arXiv subjects

Maude Lariviere

Publications and source records attributed to Maude Lariviere.

3 recordsLinked to original sources

arXiv2026

Identifying observable MeV lines from the decays of weak and main $r$-process isotopes in mergers

We consider predictions for the MeV gamma-ray spectrum emitted by the $β$ decays of freshly synthesized isotopes from a neutron star merger at timescales of relevance for post-merger (days) and remnant (years) emission. We develop a search algorithm to identify observable spectral peaks and then determine if a specific isotope has a dominant emission line producing the spectral feature. We predict emission spectra using nucleosynthesis calculations which consider nuclear models with distinct masses, $β$-decays, and fission properties as well as variations on main ($A>130$) and weak ($A<130$) $r$-process astrophysical conditions. We tabulate all lines from decaying isotopes that our procedure identifies and provide the predicted range in time over which each line could be visible. We find that Rh-106 presents a unique opportunity to distinguish between main and weak $r$-process emission, as our calculated spectrum above $\sim 1$ MeV for an event dominated by the weak $r$ process is identical to the Rh-106 emission spectrum from $\sim$ 0.2 to $\sim$17 years. We further find emission from species such as Hf-181, Ta-182, Ta-184, and Re-188 offers the potential to be able to distinguish between nuclear models. We investigate whether the 2.6 MeV strong gamma-ray line from Tl-208 is predicted to be robustly observable across calculation variations on both timescale of days and years. We find Tl-208 to consistently shine through on the order of years, though it can face competition from Ga-72 and La-140 at early times ($\sim$ days). We additionally highlight numerous isotopes of interest for observation and nuclear experiment.

astro-ph.HE↗

arXiv2025

Classifying metal-poor stars with machine learning using nucleosynthesis calculations

We apply the capabilities of machine learning (ML) to discern patterns in order to classify metal-poor stars. To do so, we train an ML model on a bank of nucleosynthesis calculations derived from hydrodynamic simulations for events such as neutron star mergers where the rapid ($r$) neutron capture process can take place. Likewise we consider a bank of calculations from simulations of the slow ($s$) neutron capture process and also consider a few calculations for the intermediate ($i$) neutron capture process. We demonstrate that the ML does well overall in recognizing the $s$ process from the $r$ process, and after training on theoretical calculations ML stellar assignments match conventional labels 87% of the time. We highlight that this method then points to stars that could benefit from additional observational measurements. We also demonstrate that the ML assigns some of the presently considered $i$-process stars to instead be of $r$ or $s$ in origin, but likewise, finds stars currently labeled as $s$ to be potentially more aligned with $i$ enrichment. This first application of ML to classify metal-poor star enrichment using theoretical nucleosynthesis calculations thus reveals the promise, and some challenges, associated with this new data-driven path forward.

nucl-th↗

arXiv2023

Thallium-208: a beacon of in situ neutron capture nucleosynthesis

We demonstrate that the well-known 2.6 MeV gamma-ray emission line from thallium-208 could serve as a real-time indicator of astrophysical heavy element production, with both rapid (r) and intermediate (i) neutron capture processes capable of its synthesis. We consider the r process in a Galactic neutron star merger and show Tl-208 to be detectable from ~12 hours to ~10 days, and again ~1-20 years post-event. Detection of Tl-208 represents the only identified prospect for a direct signal of lead production (implying gold synthesis), arguing for the importance of future MeV telescope missions which aim to detect Galactic events but may also be able to reach some nearby galaxies in the Local Group.

nucl-th↗