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Carlo Giocoli

Publications and source records attributed to Carlo Giocoli.

At least 37 records · Page 2Linked to original sources

The Three Hundred: $M_{sub}-V_{circ}$ relation

In this study, we investigate a recent finding based on strong lensing observations, which suggests that the sub-halos observed in clusters exhibit greater compactness compared to those predicted by $Λ$CDM simulations. To address this discrepancy, we performed a comparative analysis by comparing the cumulative mass function of sub-halos and the $M_{\text{sub}}$-$V_{\text{circ}}$ relation between observed clusters and 324 simulated clusters from The Three Hundred project, focusing on re-simulations using GADGET-X and GIZMO-SIMBA baryonic models. The sub-halos' cumulative mass function of the GIZMO-SIMBA simulated clusters agrees with observations, while the GADGET-X simulations exhibit discrepancies in the lower sub-halo mass range possibly due to its strong SuperNova feedback. Both GADGET-X and GIZMO-SIMBA simulations demonstrate a redshift evolution of the sub-halo mass function and the $V_{max}$ function, with slightly fewer sub-halos observed at lower redshifts. Neither the GADGET-X nor GIZMO-SIMBA(albeit a little closer) simulated clusters' predictions for the $M_{\text{sub}}$-$V_{\text{circ}}$ relation align with the observational result. Further investigations on the correlation between sub-halo/halo properties and the discrepancy in the $M_{\text{sub}}$-$V_{\text{circ}}$ relation reveals that the sub-halo's half mass radius and galaxy stellar age, the baryon fraction and sub-halo distance from the cluster's centre, as well as the halo relaxation state play important roles on this relation. Nevertheless, we think it is still challenging in accurately reproducing the observed $M_{\text{sub}}$-$V_{\text{circ}}$ relation in our current hydrodynamic cluster simulation under the standard $Λ$CDM cosmology.

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AMICO galaxy clusters in KiDS-DR3: constraints on $Λ$CDM from extreme value statistics

We constrain the $Λ$CDM cosmological parameter $σ_{8}$ by applying the extreme value statistics for galaxy cluster mass on the AMICO KiDS-DR3 catalog. We sample the posterior distribution of the parameters by considering the likelihood of observing the largest cluster mass value in a sample of $N_{\textrm{obs}} = 3644$ clusters with intrinsic richness $λ^{*} > 20$ in the redshift range $z\in[0.10, 0.60]$. We obtain $σ_{8}=0.90_{-0.18}^{+0.20}$, consistent within $1σ$ with the measurements obtained by the Planck collaboration and with previous results from cluster cosmology exploiting AMICO KiDS-DR3. The constraints could improve by applying this method to forthcoming missions, such as $\textit{Euclid}$ and LSST, which are expected to deliver thousands of distant and massive clusters.

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FORECAST: a flexible software to forward model cosmological hydrodynamical simulations mimicking real observations

We present FORECAST, a new flexible and adaptable software package that performs forward modeling of the output of any cosmological hydrodynamical simulations to create a wide range of realistic synthetic astronomical images. With customizable options for filters, field of view size and survey parameters, it allows users to tailor the synthetic images to their specific requirements. FORECAST constructs light-cone exploiting the output snapshots of a simulation and computes the observed flux of each simulated stellar element, modeled as a Single Stellar Population, in any chosen set of pass-band filters, including k-correction, IGM absorption and dust attenuation. As a first application, we emulated the GOODS-South field as observed for the CANDELS survey exploiting the IllustrisTNG simulation. We produce images of 200 sq. arcmin., in 13 bands (eight Hubble Space Telescope optical and near-infrared bands from ACS B435 to WFC3 H160, the VLT HAWK-I Ks band, and the four IRAC filters from Spitzer), with depths consistent with the real data. We analysed the images with the same processing pipeline adopted for real data in CANDELS and ASTRODEEP publications, and we compared the results against both the input data used to create the images, and real data, generally finding good agreement with both, with some interesting exceptions which we discuss. As part of this work, we release the FORECAST code and two datasets: the CANDELS dataset analyzed in this study, and 10 JWST CEERS survey-like images (8 NIRCam and 2 MIRI) in a field of view of 200 sq. arcmin. between z=0-20. FORECAST is a flexible tool: it creates images that can then be processed and analysed using standard photometric algorithms, allowing for a consistent comparison among observations and models, and for a direct estimation of the biases introduced by such techniques.

