A numerical framework for Newtonian-noise estimation at the Einstein Telescope: 2-D simulations beyond the plane-wave approximation

TL;DR

This paper introduces a numerical spectral-element framework for estimating Newtonian noise at the Einstein Telescope, surpassing traditional analytical models by incorporating complex geological heterogeneity and wave interactions for improved site-specific predictions.

Contribution

The work develops a 2-D spectral-element simulation framework for Newtonian-noise estimation, validated against analytical models, and demonstrates its potential for detailed 3-D site-specific seismic analysis.

Findings

Excellent agreement with analytical plane-wave predictions in homogeneous media.

Lower P-wave fraction suggests better prospects for noise mitigation.

Framework adaptable to 3-D models and complex local seismic data.

Abstract

The Einstein Telescope (ET) is a third-generation underground gravitational-wave observatory designed to extend the detection sensitivity down to a few Hertz. Newtonian noise is expected to limit the low-frequency sensitivity of ET, particularly in the 1.7-6 Hz band. Most existing estimates rely on analytical or semi-analytical models assuming homogeneous or layered media, neglecting geological heterogeneity and complex wave interactions. In this work, we present a numerical framework for Newtonian-noise estimation based on spectral-element simulations of a seismic wave field. As a proof of concept, we first benchmark the numerical results against analytical plane-wave predictions in a two-dimensional homogeneous medium with a single surface source, demonstrating excellent agreement for both bulk and cavern contributions. We then extend the model to an array of 30 stochastic surface sources to approximate stationary ambient seismic excitation. The P-wave fraction inferred from the simulated wave field is, in this simple homogeneous case, significantly lower than commonly assumed, indicating enhanced prospects for Newtonian-noise mitigation. The framework is readily applicable to three-dimensional simulations and to integration of detailed local seismic models and topography, offering strong potential for site-specific Newtonian-noise estimation.