Paper detail

On using the counting method to constrain the anisotropy of kilonova radiation

A large number of binary neutron star (BNS) mergers are expected to be detected by gravitational wave (GW) detectors and the electromagnetic (EM) counterparts (e.g., kilonovae) of a fraction of these mergers may be detected in multi-bands by large area survey telescopes. For a given number of BNS mergers detected by their GW signals, the expected numbers of their EM counterparts that can be detected by a survey with given selection criteria depend on the kilonova properties, including the anisotropy. In this paper, we investigate whether the anisotropy of kilonova radiation and the kilonova model can be constrained statistically by the counting method, i.e., using the numbers of BNS mergers detected via GW and multi-band EM signals. Adopting simple models for the BNS mergers, afterglows, and a simple two (blue and red)-component model for kilonovae, we generate mock samples for GW detected BNS mergers, their associated kilonovae and afterglows detected in multi-bands. By assuming some criteria for searching the EM counterparts, we simulate the observations of these EM counterparts and obtain the EM observed samples in different bands. With the numbers of BNS mergers detected by GW detectors and EM survey telescopes in different bands, we show that the anisotropy of kilonova radiation and the kilonova model can be well constrained by using the Bayesian analysis. Our results suggest that the anisotropy of kilonova radiation may be demographically and globally constrained by simply using the detection numbers of BNS mergers by GW detectors and EM survey telescopes in multi-bands.

preprint2024arXivOpen 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.