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Exploring the cosmological synergy between galaxy cluster and cosmic void number counts

Galaxy clusters and cosmic voids, the most extreme objects of our Universe in terms of mass and size, trace two opposite sides of the large-scale matter density field. By studying their abundance as a function of their mass and radius, respectively, i.e. the halo mass function (HMF) and void size function (VSF), it is possible to achieve fundamental constraints on the cosmological model. While the HMF has already been extensively exploited providing robust constraints on the main cosmological model parameters (e.g. $Ω_{\rm m}$, $σ_8$ and $S_8$), the VSF is still emerging as a viable and effective cosmological probe. Given the expected complementarity of these statistics, in this work we aim at estimating the costraining power deriving from their combination. To this end, we exploit realistic mock samples of galaxy clusters and voids extracted from state-of-the-art large hydrodynamical simulations, in the redshift range $0.2 \leq z \leq 1$. We perform an accurate calibration of the free parameters of the HMF and VSF models, needed to take into account the differences between the types of mass tracers used in this work and those considered in previous literature analyses. Then, we obtain constraints on $Ω_{\rm m}$ and $σ_8$ by performing a Bayesian analysis. We find that cluster and void counts represent powerful independent and complementary probes to test the cosmological framework. In particular, the constraining power of the HMF on $Ω_{\rm m}$ and $σ_8$ improves drastically with the VSF contribution, increasing the $S_8$ constraint precision by a factor of about 60%.

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Exploring the mass and redshift dependence of the cluster pressure profile with stacks on thermal SZ maps

We provide novel constraints on the parameters defining the universal pressure profile (UPP) within clusters of galaxies, and explore their dependence on the cluster mass and redshift, from measurements of Sunyaev-Zel'dovich Compton-$y$ profiles. We employ both the $\textit{Planck}$ 2015 MILCA and the ACT-DR4 $y$ maps over the common $\sim 2,100\,\text{deg}^2$ footprint. We combine existing cluster catalogs based on KiDS, SDSS and DESI observations, for a total of 23,820 clusters spanning the mass range $10^{14.0}\,\text{M}_{\odot}<M_{500}<10^{15.1}\,\text{M}_{\odot}$ and the redshift range $0.02<z<0.98$. We split the clusters into three independent bins in mass and redshift; for each combination we detect the stacked SZ cluster signal and extract the mean $y$ angular profile. The latter is predicted theoretically adopting a halo model framework, and MCMCs are employed to estimate the UPP parameters, the hydrostatic mass bias $b_{\rm h}$ and possible cluster miscentering effects. We constrain $[P_0,c_{500},α,β]$ to $[5.9,2.0,1.8,4.9]$ with $\textit{Planck}$ and to $[3.8,1.3,1.0,4.4]$ with ACT using the full cluster sample, in agreement with previous findings. We do not find any compelling evidence for a residual mass or redshift dependence, thus expanding the validity of the cluster pressure profile over much larger $M_{500}$ and $z$ ranges; this is the first time the model has been tested on such a large (complete and representative) cluster sample. Finally, we obtain loose constraints on the hydrostatic mass bias in the range 0.2-0.3, again in broad agreement with previous works.

