"Refsdal" meets Popper: comparing predictions of the re-appearance of the multiply imaged supernova behind MACSJ1149.5+2223

Abstract: Supernova "Refsdal," multiply imaged by cluster MACSJ1149.5+2223, represents a rare opportunity to make a true blind test of model predictions in extragalactic astronomy, on a time scale that is short compared to a human lifetime. In order to take advantage of this event, we produced seven gravitational lens models with five independent methods, based on Hubble Space Telescope (HST) Hubble Frontier Field images, along with extensive spectroscopic follow-up observations by HST, the Very Large and the Keck Telescopes. We compare the model predictions and show that they agree reasonably well with the measured time delays and magnification ratios between the known images, even though these quantities were not used as input. This agreement is encouraging, considering that the models only provide statistical uncertainties, and do not include additional sources of uncertainties such as structure along the line of sight, cosmology, and the mass sheet degeneracy. We then present the model predictions for the other appearances of SN "Refsdal." A future image will reach its peak in the first half of 2016, while another image appeared between 1994 and 2004. The past image would have been too faint to be detected in existing archival images. The future image should be approximately one third as bright as the brightest known image (i.e., H_AB~25.7 mag at peak and H_AB~26.7 mag six months before peak), and thus detectable in single-orbit HST images. We will find out soon whether our predictions are correct.

• The paper compares seven gravitational lens models to predict the reappearance time and location of the multiply imaged supernova "Refsdal" behind the cluster MACSJ1149.5+2223.
• Distinct models using parameterized, free-form, and light-traces-mass methods are tested against observed time delays and magnification ratios of known supernova images.
• Results show model agreement on known image properties and predict a future appearance of SN Refsdal around the first half of 2016, offering a critical empirical test for the models.

An Expert Overview of "Refsdal" Meets Popper: Comparing Predictions of the Reappearance of the Multiply Imaged Supernova Behind MACSJ1149.5+2223

The paper authored by Treu et al. presents a detailed comparative analysis of seven gravitational lens models to predict the reappearance of supernova (SN) "Refsdal", a multiply imaged SN undergoing gravitational lensing by the galaxy cluster MACSJ1149.5+2223. This analysis represents a significant application of extragalactic astronomy, where model predictions are tested against observed astrophysical phenomena in relatively short timescales, thus offering a robust empirical assessment of lensing models under real-world conditions.

Key Contributions and Analysis

The focal point of the study is the "Refsdal" supernova, identified as a multiple image system resulting from its lensing by the foreground cluster MACSJ1149.5+2223, as first proposed by Refsdal in 1964. The paper applies five independent methods, creating seven distinct models to approximate the reappearance of the SN images based on data from the Hubble Space Telescope (HST), the Very Large, and the Keck Telescopes. Each model is benchmarked against observed time delays and magnification ratios of the supernova images, followed by predictions concerning other potential appearances of the supernova.

The results show a reasonable agreement among the models on the time delays and magnification ratios of the known SN images, capturing the predictions' focal points despite inherent statistical uncertainties. The models forecast a future appearance of the SN "Refsdal" with a time delay set at the first half of 2016, and another predicted image that might have appeared faint in between 1994 and 2004, undetectable in current archival images due to its faintness.

Methodological Approach

The research relies on an ensemble of approximately seven distinct gravitational lens models constructed using HST's high-quality imaging data combined with deep spectroscopic data. These models include:

1. Simply-Parameterized Models: Used by Grillo et al., Oguri et al., and Sharon et al., these models employ a mass distribution approximation with parameters closely tied to the physical components like galaxy members and cluster halos.
2. Free-Form Model: As demonstrated by Diego et al., this approach employs more flexible mass distribution representations, conceptualized through the use of basis components or grid-based techniques.
3. Light-Traces-Mass (LTM) Model: Used by Zitrin et al., this method assumes that the projected dark matter distribution directly correlates with the luminous matter distribution in the lensing cluster.

These models collectively work towards setting constraints and predicting outcomes using different sets of multiply imaged galaxies, guided by spectroscopic redshifts and intrinsic brightness distributions. The relative agreement among these diverse models is an indicator of their robustness in making verifiable predictions under complex astrophysical configurations.

Numerical Results and Implications

Numerical results underscore the rigorous test against observational data, providing empirical validation for the lens models. Notably, the predicted future occurrence of SN "Refsdal" will provide a pivotal test for these models. The study lays a procedural groundwork for improving our understanding of cosmic phenomena through gravitational lensing effects—essential for advancing methodologies in astronomical predictions, cosmological parameters assessment, and the general understanding of dark matter distribution.

Future Developments and Challenges

One of the most poignant aspects of this research is its implication for future gravitational lensing studies. The observed models’ agreement in terms of predictions denotes the models’ relevance in aiding future astronomical surveys that depend on precise lensing effects. However, the challenges include addressing limitations concerning systematic uncertainties such as the mass-sheet degeneracy, cosmic variance, line-of-sight mass structures, and the incomplete modeling of baryonic physics intertwined with dark matter distributions.

In sum, the research advances gravitational lensing models' computational strategies, offering deeper insights into simulating and explicating cosmological phenomena through precise modeling techniques—a significant milestone for predictive astronomy.