arXiv subjects

Christopher T. Davies

Publications and source records attributed to Christopher T. Davies.

At least 19 recordsLinked to original sources

arXiv2026

Impact of galaxy intrinsic alignments on non-Gaussian weak lensing statistics for modified gravity

Non-Gaussian weak lensing statistics improve the constraining power of cosmic shear data by harvesting information unavailable to two-point statistics, within and beyond the GR+$Λ$CDM scenario. Dark energy, total neutrino mass and deviations from GR have all been shown to be better measured with non-Gaussian lensing probes, in simplified conditions. Previous studies typically overlook the impact of secondary lensing signals, which can be large and therefore can significantly affect the conclusions. Here we investigate the impact on measurements of cosmological and modified gravity parameters in the presence of galaxy intrinsic alignments. We focus on the power spectra, lensing PDF, peaks and minima counts, void abundance and void profiles. These non-Gaussian statistics are measured from the MGLenS mock weak lensing maps, in which three cosmological parameters and one gravitational parameter are varied, either in the $f(R)$ or nDGP scenario, assuming Stage-IV lensing survey precision. These simulations are infused with the non-linear linear alignment model, allowing us to build emulators for each statistic with or without IA, and to study biases in full MCMC analyses. We show that in the absence of IA, lensing void profiles and abundance generally yield the highest Figure of Merit in the $S_8 - f_{R0}$ and $S_8 - H_0 r_{\rm c}$ planes, at times improving by an order of magnitude over two-point functions. When IA is unaccounted for, major parameter biases are observed in the cosmology sector, while the modified gravity sector is relatively unaffected. We find that these biases can generally be flagged from poor goodness-of-fit measurements, except for a few cases where IA can fully masquerade as a lower $Ω_{\rm m}$ and lower $S_8$ cosmology.

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arXiv2025

Fully non-linear simulations of galaxy intrinsic alignments for weak lensing with the MillenniumTNG lightcone

We present a complete forward model of a realistic weak lensing galaxy catalogue based on the 740 Mpc hydrodynamical MillenniumTNG (MTNG) simulation. Starting with a complete particle and cell lightcone covering one octant of the sky with redshift range 0 < $z$ < 1.5, we apply a group and subhalo finder to generate the corresponding galaxy catalogue for a fiducial observer. For all galaxies, we compute both their intrinsic and lensing-induced shear. The intrinsic component is derived from the luminosity-weighted inertia tensor of stellar particles, while the extrinsic (gravitational) shear is obtained through full-sky ray-tracing on the same lightcone. This allows us to directly predict the impact of intrinsic alignment (IA) of galaxies on the shear correlation function and popular convergence statistics in a fully non-linear forward model. We find that IA modifies the convergence power spectrum at all angular scales by up to 20%, it significantly impacts the PDF, altering its tails by 10-20%, and distorts peak and minimum counts up to 30%, depending on redshift and scale. We also evaluate the impact of the IA signal on the shear correlation function finding that, along with a redshift dependence, the signal strongly increases for higher galaxy stellar mass cuts applied to the catalogue. Notably, with the highest stellar mass cut we apply, the intrinsic shear autocorrelation can become comparable to the gravitational shear component on small angular scales. Our results highlight the importance of accurately modeling IA for precision weak lensing cosmology with upcoming Stage IV surveys.

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arXiv2025

Cosmological Inference with Cosmic Voids and Neural Network Emulators

Cosmic Voids are a promising probe of cosmology for spectroscopic galaxy surveys due to their unique response to cosmological parameters. Their combination with other probes promises to break parameter degeneracies. Due to simplifying assumptions, analytical models for void statistics are only representative of a subset of the full void population. We present a set of neural-based emulators for void summary statistics of watershed voids, which retain more information about the full void population than simplified analytical models. We build emulators for the void size function and void density profiles traced by the halo number density using the Quijote suite of simulations for a broad range of the $Λ\mathrm{CDM}$ parameter space. The emulators replace the computation of these statistics from computationally expensive cosmological simulations. We demonstrate the cosmological constraining power of voids using our emulators, which offer orders-of-magnitude acceleration in parameter estimation, capture more cosmological information compared to analytic models, and produce more realistic posteriors compared to Fisher forecasts. We find that the parameters $Ω_m$ and $σ_8$ in this Quijote setup can be recovered to $14.4\%$ and $8.4\%$ accuracy respectively using void density profiles; including the additional information in the void size function improves the accuracy on $σ_8$ to $6.8\%$. We demonstrate the robustness of our approach to two important variables in the underlying simulations, the resolution, and the inclusion of baryons. We find that our pipeline is robust to variations in resolution, and we show that the posteriors derived from the emulated void statistics are unaffected by the inclusion of baryons with the Magneticum hydrodynamic simulations. This opens up the possibility of a baryon-independent probe of the large-scale structure.