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New applications of Graph Neural Networks in Cosmology

Upcoming cosmological surveys will provide unprecedented amount of data, which will require innovative statistical methods to maximize the scientific exploitation. Standard cosmological analyses based on abundances, two-point and higher-order statistics of cosmic tracers have been widely used to investigate the properties of the cosmic web and Large Scale Structure. However, these statistics can only exploit a subset of the entire information content available. Our goal is thus to implement new data analysis techniques based on machine learning to extract cosmological information through forward modelling, by directly exploiting the spatial coordinates and other observed properties of galaxies and galaxy clusters. Specifically, we investigated a new representation of large-scale structure data in the form of graphs. This data format can be directly fed to Graph Neural Networks, a recently proposed class of supervised Deep Learning algorithms. We tested the method on dark matter halo catalogues in different cosmologies, finding promising results. In particular, the method can discriminate among different dark energy models with high accuracy, through both binary classification ($99\%-$accuracy) and multi-class classification ($97\%-$accuracy). Moreover, it provides constraints on the value of $w_0$, through regression, with high precision.

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Galaxies in the central regions of simulated galaxy clusters

In this paper, we assess the impact of numerical resolution and of the implementation of energy input from AGN feedback models on the inner structure of cluster sub-haloes in hydrodynamic simulations. We compare several zoom-in re-simulations of a sub-sample of the cluster-sized haloes studied in Meneghetti et al. (2020), obtained by varying mass resolution, softening length and AGN energy feedback scheme. We study the impact of these different setups on the subhalo abundances, their radial distribution, their density and mass profiles and the relation between the maximum circular velocity, which is a proxy for subhalo compactness. Regardless of the adopted numerical resolution and feedback model, subhaloes with masses Msub < 1e11Msun/h, the most relevant mass-range for galaxy-galaxy strong lensing, have maximum circular velocities ~30% smaller than those measured from strong lensing observations of Bergamini et al. (2019). We also find that simulations with less effective AGN energy feedback produce massive subhaloes (Msub> 1e11 Msun/h ) with higher maximum circular velocity and that their Vmax - Msub relation approaches the observed one. However the stellar-mass number count of these objects exceeds the one found in observations and we find that the compactness of these simulated subhaloes is the result of an extremely over-efficient star formation in their cores, also leading to larger-than-observed subhalo stellar mass. We conclude that simulations are unable to simultaneously reproduce the observed stellar masses and compactness (or maximum circular velocities) of cluster galaxies. Thus, the discrepancy between theory and observations that emerged from the analysis of Meneghetti et al. (2020) persists. It remains an open question as to whether such a discrepancy reflects limitations of the current implementation of galaxy formation models or the LCDM paradigm.

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The probability of galaxy-galaxy strong lensing events in hydrodynamical simulations of galaxy clusters

Meneghetti et al. (2020) recently reported an excess of galaxy-galaxy strong lensing (GGSL) in galaxy clusters compared to expectations from the LCDM cosmological model. Theoretical estimates of the GGSL probability are based on the analysis of numerical hydrodynamical simulations in the LCDM cosmology. We quantify the impact of the numerical resolution and AGN feedback scheme adopted in cosmological simulations on the predicted GGSL probability and determine if varying these simulation properties can alleviate the gap with observations. We repeat the analysis of Meneghetti et al. (2020) on cluster-size halos simulated with different mass and force resolutions and implementing several independent AGN feedback schemes. We find that improving the mass resolution by a factor of ten and twenty-five, while using the same galaxy formation model that includes AGN feedback, does not affect the GGSL probability. We find similar results regarding the choice of gravitational softening. On the contrary, adopting an AGN feedback scheme that is less efficient at suppressing gas cooling and star formation leads to an increase in the GGSL probability by a factor between three and six. However, we notice that such simulations form overly massive subhalos whose contribution to the lensing cross-section would be significant while their Einstein radii are too large to be consistent with the observations. The primary contributors to the observed GGSL cross-sections are subhalos with smaller masses, that are compact enough to become critical for lensing. The population with these required characteristics appears to be absent in simulations.

