Optical Follow-Up Strategies for the Next Neutrino-Detected Galactic Core-Collapse Supernova

TL;DR

The paper addresses how to efficiently detect optical/NIR counterparts to Galactic CCSNe triggered by MeV neutrino bursts. It couples a realistic CCSN population model (three progenitors) with neutrino triangulation across detector networks to generate skymaps, which are then processed by GWEMOPT to plan follow-up with LSST-VRO and TAROT, including SBO considerations and Galactic extinction. Key findings show that HK-inclusive networks yield tighter localizations, TAROT can match LSST-VRO in success rates with far fewer pointings, and rapid, coordinated scheduling is crucial for capturing early emission, including the SBO when visible. The study demonstrates the practical feasibility and benefits of multi-messenger follow-up for nearby CCSNe, highlighting the complementary strengths of large, deep surveys and rapid, wide-field robotic telescopes in maximizing detection probability and scientific return.

Abstract

Core-collapse supernovae (CCSNe) are expected to produce intense bursts of neutrinos preceding the emergence of their electromagnetic (EM) counterparts. The prompt detection of such neutrino signals offers a unique opportunity to trigger early follow-up observations in the EM domain. We aim to assess the feasibility and efficiency of an optical-NIR follow-up strategy for CCSNe discovered via neutrino bursts, by modelling the spatial distribution of events and simulating realistic observational campaigns taking into account the size of the localization error box generated by triangulating the neutrino burst. We modelled the Galactic distribution of CCSNe, including the effects of interstellar extinction, and considered three main progenitor types: Wolf-Rayet stars, red and blue supergiants. We included the shock breakout in the EM signatures that could be detected following the neutrino burst. A population of CCSNe was generated and detected by different networks of neutrino observatories, including IceCube, KM3NeT, Super-Kamiokande, Hyper-Kamiokande, and JUNO. The resulting skymaps were used as input for GWEMOPT to produce optimized follow-up plans with two optical facilities: LSST and the TAROT robotic telescopes. Both LSST and TAROT exhibit comparable detection efficiencies for the simulated CCSN population. However, the TAROT network achieves similar success rates while requiring fewer pointings to cover the CCSN skymap. Our simulations demonstrate that neutrino follow-up campaigns can effectively CCSN optical counterparts using both large and small facilities. Depending on the neutrino network, the median number of pointings for the two tested optical facilities is of the order of 20 to 100 to find the EM emission. The number of images is larger for LSST than for TAROT by a factor of 2 to 4.

Figures (10)

• Figure 1: Absolute magnitude distribution of 103 observed type IIp SNe and 222 type Ib/c observed SNe. The data are taken from li2011nearby and perley2020zwicky for the SN IIp and only the latter for the SN Ib/c. The red curve shows the Normal distribution with mean $\mu = -16.70$ mag and standard deviation $\sigma = 1.17$ mag used to generate the SN IIp population. The black curve shows the Normal distribution with mean $\mu = -17.46$ mag and standard deviation $\sigma = 0.92$ mag used to generate the SN Ib/c population.
• Figure 2: Distributions of the E(B-V) colour excess for a sample of 50000 positions in the MW using the BAYESTAR dust map that were generated following the same distribution as in Eq. \ref{['eq:space_distr']}. The left panel shows the colour excess results without the transformation presented in Eq. \ref{['eq:ebv_transf']}, and the right panel shows the results that include them. Both plots show the 500 injected SNe, with the RSG progenitor represented by black stars, the BSG by orange crosses, and the WR ones by red crosses.
• Figure 3: Temporal diagram with the events following the neutrino burst that triggers the optical observations. The duration of the shock breakout propagation is visible as the arrows in blue and the shock breakout duration is presented as the green arrow. However, the values presented in the figure are arbitrary and chosen to make the plot clearer. The orange lightcurve is based on the template presented in 1999ApJ...521...30G for the Type IIp events. The blue curve corresponds to the Type Ib/c CCSN and is based on the template presented in 2005ApJ...624..880L.
• Figure 4: Percentile-Percentile plot for the four neutrino network configurations. The left and right panels show the results, respectively, before and after the randomization of the SNe position. For both panels, the dark blue curve corresponds the network IC-ARCA-HK-JUNO, the blue curve corresponds the IC-ARCA-HK network, the green curve corresponds the IC-ARCA-SK network, and the yellow curve corresponds to the IC-ARCA-JUNO network. The grey area corresponds to the 1, 2, and 3 $\sigma$ deviations from the diagonal. On the left panel, the curves are largely deviating from the diagonal by more than 10$\sigma$. On the right panel, all the curves are diagonal and compatible with a uniform search probability distribution. The deviations for each network configuration are indicated in the legend of the plot.
• Figure 5: Skymaps obtained with lightcurve-matching for injection n$^{\circ}$69 for the different neutrinos network configurations described in Sec. \ref{['sec:network']}. The black contour corresponds to the IC-ARCA-HK-JUNO configuration, the blue contour corresponds to the IC-ARCA-SK configuration, the orange contour corresponds to the IC-ARCA-JUNO configuration and the red contour corresponds to the IC-ARCA-HK configuration. The plot is made in the ICRS frame. The position of the CCSN injection is shown as a star marker.