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arXiv2025

Ray-tracing vs. Born approximation in full-sky weak lensing simulations of the MillenniumTNG project

Weak gravitational lensing is a powerful tool for precision tests of cosmology. As the expected deflection angles are small, predictions based on non-linear N-body simulations are commonly computed with the Born approximation. Here we examine this assumption using ${\small DORIAN}$, a newly developed full-sky ray-tracing scheme applied to high-resolution mass-shell outputs of the two largest simulations in the MillenniumTNG suite, each with a 3000 Mpc box containing almost 1.1 trillion cold dark matter particles in addition to 16.7 billion particles representing massive neutrinos. We examine simple two-point statistics like the angular power spectrum of the convergence field, as well as statistics sensitive to higher order correlations such as peak and minimum statistics, void statistics, and Minkowski functionals of the convergence maps. Overall, we find only small differences between the Born approximation and a full ray-tracing treatment. While these are negligibly small at power-spectrum level, some higher order statistics show more sizable effects; ray-tracing is necessary to achieve percent level precision. At the resolution reached here, full-sky maps with 0.8 billion pixels and an angular resolution of 0.43 arcmin, we find that interpolation accuracy can introduce appreciable errors in ray-tracing results. We therefore implemented an interpolation method based on nonuniform fast Fourier transforms (NUFFT) along with more traditional methods. Bilinear interpolation introduces significant smoothing, while nearest grid point sampling agrees well with NUFFT, at least for our fiducial source redshift, $z_s=1.0$, and for the 1 arcmin smoothing we use for higher-order statistics.

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arXiv2024

The Gravitational Lensing Imprints of DES Y3 Superstructures on the CMB: A Matched Filtering Approach

$ $Low density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence $κ$. This effect provides insight into the distribution of matter within voids, and can also be used to study the growth of structure. We measure this lensing imprint by cross-correlating the Planck CMB lensing convergence map with voids identified in the Dark Energy Survey Year 3 data set, covering approximately 4,200 deg$^2$ of the sky. We use two distinct void-finding algorithms: a 2D void-finder which operates on the projected galaxy density field in thin redshift shells, and a new code, Voxel, which operates on the full 3D map of galaxy positions. We employ an optimal matched filtering method for cross-correlation, using the MICE N-body simulation both to establish the template for the matched filter and to calibrate detection significances. Using the DES Y3 photometric luminous red galaxy sample, we measure $A_κ$, the amplitude of the observed lensing signal relative to the simulation template, obtaining $A_κ= 1.03 \pm 0.22$ ($4.6σ$ significance) for Voxel and $A_κ= 1.02 \pm 0.17$ ($5.9σ$ significance) for 2D voids, both consistent with $Λ$CDM expectations. We additionally invert the 2D void-finding process to identify superclusters in the projected density field, for which we measure $A_κ= 0.87 \pm 0.15$ ($5.9σ$ significance). The leading source of noise in our measurements is Planck noise, implying that future data from the Atacama Cosmology Telescope (ACT), South Pole Telescope (SPT) and CMB-S4 will increase sensitivity and allow for more precise measurements.

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arXiv2024

Constraining modified gravity with weak lensing peaks

It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision.