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Brightest Cluster Galaxies Trace Weak Lensing Mass Bias and Halo Triaxiality in The Three Hundred Project

Galaxy clusters have a triaxial matter distribution. The weak-lensing signal, an important part in cosmological studies, measures the projected mass of all matter along the line-of-sight, and therefore changes with the orientation of the cluster. Studies suggest that the shape of the brightest cluster galaxy (BCG) in the centre of the cluster traces the underlying halo shape, enabling a method to account for projection effects. We use 324 simulated clusters at four redshifts between 0.1 and 0.6 from `The Three Hundred Project' to quantify correlations between the orientation and shape of the BCG and the halo. We find that haloes and their embedded BCGs are aligned, with an average $\sim$20 degree angle between their major axes. The bias in weak lensing cluster mass estimates correlates with the orientation of both the halo and the BCG. Mimicking observations, we compute the projected shape of the BCG, as a measure of the BCG orientation, and find that it is most strongly correlated to the weak-lensing mass for relaxed clusters. We also test a 2-dimensional cluster relaxation proxy measured from BCG mass isocontours. The concentration of stellar mass in the projected BCG core compared to the total stellar mass provides an alternative proxy for the BCG orientation. We find that the concentration does not correlate to the weak-lensing mass bias, but does correlate with the true halo mass. These results indicate that the BCG shape and orientation for large samples of relaxed clusters can provide information to improve weak-lensing mass estimates.

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Scatter in the satellite galaxy SHMR: fitting functions, scaling relations & physical processes from the IllustrisTNG simulation

The connection between galaxies and their dark matter haloes is often described with the Stellar-to-Halo Mass relation (SHMR). Satellite galaxies in clusters have been shown to follow a SHMR distinct from central galaxies because of the environmental processes that they are subject to. In addition, the variety of accretion histories leads to an important scatter in this relation, even more for satellites than for central galaxies. In this work, we use the hydrodynamical simulation IllustrisTNG to study the scatter in the satellite galaxy SHMR, and extract the parameters that can best allow to understand it. Active galaxies, that represent a very small fraction of cluster galaxies, follow a very different relation than their passive counterparts, mainly because they were accreted much more recently. For this latter population, we find that the distance to the cluster centre is a good predictor of variations in the SHMR, but some information on the galaxy orbital history, such as the distance of closest approach to the host centre, is an even better one, although it is in practice more difficult to measure. In addition, we found that galaxy compactness is also correlated with the SHMR, while the host cluster properties (mass and concentration, formation redshift, mass and size of BCG) do not play a significant role. We provide accurate fitting functions and scaling relations to the scientific community, useful to predict the subhalo mass given a set of observable parameters. Finally, we connect the scatter in the SHMR to the physical processes affecting galaxies in clusters, and how they impact the different satellite sub-populations.

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AMICO galaxy clusters in KiDS-DR3: Measurement of the halo bias and power spectrum normalization from a stacked weak lensing analysis

Galaxy clusters are biased tracers of the underlying matter density field. At very large radii beyond about 10 Mpc/\textit{h}, the shear profile shows evidence of a second-halo term. This is related to the correlated matter distribution around galaxy clusters and proportional to the so-called halo bias. We present an observational analysis of the halo bias-mass relation based on the AMICO galaxy cluster catalog, comprising around 7000 candidates detected in the third release of the KiDS survey. We split the cluster sample into 14 redshift-richness bins and derive the halo bias and the virial mass in each bin by means of a stacked weak lensing analysis. The observed halo bias-mass relation and the theoretical predictions based on the $Λ$CDM standard cosmological model show an agreement within $2σ$. The mean measurements of bias and mass over the full catalog give $M_{200c} = (4.9 \pm 0.3) \times 10^{13} M_{\odot}/\textit{h}$ and $b_h σ_8^2 = 1.2 \pm 0.1$. With the additional prior of a bias-mass relation from numerical simulations, we constrain the normalization of the power spectrum with a fixed matter density $Ω_m = 0.3$, finding $σ_8 = 0.63 \pm 0.10$.

