Constraining Primordial Power Asymmetry from Galaxy Clustering and Peculiar Velocity Information
Keita Minato, Atsushi Taruya, Teppei Okumura, Maresuke Shiraishi
Abstract
Primordial power asymmetry would probe departures from statistical isotropy, offering a clue to the physics of the primordial Universe. We investigate how such asymmetries can be tested with galaxy surveys and quantify how peculiar-velocity information can improve these tests. We develop a unified bipolar spherical harmonic (BipoSH) analysis of the auto- and cross-power spectra of galaxy density and line-of-sight peculiar velocity, and perform Fisher forecasts combining a Euclid-like spectroscopic galaxy survey with peculiar velocities reconstructed from Simons Observatory-like CMB maps through the kinetic Sunyaev-Zel'dovich effect. For dipolar asymmetry, we consider both scale-independent and scale-dependent modulations proportional to k-0.5. Galaxy clustering provides most of the constraining power in both cases, while peculiar velocities add only modest information. For quadrupolar asymmetry, we account for the recently identified anisotropic galaxy-bias response and marginalize over its amplitude. We find that galaxy clustering alone suffers from a degeneracy between the primordial quadrupolar modulation and anisotropic galaxy bias. This degeneracy can be substantially broken by adding peculiar-velocity information: the density-velocity cross-spectrum provides complementary information to the galaxy auto-spectrum, while the velocity auto-spectrum constrains the primordial modulation independently of anisotropic galaxy bias. The velocity information becomes increasingly effective for more negative scale dependence, yielding constraints tighter than those from BOSS for scale dependences proportional to k-1 and k-2. Our results demonstrate that peculiar-velocity information provides a complementary avenue for testing primordial power asymmetry with large-scale structure, particularly for quadrupolar asymmetry in the presence of anisotropic galaxy bias.
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