. We provide the corrected
IceCube neutrino dataset at this URL .
B. Supernova sample
The supernova sample we use for our analysis is from
combining SNe Ib/c from the Open Supernova Cat-
alog [60], the Weizmann Interactive Supernova Data
Repository (WISeREP) [61], and the All-Sky Automated
Survey for Supernovae (ASAS-SN) [62–65]. These cata-
logs have collected more than 36,000, 20,000, and 1,300
supernovae, respectively, from a variety of astronomi-
cal surveys and existing archives. We further compare
our combined supernova sample with the publicly avail-
able catalog of bright supernovae [66,67] and incorporate
those that are missed in the above.
Sometimes a supernova is independently discovered by
different groups and thus has multiple aliases. This leads
to a small fraction of potentially duplicate sources in our
sample. To avoid double-counting, we first search for the
supernovae with an angular distance smaller than 0.1◦.
We then merge these supernovae if they are classified
as the same type and the differences in their maximal
brightness time and redshift are less than 30 days and
10%, respectively. The examples of supernova pairs sat-
isfying our criteria are {SN 2010O, SN 2010P}and {SN
2016coi, ASASSN-16fp}. As these potentially duplicate
sources have very similar observational properties, we re-
move one of them from our sample.
Finally, we keep the supernovae in our sample only if
they were observed at Dec ≥ −10◦and have a time win-
dow (defined in Sec. III B) overlapping with the uptime of
IceCube between April 2008 and July 2018 to match our
selected data (Sec. II A). In total, our final sample con-
sists of 386 SNe Ib/c, including 30, 36, 36, 36, and 248 for
IC40, IC59, IC79, IC86-I, and IC86-II–VII, respectively.
We provide the details of our supernova sample at this
URL .
C. cjSN models for neutrino emission
We assume choked jets to be nearly calorimetric
sources (except for the suppression factor) so that neu-
trinos are produced by all available energy ECR in cosmic
rays. The all-flavor neutrino spectrum from a single burst
of supernova is thus given by [69,70]
dNν(εν;ECR)
dενεν=0.05εp≈3
8fsup min[1, fpγ ]ECR
Rp(εp)ε−2
ν,
(1)
where the factor 3/8 is the fraction of energy taken away
by neutrinos from charged pions produced in the pγ inter-