Cosmic voids are an important probe of large-scale structure that can constrain cosmological parameters and test cosmological models. We present a new paradigm for void studies: void detection in weak lensing convergence maps. This approach identifies objects that relate directly to our theoretical understanding of voids as underdensities in the total matter field and presents several advantages compared to the customary method of finding voids in the galaxy distribution. We exemplify this approach by identifying voids using the weak lensing peaks as tracers of the large-scale structure. We find self-similarity in the void abundance across a range of peak signal-to-noise selection thresholds. The voids obtained via this approach give a tangential shear signal up to ∼ 40 times larger than voids identified in the galaxy distribution.

Modifications to General Relativity (GR) often incorporate screening mechanisms in order to remain compatible with existing tests of gravity. The screening is less efficient in underdense regions, which suggests that cosmic voids can be a useful cosmological probe for constraining modified gravity models. In particular, weak lensing by voids has been proposed as a promising test of such theories. Usually, voids are identified from galaxy distributions, making them biased tracers of the underlying matter field. An alternative approach is to study voids identified in weak lensing maps -weak lensing voids -which have been shown to better correspond to true underdense regions. In this paper, we study the ability of weak lensing voids to detect the signatures of modified gravity. Focusing on the void abundance and weak lensing profiles, we find that both statistics are sensitive probes of gravity. These are quantified in terms of the signal-to-noise ratios (SNR) with which an LSST-like survey will be able to distinguish between different gravity models. We find that the tangential shear profiles of weak lensing voids are considerably better than galaxy voids at this, though voids have somewhat lower SNR than weak lensing peaks. The abundances of voids and peaks have respectively SNR = 40 and 50 for a popular class of modified gravity in an LSST-like survey.

We investigate the accuracy of weak lensing simulations by comparing the results of five independently developed lensing simulation codes run on the same input N -body simulation. Our comparison focuses on the lensing convergence maps produced by the codes, and in particular on the corresponding PDFs, power spectra and peak counts. We find that the convergence power spectra of the lensing codes agree to 2% out to scales ≈ 4000. For lensing peak counts, the agreement is better than 5% for peaks with signal-to-noise 6. We also discuss the systematic errors due to the Born approximation, line-of-sight discretization, particle noise and smoothing. The lensing codes tested deal in markedly different ways with these effects, but they nonetheless display a satisfactory level of agreement. Our results thus suggest that systematic errors due to the operation of existing lensing codes should be small. Moreover their impact on the convergence power spectra for a lensing simulation can be predicted given its numerical details, which may then serve as a validation test.

Cosmic voids are a key component of the large-scale structure that contain a plethora of cosmological information. Typically, voids are identified from the underlying galaxy distribution, which is a biased tracer of the total matter field. Previous works have shown that 2D voids identified in weak lensing maps – weak lensing voids – correspond better to true underdense regions along the line of sight. In this work, we study how the properties of weak lensing voids depend on the choice of void finder, by adapting several popular void finders. We present and discuss the differences between identifying voids directly in the convergence maps, and in the distribution of weak lensing peaks. Particular effort has been made to test how these results are affected by galaxy shape noise, which is a dominant source of noise in weak lensing observations. By studying the signal-to-noise ratios (SNR) for the tangential shear profile of each void finder, we find that voids identified directly in the convergence maps have the highest SNR but are also the ones most affected by galaxy shape noise. Troughs are least affected by noise, but also have the lowest SNR. The tunnel algorithm, which identifies voids in the distribution of weak lensing peaks, represents a good compromise between finding a large tangential shear SNR and mitigating the effect of galaxy shape noise.

We study the statistics of weak lensing convergence peaks, such as their abundance and twopoint correlation function (2PCF), for a wide range of cosmological parameters Ω m and σ 8 within the standard ΛCDM paradigm, focusing on intermediate-height peaks with signal-tonoise ratio (SNR) of 1.5 to 3.5. We find that the cosmology dependence of the peak abundance can be described by a one-parameter fitting formula that is accurate to within ∼ 3%. The peak 2PCFs are shown to feature a self-similar behaviour: if the peak separation is rescaled by the mean inter-peak distance, catalogues with different minimum peak SNR values have identical clustering, which suggests that the peak abundance and clustering are closely interconnected. A simple fitting model for the rescaled 2PCF is given, which together with the peak abundance model above can predict peak 2PCFs with an accuracy better than ∼ 5%. The abundance and 2PCFs for intermediate peaks have very different dependencies on Ω m and σ 8 , implying that their combination can be used to break the degeneracy between these two parameters.