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arXiv2024

The ACT-DR5 MCMF Galaxy Cluster Catalog

Galaxy clusters are useful cosmological probes and interesting astrophysical laboratories. With growing cluster samples, a deeper understanding of the sample characteristics and improved control of systematics becomes more crucial. In this analysis we create a new and larger ACT-DR5-based thermal Sunyaev-Zel'dovich Effect (tSZE) selected galaxy cluster catalog with improved control over sample purity and completeness. We employ the red sequence based cluster redshift and confirmation tool MCMF together with optical imaging data from the Legacy Survey DR-10 and infrared data from the WISE satellite to systematicallyidentify true clusters from a new cluster candidate detection run on the ACT-DR5 dataset. The resulting ACT-DR5 MCMF sample contains 6,237 clusters with a residual contamination of 10.7%. This is an increase of 51% compared to the previous ACT-DR5 cluster catalog, making this catalog the largest tSZE-selected cluster catalog to date. The z>1 subsample contains 703 clusters, three times more than in the previous ACT-DR5 catalog. Matching the ACT-DR5 MCMF cluster catalog with a deeper tSZE sample from SPTpol 500d allows us to confirm the completeness and purity of the new ACT-DR5 MCMF sample. Cross-matching to the two largest X-ray selected cluster samples, the all-sky RASS MCMF and the half-sky eRASS1, confirms the sample purity of the RASS MCMF sample and in the case of eRASS1 reveals that 43% of the matched clusters are designated in eRASS1 as X-ray point sources rather than clusters. Cross-correlating the ACT-DR5 MCMF cluster catalog with ACT-DR6 lensing maps results in a 16.4σdetection of CMB lensing around the clusters, corresponding to the strongest signal found so far for a galaxy cluster sample. Repeating the measurement for the z>1 cluster subsample yields a significance of 4.3σ, which is the strongest CMB lensing detection in a z>1 cluster sample to date.

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arXiv2024

The MillenniumTNG Project: The impact of baryons and massive neutrinos on high-resolution weak gravitational lensing convergence maps

We study weak gravitational lensing convergence maps produced from the MillenniumTNG (MTNG) simulations by direct projection of the mass distribution on the past backwards lightcone of a fiducial observer. We explore the lensing maps over a large dynamic range in simulation mass and angular resolution, allowing us to establish a clear assessment of numerical convergence. By comparing full physics hydrodynamical simulations with corresponding dark-matter-only runs we quantify the impact of baryonic physics on the most important weak lensing statistics. Likewise, we predict the impact of massive neutrinos reliably far into the non-linear regime. We also demonstrate that the "fixed & paired" variance suppression technique increases the statistical robustness of the simulation predictions on large scales not only for time slices but also for continuously output lightcone data. We find that both baryonic and neutrino effects substantially impact weak lensing shear measurements, with the latter dominating over the former on large angular scales. Thus, both effects must explicitly be included to obtain sufficiently accurate predictions for stage IV lensing surveys. Reassuringly, our results agree accurately with other simulation results where available, supporting the promise of simulation modelling for precision cosmology far into the non-linear regime.

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arXiv2024

Constraining $f(R)$ gravity using future galaxy cluster abundance and weak-lensing mass calibration datasets

We present forecasts for constraints on the Hu \& Sawicki $f(R)$ modified gravity model using realistic mock data representative of future cluster and weak lensing surveys. We create mock thermal Sunyaev-Zel'dovich effect selected cluster samples for SPT-3G and CMB-S4 and the corresponding weak gravitational lensing data from next-generation weak-lensing (ngWL) surveys like Euclid and Rubin. We employ a state-of-the-art Bayesian likelihood approach that includes all observational effects and systematic uncertainties to obtain constraints on the $f(R)$ gravity parameter $\log_{10}|f_{R0}|$. In this analysis we vary the cosmological parameters $[Ω_{\rm m}, Ω_νh^2, h^2, A_s, n_s, \log_{10}|f_{R0}|]$, which allows us to account for possible degeneracies between cosmological parameters and $f(R)$ modified gravity. The analysis accounts for $f(R)$ gravity via its effect on the halo mass function which is enhanced on cluster mass scales compared to the expectations within general relativity (GR). Assuming a fiducial GR model, the upcoming cluster dataset SPT-3G$\times$ngWL is expected to obtain an upper limit of $\log_{10}|f_{R0}| < -5.95$ at $95\,\%$ credibility, which significantly improves upon the current best bounds. The CMB-S4$\times$ngWL dataset is expected to improve this even further to $\log_{10}|f_{R0}| < -6.23$. Furthermore, $f(R)$ gravity models with $\log_{10}|f_{R0}| \geq -6$, which have larger numbers of clusters, would be distinguishable from GR with both datasets. We also report degeneracies between $\log_{10}|f_{R0}|$ and $Ω_{\mathrm{m}}$ as well as $σ_8$ for $\log_{10}|f_{R0}| > -6$ and $\log_{10}|f_{R0}| > -5$ respectively. Our forecasts indicate that future cluster abundance studies of $f(R)$ gravity will enable substantially improved constraints that are competitive with other cosmological probes.