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On the road to percent accuracy V: the non-linear power spectrum beyond $Λ$CDM with massive neutrinos and baryonic feedback

In the context of forthcoming galaxy surveys, to ensure unbiased constraints on cosmology and gravity when using non-linear structure information, percent-level accuracy is required when modelling the power spectrum. This calls for frameworks that can accurately capture the relevant physical effects, while allowing for deviations from $Λ$CDM. Massive neutrino and baryonic physics are two of the most relevant such effects. We present an integration of the halo model reaction frameworks for massive neutrinos and beyond-$Λ$CDM cosmologies. The integrated halo model reaction, combined with a pseudo power spectrum modelled by HMCode2020 is then compared against $N$-body simulations that include both massive neutrinos and an $f(R)$ modification to gravity. We find that the framework is 4% accurate down to at least $k\approx 3 \, h/{\rm Mpc}$ for a modification to gravity of $|f_{\rm R0}|\leq 10^{-5}$ and for the total neutrino mass $M_ν\equiv \sum m_ν\leq 0.15$ eV. We also find that the framework is 4% consistent with EuclidEmulator2 as well as the Bacco emulator for \B{most of the considered} $νw$CDM cosmologies down to at least $k \approx 3 \, h$/Mpc. Finally, we compare against hydrodynamical simulations employing HMCode2020's baryonic feedback modelling on top of the halo model reaction. For $νΛ$CDM cosmologies we find 2% accuracy for $M_ν\leq 0.48$eV down to at least $k\approx 5h$/Mpc. Similar accuracy is found when comparing to $νw$CDM hydrodynamical simulations with $M_ν= 0.06$eV. This offers the first non-linear, theoretically general means of accurately including massive neutrinos for beyond-$Λ$CDM cosmologies, and further suggests that baryonic, massive neutrino and dark energy physics can be reliably modelled independently.

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Nuw CDM cosmology from the weak lensing convergence PDF

Pinning down the total neutrino mass and the dark energy equation of state is a key aim for upcoming galaxy surveys. Weak lensing is a unique probe of the total matter distribution whose non-Gaussian statistics can be quantified by the one-point probability distribution function (PDF) of the lensing convergence. We calculate the convergence PDF on mildly non-linear scales from first principles using large-deviation statistics, accounting for dark energy and the total neutrino mass. For the first time, we comprehensively validate the cosmology-dependence of the convergence PDF model against large suites of simulated lensing maps, demonstrating its percent-level precision and accuracy. We show that fast simulation codes can provide highly accurate covariance matrices, which can be combined with the theoretical PDF model to perform forecasts and eliminate the need for relying on expensive N-body simulations. Our theoretical model allows us to perform the first forecast for the convergence PDF that varies the full set of $Λ$CDM parameters. Our Fisher forecasts establish that the constraining power of the convergence PDF compares favourably to the two-point correlation function for a Euclid-like survey area at a single source redshift. When combined with a CMB prior from Planck, the PDF constrains both the neutrino mass $M_ν$ and the dark energy equation of state $w_0$ more strongly than the two-point correlation function.

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AMICO galaxy clusters in KiDS-DR3: cosmological constraints from large-scale stacked weak lensing profiles

Context. The large-scale mass distribution around dark matter haloes hosting galaxy clusters provides sensitive cosmological information. Aims. In this work, we make use of a large photometric galaxy cluster sample, constructed from the public Third Data Release of the Kilo-Degree Survey, and the corresponding shear signal, to assess cluster masses and test the concordance $Λ$-cold dark matter ($Λ$CDM) model. In particular, we study the weak gravitational lensing effects on scales beyond the cluster virial radius, where the signal is dominated by correlated and uncorrelated matter density distributions along the line-of-sight. The analysed catalogue consists of 6962 galaxy clusters, in the redshift range $0.1 \leq z \leq 0.6$ and with signal-to-noise ratio larger than 3.5. Methods. We perform a full Bayesian analysis to model the stacked shear profiles of these clusters. The adopted likelihood function considers both the small-scale 1-halo term, used primarily to constrain the cluster structural properties, and the 2-halo term, that can be used to constrain cosmological parameters. Results. We find that the adopted modelling is successful to assess both the cluster masses and the total matter density parameter, $Ω_M$, when fitting shear profiles up to the largest available scales of 35 Mpc/h. Moreover, our results provide a strong observational evidence of the 2-halo signal in the stacked gravitational lensing of galaxy clusters, further demonstrating the reliability of this probe for cosmological studies. The main result of this work is a robust constraint on $Ω_M$, assuming a flat $Λ$CDM cosmology. We get $Ω_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments.

