Improved lanthanide constraints for the kilonova AT 2017gfo

TL;DR

The paper tackles the challenge of constraining heavy-element production in kilonova AT 2017gfo by exploiting newly calibrated lanthanide line data to improve spectral identifications. Using the 3.4-day X-shooter spectrum and the radiative-transfer code TARDIS, it reveals that previous lanthanide contributions were severely underestimated owing to incomplete line lists, and finds a best-fit lanthanide mass fraction of $X_{\textsc{ln}} \approx 2.5 \times 10^{-3}$, about $20\times$ lower than earlier estimates. This outcome highlights the critical role of complete, calibrated atomic data for interpreting kilonova spectra and placing robust constraints on r-process yields. The work implies sub-Solar lanthanide abundances in the line-forming region for AT 2017gfo and stresses the need for broader atomic datasets to reliably map observed features to specific heavy elements.

Abstract

Spectroscopic observations of the kilonova AT 2017gfo provide a unique opportunity to identify signatures from individual heavy elements freshly synthesised via the {\it r}-process, the nucleosynthetic channel responsible for producing $\sim$half of all trans-iron-group elements. Limitations in the available atomic data have historically hampered comprehensive line identification studies; however, renewed interest has led to the generation of improved (more complete and accurately calibrated) line lists for {\it r}-process species. Here we demonstrate the utility of such data, by exploiting newly generated line lists for the lanthanides to model the photospheric-phase 3.4d X-shooter spectrum of AT 2017gfo with the radiative transfer tool \textsc{tardis}. We find the data can only be reproduced by invoking a substantially diminished lanthanide mass fraction ($X_{\textsc{ln}}$) than that proposed by previous studies. Specifically, our model necessitates $X_{\textsc{ln}} \approx 2.5 \times 10^{-3}$, a value $20 \times$ lower than previously claimed. This substantial reduction in $X_{\textsc{ln}}$ is driven by our inclusion of much more complete lanthanide line information that enables better estimation of their total contribution to the observations. We encourage future modelling works to exploit all atomic data advances, and also encourage continued efforts to generate the necessary data for the remaining {\it r}-process species of interest.

Figures (4)

• Figure 1: Comparison of the best-fitting tardis model from PaperI (blue) with the observed 3.4 d X-shooter spectrum of AT 2017gfo (black). Regions of strong telluric absorption are shaded. We also show the resultant spectrum obtained by re-generating this best-fitting model with the updated tardis code and its corrected relativistic treatment (orange), to illustrate the impact this correction has on the synthetic spectrum. Finally, we present the same model, but with $T$ re-scaled, to approximately account for this correction ($T = 3200$ K, versus the original $T = 3400$ K; red). We find that this re-scaled model closely resembles both the best-fitting model presented by PaperI, and the observed data.
• Figure 2: Top: Updated best-fitting models compared with the 3.4 d X-shooter spectrum of AT 2017gfo (black). Regions of strong telluric absorption in the observations are shaded. The re-scaled $T = 3200$ K model that closely matches that of PaperI is again shown (red). The same model generated with our updated atomic data set is plotted for comparison (blue). Note how the entire SED has changed shape, due to the significantly increased lanthanide opacity. Bottom: Model decomposition plot to illustrate the strongest contributions to the new model SED. Contributions from specific species are colour-coded; absorption is represented by shaded regions below Flux = 0, while emission is represented by shaded regions above Flux = 0.
• Figure 3: Top: Comparison between our new best-fitting model (blue), our old best-fitting model (red), and the 3.4 d X-shooter spectrum of AT 2017gfo (black). Regions of strong telluric absorption are again shaded. This best-fitting model was obtained with a modified version of the $Y_e$$- 0.29$a composition profile. Bottom: Model decomposition plot for our new best-fitting model.
• Figure 4: Comparison between the Solar $r$-process distributions of Goriely1999 (black) and Prantzos2020 (blue), the $Y_e$$- 0.29$a composition profile of PaperI (orange), and our re-scaled composition profile invoked in this work (red). All distributions have been re-scaled such that they have identical $_{52}$Te relative mass fractions. Elements of interest have been labelled, and shaded regions highlight the lanthanide elements (pink) and elements with very incomplete atomic data (grey).