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arXiv2023

An emulator-based halo model in modified gravity -- I. The halo concentration-mass relation and density profile

In this series of papers we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function, concentration-mass relation and halo-matter cross-correlation function. The emulators are trained on data extracted from the \textsc{FORGE} and \textsc{BRIDGE} suites of $N$-body simulations, respectively for two modified gravity (MG) theories: $f(R)$ gravity and the DGP model, varying three standard cosmological parameters $Ω_{\mathrm{m0}}, H_0, σ_8$, and one MG parameter, either $\bar{f}_{R0}$ or $r_{\mathrm{c}}$. Our halo property emulators achieve an accuracy of $\lesssim 1\%$ on independent test data sets. We demonstrate that the emulators can be combined with a galaxy-halo connection prescription to accurately predict the galaxy-galaxy and galaxy-matter correlation functions using the halo model framework.

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arXiv2022

MGLenS: Modified gravity weak lensing simulations for emulation-based cosmological inference

We present MGLenS, a large series of modified gravity lensing simulations tailored for cosmic shear data analyses and forecasts in which cosmological and modified gravity parameters are varied simultaneously. Based on the FORGE and BRIDGE $N$-body simulation suites presented in companion papers, we construct 500,000 deg$^2$ of mock Stage-IV lensing data, sampling a pair of 4-dimensional volumes designed for the training of emulators. We validate the accuracy of MGLenS with inference analyses based on the lensing power spectrum exploiting our implementation of $f(R)$ and nDGP theoretical predictions within the cosmoSIS cosmological inference package. A Fisher analysis reveals that the vast majority of the constraining power from such a survey comes from the highest redshift galaxies alone. We further find from a full likelihood sampling that cosmic shear can achieve 95% CL constraints on the modified gravity parameters of log$_{10}\left[ f_{R_0}\right] < -5.24$ and log$_{10}\left[ H_0 r_c\right] > -0.05$, after marginalising over intrinsic alignments of galaxies and including scales up to $\ell=5000$. Such a survey setup could in fact detect with more than $3σ$ confidence $f(R)$ values larger than $3 \times 10^{-6}$ and $H_0 r_c$ smaller than 1.0. Scale cuts at $\ell=3000$ reduce the degeneracy breaking between $S_8$ and the modified gravity parameters, while photometric redshift uncertainty seem to play a subdominant role in our error budget. We finally explore the consequences of analysing data with the wrong gravity model, and report the catastrophic biases for a number of possible scenarios. The Stage-IV MGLenS simulations, the FORGE and BRIDGE emulators and the cosmoSIS interface modules will be made publicly available upon journal acceptance.

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arXiv2022

Cosmological forecasts with the clustering of weak lensing peaks

Maximising the information that can be extracted from weak lensing measurements is a key goal for upcoming surveys such as LSST and Euclid. This is typically achieved through statistics that are complementary to the cosmic shear two-point correlation function, the most well established of which is the weak lensing peak abundance. In this work, we study the clustering of weak lensing peaks, and present parameter constraint forecasts for an LSST-like survey. We use the cosmoslics $w$CDM simulations to measure the peak two-point correlation function for a range of cosmological parameters, and use the simulation data to train a Gaussian process regression emulator which is applied to generate likelihood contours and provide parameter constraint forecasts from mock observations. We investigate the dependence of the peak two-point correlation function on the peak height, and find that the clustering of low amplitude peaks is complementary to that of high amplitude peaks. Consequently, their combination gives significantly tighter constraints than the clustering of high peaks alone. The peak two-point correlation function is significantly more sensitive to the cosmological parameters $h$ and $w_0$ than the peak abundance, and when the probes are combined, constraints on $Ω_{\rm m}$, $S_8$, $h$ and $w_0$ improve by at least a factor of two, relative to the peak abundance alone. Finally, we compare the forecasts for weak lensing peaks and weak lensing voids, and show that the two are also complementary; both probes can offer better constraints on $S_8$ and $w_0$ than the shear correlation function by roughly a factor of two.