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Cosmic voids in modified gravity models with massive neutrinos

Cosmic voids are progressively emerging as a new viable cosmological probe. Their abundance and density profiles are sensitive to modifications of gravity, as well as to dark energy and neutrinos. The main goal of this work is to investigate the possibility of exploiting cosmic void statistics to disentangle the degeneracies resulting from a proper combination of $f(R)$ modified gravity and neutrino mass. We use N-body simulations to analyse the density profiles and size function of voids traced by both dark matter particles and haloes. We find clear evidence of the enhancement of gravity in $f(R)$ cosmologies in the void density profiles at $z=1$. However, these effects can be almost completely overridden by the presence of massive neutrinos because of their thermal free-streaming. Despite the limited volume of the analysed simulations does not allow us to achieve a statistically relevant abundance of voids larger than $40 \ \mathrm{Mpc}/h$, we find that the void size function at high redshifts and for large voids is potentially an effective probe to disentangle these degenerate cosmological models, which is key in the prospective of the upcoming wide field redshift surveys.

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Impact of baryons in cosmic shear analyses with tomographic aperture mass statistics

NonGaussian cosmic shear statistics based on weak-lensing aperture mass ($M_{\rm ap}$) maps can outperform the classical shear two-point correlation function ($γ$-2PCF) in terms of cosmological constraining power. However, reaching the full potential of these new estimators requires accurate modeling of the physics of baryons as the extra nonGaussian information mostly resides at small scales. We present one such modeling based on the Magneticum hydrodynamical simulation for the KiDS-450 and DES-Y1 surveys and a Euclid-like survey. We compute the bias due to baryons on the lensing PDF and the distribution of peaks and voids in $M_{\rm ap}$ maps and propagate it to the cosmological forecasts on the structure growth parameter $S_8$, the matter density parameter $Ω_{\rm m}$, and the dark energy equation of state $w_0$ using the SLICS and cosmo-SLICS sets of dark-matter-only simulations. We report a negative bias of a few percent on $S_8$ and $Ω_{\rm m}$ and also measure a positive bias of the same level on $w_0$ when including a tomographic decomposition. These biases reach $\sim 5$% when combining $M_{\rm ap}$ statistics with the $γ$-2PCF as these estimators show similar dependency on the AGN feedback. We verify that these biases constitute a less than $1σ$ shift on the probed cosmological parameters for current cosmic shear surveys. However, baryons need to be accounted for at the percentage level for future Stage IV surveys and we propose to include the uncertainty on the AGN feedback amplitude by marginalizing over this parameter using multiple simulations such as those presented in this paper. Finally, we explore the possibility of mitigating the impact of baryons by filtering the $M_{\rm ap}$ map but find that this process would require to suppress the small-scale information to a point where the constraints would no longer be competitive.

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An excess of small-scale gravitational lenses observed in galaxy clusters

Cold dark matter (CDM) constitutes most of the matter in the Universe. The interplay between dark and luminous matter in dense cosmic environments like galaxy clusters is studied theoretically using cosmological simulations. Observed gravitational lensing is used to test and characterize the properties of substructures - the small-scale distribution of dark matter - in clusters. An apt metric, the probability of strong lensing events produced by dark matter substructure, is devised and computed for 11 galaxy clusters. We report that observed cluster substructures are more efficient lenses than predicted by CDM simulations, by more than an order of magnitude. We suggest that hitherto undiagnosed systematic issues with simulations or incorrect assumptions about the properties of dark matter could explain our results.

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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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