Paper detail

One star, two stars, or both? Investigating metallicity-dependant models for Gamma-Ray Burst progenitors with the IllustrisTNG simulation

The rate of long-duration gamma ray bursts (GRBs) has been identified as a potential proxy for the star formation rate (SFR) across redshift, but the exact relationship depends on GRB progenitor models (single versus binary). The single-progenitor collapsar model accounts for the preference towards low-metallicity GRB progenitors, but is in apparent tension with some high-metallicity GRB host galaxy measurements. As a possible solution, we consider the scenario where high-metallicity GRB hosts harbour low metallicity regions in which GRB progenitors form. For this, we use the IllustrisTNG cosmological hydrodynamical simulation to investigate the internal metallicity distribution of GRB hosts, implementing in post-processing different GRB formation models. Predictions (GRB rate, host metallicities and stellar masses) are compared to the high-completeness GRB legacy surveys BAT6 and SHOALS and a sample of high-redshift GRB-DLA metallicities, allowing us to compute their relative likelihoods. When the internal metallicity distribution of galaxies is ignored, the best-fitting model requires a metallicity-independent channel, as previously proposed by Trenti, Perna & Jimenez. However, when the internal metallicity distribution is considered, a basic metallicity bias model with a cutoff at $Z_{max}=0.35Z_\odot$ is the best fitting one. Current data are insufficient to discriminate among more detailed metallicity bias models, such as weak metallicity dependence of massive binaries vs stronger metallicity bias of collapsars. An increased sample of objects, and direct measurements of host stellar masses at redshift $z>2$ would allow to further constrain the origin of long GRBs.

preprint2020arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.