Testing Gravitational Memory Generation with Compact Binary Mergers

Gravitational memory is an important prediction of General Relativity, which is intimately related to asymptotic symmetries at null infinity and the so-called soft graviton theorem. For a given transient astronomical event, the angular distribution of energy and angular momentum fluxes uniquely determine the displacement and spin memory effect in the sky. We investigate the possibility of using the binary black hole merger events detected by Advanced LIGO/Virgo to test the relation between the source’s energy emission and the gravitational memory measured on Earth, as predicted by General Relativity. We find that while it is difficult for Advanced LIGO/Virgo one-year detection of a third-generation detector network will easily rule out the hypothesis assuming isotropic memory distribution. In addition, we construct a phenomenological model for memory waveforms of binary neutron star mergers and use it to address the detectability of memory from these events in the third-generation detector era. We find that measuring gravitational memory from neutron star mergers is a possible way to distinguish between different neutron star equations of state.

Figure 1

Left panel: The distribution of the combined SNR of the gravitational memory for all events with expected memory SNR greater than 0.1, following a five-year observation period with a network of GW detectors containing Advanced LIGO (Livingston and Hanford) and Advanced Virgo at design sensitivities. As a comparison, we also plot the combined SNRs for the same set of events assuming third-generation detectors with a one-year observation period. The red dashed line highlights one commonly used detection threshold. Right panel: The inferred ${\mathrm{SNR}}_{\mathrm{eff}}^{50\%}$ for distinguishing the two hypotheses in Eq. (3) for the same set of detectors and with the same period of observation.

Figure 2

The $1\sigma$ uncertainty (bound by the blue and yellow line) of angular dependence $f(\iota )$ reconstructed from a set of simulated events, as indicated by the shaded region. The green line presents the underlying angular distribution in Eq. (2). The SNR and $\iota$ of simulated events are presented by the dots in the plot.