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arXiv2021

Constraining cosmology with weak lensing voids

Upcoming surveys such as \LSST{} and \Euclid{} will significantly improve the power of weak lensing as a cosmological probe. To maximise the information that can be extracted from these surveys, it is important to explore novel statistics that complement standard weak lensing statistics such as the shear-shear correlation function and peak counts. In this work, we use a recently proposed weak lensing observable -- weak lensing voids -- to make parameter constraint forecasts for an LSST-like survey. We use the \cosmoslics{} $w$CDM simulation suite to measure void statistics as a function of cosmological parameters. The simulation data is used to train a Gaussian process regression emulator that we use to generate likelihood contours and provide parameter constraints from mock observations. We find that the void abundance is more constraining than the tangential shear profiles, though the combination of the two gives additional constraining power. We forecast that without tomographic decomposition, these void statistics can constrain the matter fluctuation amplitude, $S_8$ within 0.3\% (68\% confidence interval), while offering 1.5, 1.5 and 2.7\% precision on the matter density parameter, $Ω_{\rm m}$, the reduced Hubble constant, $h$, and the dark energy equation of state parameter, $w_0$, respectively. These results are tighter than the constraints from the shear-shear correlation function with the same observational specifications for $Ω_m$, $S_8$ and $w_0$. The constraints from the WL voids also have complementary parameter degeneracy directions to the shear 2PCF for all combinations of parameters that include $h$, making weak lensing void statistics a promising cosmological probe.

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arXiv2020

Proca-stinated Cosmology II: Matter, Halo, and Lensing Statistics in the vector Galileon

The generalised Proca (GP) theory is a modified gravity model in which the acceleration of the cosmic expansion rate can be explained by self interactions of a cosmological vector field. In this paper we study a particular sub-class of the GP theory, with up to cubic order Lagrangian, known as the cubic vector Galileon (cvG) model. This model is similar to the cubic scalar Galileon (csG) in many aspects, including a fifth force and the Vainshtein screening mechanism, but with the additional flexibility that the strength of the fifth force depends on an extra parameter -- interpolating between zero and the full strength of the csG model -- while the background expansion history is independent of this parameter. It offers an interesting alternative to LambdaCDM in explaining the cosmic acceleration, as well as a solution to the tension between early- and late-time measurements of the Hubble constant H_0. To identify the best ways to test this model, in this paper we conduct a comprehensive study of the phenomenology of this model in the nonlinear regime of large-scale structure formation, using a suite of N-body simulations run with the modified gravity code ECOSMOG. By inspecting thirteen statistics of the dark matter field, dark matter haloes and weak lensing maps, we find that the fifth force in this model can have particularly significant effects on the large-scale velocity field and lensing potential at late times, which suggest that redshift-space distortions and weak lensing can place strong constraints on it.

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arXiv2020

Optimal void finders in weak lensing maps

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.

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arXiv2020

The Accuracy of Weak Lensing Simulations

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 $\lesssim 2\%$ out to scales $\ell \approx 4000$. For lensing peak counts, the agreement is better than $5\%$ for peaks with signal-to-noise $\lesssim 6$. 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.

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arXiv2019

Cosmological test of gravity using weak lensing voids

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 $\rm{SNR} = 50$ and $70$ for a popular class of modified gravity in an LSST-like survey.

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arXiv2019

The self similarity of weak lensing peaks

We study the statistics of weak lensing convergence peaks, such as their abundance and two-point correlation function (2PCF), for a wide range of cosmological parameters $Ω_m$ and $σ_8$ within the standard $Λ$CDM paradigm, focusing on intermediate-height peaks with signal-to-noise 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 $\sim3\%$. 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 $\sim5\%$. 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.

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