SW1D: A Python package for seismic surface wave solutions in 1-D elastic media
Abstract
We present SW1D, a Python version of a legacy code for the forward computation of Rayleigh and Love wave dispersion curves as well as synthetic seismograms, in elastic, isotropic, laterally homogeneous media. This code solves the surface wave eigenvalue problem for 1-D media using a propagator-matrix technique and subsequently obtains surface wave excitations, in the frequency domain, for a point source described by its moment tensor. SW1D is validated through rigorous theoretical analyses and benchmarked against a well-established seismological software package. Ultimately, we demonstrate its place within an ecosystem of Python-based seismological tools designed for niche applications such as modelling surface wave propagation across lateral discontinuities, or forward modelling of ambient noise cross-correlations with arbitrary spatial distributions of ambient seismic sources.
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BibTeX
@misc{kolhe2026sw1d,
title = {{SW1D: A Python package for seismic surface wave solutions in 1-D elastic media}},
author = {Piyush Kolhe and Arjun Datta and Shijil Umer and Bivas Das},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.02194},
eprint = {2610.02194},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.02194},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - SW1D: A Python package for seismic surface wave solutions in 1-D elastic media
AU - Piyush Kolhe
AU - Arjun Datta
AU - Shijil Umer
AU - Bivas Das
PY - 2026
DA - 2026/10/01
PB - arXiv
DO - 10.48550/arxiv.2610.02194
UR - https://arxiv.org/abs/2610.02194
AB - We present SW1D, a Python version of a legacy code for the forward computation of Rayleigh and Love wave dispersion curves as well as synthetic seismograms, in elastic, isotropic, laterally homogeneous media. This code solves the surface wave eigenvalue problem for 1-D media using a propagator-matrix technique and subsequently obtains surface wave excitations, in the frequency domain, for a point source described by its moment tensor. SW1D is validated through rigorous theoretical analyses and benchmarked against a well-established seismological software package. Ultimately, we demonstrate its place within an ecosystem of Python-based seismological tools designed for niche applications such as modelling surface wave propagation across lateral discontinuities, or forward modelling of ambient noise cross-correlations with arbitrary spatial distributions of ambient seismic sources.
ER -