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Model-Independent Test for Gravity using Intensity Mapping and Galaxy Clustering
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abstract
We propose a novel method to measure the $E_G$ statistic from clustering alone. The $E_G$ statistic provides an elegant way of testing the consistency of General Relativity by comparing the geometry of the Universe, probed through gravitational lensing, with the motion of galaxies in that geometry. Current $E_G$ estimators combine galaxy clustering with gravitational lensing, measured either from cosmic shear or from CMB lensing. In this paper, we construct a novel estimator for $E_G$, using only clustering information obtained from two tracers of the large-scale structure: intensity mapping and galaxy clustering. In this estimator, both the velocity of galaxies and gravitational lensing are measured through their impact on clustering. We show that with this estimator, we can suppress the contaminations that affect other $E_G$ estimators and consequently test the validity of General Relativity robustly. We forecast that with the coming generation of surveys like HIRAX and Euclid, we will measure $E_G$ with a precision of up to 7% (3.9% for the more futuristic SKA2).
Forward citations
Cited by 2 Pith papers
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A novel test of gravity: Does spacetime geometry track matter density?
The new Ngrow statistic, built from galaxy clustering and lensing, finds no deviation from GR and forecasts stage-IV surveys to bound geometry-density growth mismatches at 2-4%.
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Forecasting the E_G measurements from the photometric and spectroscopic surveys of Chinese Space Station Survey Telescope (CSST)
CSST forecasts E_G to 3–9% over 0<z<1.2, with the modified-gravity parameter Σ0 constrained to ~5% if β errors follow an assumed external forecast.
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