Constraining domain wall dark matter with a network of superconducting gravimeters and LIGO

TL;DR

This paper explores how superconducting gravimeters and LIGO can detect domain wall dark matter by measuring anomalous accelerations and gravitational effects, setting new bounds on such models using archival data.

Contribution

It demonstrates the use of existing superconducting accelerometer data and gravitational wave detectors to constrain domain wall dark matter models with spatial gradients.

Findings

Superconducting accelerometers can detect composition-dependent accelerations caused by dark matter.

Archival data from IGETS sets new bounds on domain wall dark matter models.

LIGO can probe narrow parameter ranges of dark matter models with spatial gradients.

Abstract

There is strong astrophysical evidence that dark matter (DM) makes up some 27% of all mass in the universe. Yet, beyond gravitational interactions, little is known about its properties or how it may connect to the Standard Model. Multiple frameworks have been proposed, and precision measurements at low energy have proven useful to help restrict the parameter space for many of these models. One set of models predicts that DM is a scalar field that "clumps" into regions of high local density, rather than being uniformly distributed throughout the galaxy. If this DM field couples to the Standard Model, its interaction with matter can be thought of as changing the effective values of fundamental constants. One generic consequence of time variation of fundamental constants (or their spatial variation as the Earth passes through regions of varying density) is the presence of an anomalous, composition-dependent acceleration. Here we show how this anomalous acceleration can be measured using superconducting accelerometers, and demonstrate that >20 years of archival data from the International Geodynamics and Earth Tide Services (IGETS) network can be utilized to set new bounds on these models. Furthermore, we show how LIGO and other gravitational wave detectors can be used as exquisitely sensitive probes for narrow ranges of the parameter space. While limited to DM models that feature spatial gradients, these two techniques complement the networks of precision measurement devices already in use for direct detection and identification of dark matter.