The cosmic microwave background lensing imprint of cosmic voids detected in the WISE-Pan-STARRS luminous red galaxy catalog

Context. The cross-correlation of cosmic voids with the lensing convergence ( κ ) map of cosmic microwave background (CMB) fluctuations offers a powerful tool with which to refine our understanding of the dark sector in the consensus cosmological model. Aims. Our principal aim is to compare the lensing signature of our galaxy dataset with simulations based on the concordance model and to characterize the results with an A κ consistency parameter normalized to unity. In particular, our measurements contribute to the understanding of the “lensing-is-low” tension of the ΛCDM model. Methods. In this analysis, we selected luminous red galaxies (LRGs) from the WISE-Pan-STARRS dataset, enabling an extended cross-correlation measurement using a 14 200 deg 2 sky area, which offers a more precise measurement than previous studies. We created 2D and 3D void catalogs to cross-correlate their locations with the Planck CMB lensing map and studied their average imprint signal using a stacking methodology. Applying the same procedure, we also generated a mock galaxy catalog from the WebSky simulation to serve as a basis for comparison. Results. The 2D void analysis reveals a good agreement with the standard cosmological model, with A κ ≈ 1.06 ± 0.08 amplitude; that is, S / N = 13.3, showing a higher signal-to-noise than previous studies using voids detected in the Dark Energy Survey (DES) dataset. The 3D void analysis exhibited a lower signal-to-noise ratio and demonstrated worse agreement with our mock catalog than the 2D voids. These deviations might be attributed to limitations in the mock catalog, such as imperfections in the LRG selection, as well as a potential asymmetry between the northern and southern patches of the WISE-Pan-STARRS dataset in terms of data quality. Conclusions. Overall, we present a significant detection of a CMB lensing signal associated with cosmic voids, largely consistent with the concordance model. Future analyses using even larger datasets also hold great promise of further sharpening these results, given their complementary nature to large-scale structure analyses.