SciPost Submission Page
A multi-parameter expansion for the evolution of asymmetric binaries in astrophysical environments
by Sayak Datta and Andrea Maselli
Submission summary
| Authors (as registered SciPost users): | Sayak Datta |
| Submission information | |
|---|---|
| Preprint Link: | scipost_202507_00063v2 (pdf) |
| Date submitted: | Nov. 18, 2025, 10:07 a.m. |
| Submitted by: | Sayak Datta |
| Submitted to: | SciPost Physics |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
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| Approach: | Theoretical |
Abstract
Compact binaries with large mass asymmetries - such as Extreme and Intermediate Mass Ratio Inspirals - are unique probes of the astrophysical environments in which they evolve. Their long-lived and intricate dynamics allow for precise inference of source properties, provided waveform models are accurate enough to capture the full complexity of their orbital evolution. In this work, we develop a multi-parameter formalism, inspired by vacuum perturbation theory, to model asymmetric binaries embedded in general matter distributions with both radial and tangential pressures. In the regime of small deviations from the Schwarzschild metric, relevant to most astrophysical scenarios, the system admits a simplified description, where both metric and fluid perturbations can be cast into wave equations closely related to those of the vacuum case. This framework offers a practical approach to modelling the dynamics and the gravitational wave emission from binaries in realistic matter distributions, and can be modularly integrated with existing results for vacuum sources.
Author indications on fulfilling journal expectations
- Provide a novel and synergetic link between different research areas.
- Open a new pathway in an existing or a new research direction, with clear potential for multi-pronged follow-up work
- Detail a groundbreaking theoretical/experimental/computational discovery
- Present a breakthrough on a previously-identified and long-standing research stumbling block
Current status:
Reports on this Submission
Report #1 by Dongjun Li (Referee 1) on 2025-11-21 (Invited Report)
Report
Recommendation
Publish (surpasses expectations and criteria for this Journal; among top 10%)

Anonymous on 2025-11-18 [id 6047]
The comment author discloses that the following generative AI tools have been used in the preparation of this comment:
Chatgpt
We thank the Referees for their valuable comments and suggestions, which have greatly improved the quality of our paper. We believe we have addressed all the points raised in the reports and hope that it will be accepted for publication.