The large-scale bias of cosmic voids

In current surreys, the survey volume is large enough that large number of voids are sampled and they can be regarded as a tracer of the large-scale structure. Because they sample the underdense regions of the dark matter density field, their clustering information can be complementary to that of the halo clustering. In this talk I will discuss the clustering of voids.  Precise measurement of the void bias parameters using the separate universe simulation technique is presented.  I will also  show that the bias parameter of voids also exhibits scale dependence similar to its halo counterpart in the local primordial non-Gaussianity (PNG) scenario. By including the scale-dependent bias information from voids, constraints on the PNG parameter can be tightened by a factor of two compared to the accessible information from halos alone, when the sampling density of tracers is sufficiently high.