# GCCL Seminars

The GCCL Seminar is a virtual video-link seminar where we invite speakers from around the globe to present their recent arxiv posting. The seminars are fairly interactive, with speakers asked about the details of the analysis throughout the talk to ensure that everyone understands. GCCL members from all nodes across Germany join this fortnightly event.

If you would like to give a seminar at the GCCL please contact Jan Luca van den Busch (jlvdb@astro.rub.de).

## Seminar Schedule

### 25/3/2022: Constance Mahony

The halo model with beyond-linear halo bias

## Abstract

The halo model is a phenomenological model often used to interpret the large-scale structure of the Universe. In this model all dark matter exists within dark matter halos, which trace the underlying matter fluctuations. In its most generic form it includes a number of approximations such as dark matter halos are spherical and can be completely described by their mass, and that the halos trace the underlying matter fluctuations in a linearly biased way – linear halo bias. These assumptions have provided a useful description of large-scale structure observables until now, but with ever improving datasets need to be revisited. In this talk I will present the error introduced in a joint halo model analysis of galaxy-galaxy lensing and galaxy clustering observables when adopting the standard approximation of linear halo bias. I will discuss how we include beyond-linear halo bias, compare to an alternative approach, and show that the direction of the sizable offsets depends on the freedom afforded to the halo model through other nuisance parameters. Finally, I will conclude that beyond-linear halo bias must be included in future cosmological halo model analyses of large-scale structure observables on non-linear scales.

### 4/3/2022: Alex Hall

Cosmology from weak lensing alone and implications for the Hubble tension

## Abstract

The quantity and quality of cosmic shear data that can be accurately modelled has grown significantly in recent years and will continue to grow with Euclid and Rubin fast approaching. With this ever-growing volume of data there is a risk that the physical interpretation of the resulting parameter constraints is obscured - such an interpretation is particularly desirable given the possibility that undiagnosed systematics might be present. In this talk I will discuss what cosmic shear surveys tell us about the cosmological parameters of Lambda-CDM. Using the halo model I will explain why current cosmic shear analyses seem to have almost no sensitivity to the Hubble constant and instead constrain well the ‘S8’ parameter combination. Finally I will discuss whether cosmic shear will ever be able to throw light on the ‘Hubble tension’, and present new results combining shear with CMB lensing and BAO to measure H0 independently of both the primordial microwave background fluctuations and the local distance ladder.

### 18/2/2022: Anik Halder

## Abstract

The integrated shear 3-point correlation function (i3PCF) is a higher-order lensing statistic that can be measured directly from cosmic shear data by correlating 1-point aperture mass statistics with local shear 2-point correlation functions (2PCF) measured within well-defined patches (or apertures) distributed across a survey footprint. In our recent work, we have introduced a new theoretical model using the response function approach to perturbation theory to calculate i3PCF that is (i) accurate on small angular scales, and (ii) that allows to take baryonic feedback effects into account similar to how they are currently accounted for in 2PCFs. I will discuss both these aspects and present Fisher forecasts which show that compared to a 2PCF only analysis, a combined 2PCF & i3PCF analysis can lead to significant improvements on the constraints of both cosmological and baryonic feedback parameters. This strengthens the prospects for cosmic shear data to obtain tighter constraints not only on cosmology but also on astrophysical feedback models using higher-order lensing statistics.

### 4/2/2022: Gabriel Bartosch Caminha

Cosmological constraints with galaxy cluster strong lenses

## Abstract

Galaxy cluster strong lensing has numerous applications in cosmology. Thanks to the wealth of multi-wavelength observations of clusters using state-of-the-art observatories, such as the Hubble Space Telescope and the Very Large Telescope, this field provides significant contributions to the understanding of our Universe. One of the main points still to be fully understood is the nature of the components that drives the evolution of the Universe, such as Dark Matter and Energy. This issue motivates further tests on the ΛCDM model, both at small and large scales, and they play an essential role in the concept and design of cosmological observations and programs.

One cosmological probe not yet fully explored is the cluster strong lensing cosmography. In this talk, I will present the combined strong lensing constraints from a sample of clusters on the background geometry of the Universe (see Caminha et al. 2022 A&A 657, 83, arXiv:2110.06232), in contrast to what was done with single systems until today. I will show that these strong lensing constraints are powerful in probing Ωm and the equation of state of the dark energy, including its evolution with redshift. Finally, I will show that strong lensing cosmography nicely complements other traditional probes such as the cosmic microwave background, Supernovae-Ia and Baryonic Acoustic Oscillations. Hence, cluster strong lensing can be a competitive cosmological probe and paramount in the observations of the next generation of telescopes such as the James Webb Space Telescope, Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid space telescope.

### 8/10/2021: Laila Linke

Using three-point functions of galaxies and matter to test galaxy models and cosmology

## Abstract

Two essential issues in astronomy are explaining the formation and evolution of galaxies and determining which cosmological model best describes the development of the Universe. In this talk, I discuss how third-order statistics of galaxies and weak lensing shear can help solve these issues. I concentrate on Galaxy-Galaxy-Galaxy-Lensing (G3L), which measures the correlation between the position of galaxy pairs and the shear generated by the matter distribution. This effect is a good tool for investigating the validity of galaxy models. We use it to test semi-analytic models (SAMs) of galaxies, which combine analytical prescriptions for baryonic effects with dark matter simulations, and the entirely analytical halo model approach. We compare G3L measurements in the overlap of the Kilo-Degree Survey (KiDS), the VISTA Kilodegree Infrared Galaxy survey (VIKING) and the Galaxy And Mass Assembly survey (GAMA) (KV450 x GAMA) to two SAMs. Then, we test whether an analytical model for galaxy-matter statistics can correctly describe the observed G3L. I present a halo model for G3L and investigate whether it can explain the G3L signal predicted by a simulation and observed in the KV450 x GAMA data set. Finally, I give a brief look into ongoing work in modelling and measuring third-order shear statistics. These statistics could help constrain cosmological models and calibrate “nuisance parameters” like the intrinsic alignment of galaxies.

### 24/9/2021: Tilman Tröster

## Abstract

Future weak lensing surveys aim to probe the matter distribution far into the non-linear regime. At these non-linear scales, weak lensing is sensitive to the effects of galaxy formation on the matter distribution, such as the redistribution of gas due to feedback from active galactic nuclei. In this talk I will present a cross-correlation analysis of weak lensing, a probe of the total matter distribution, and the tSZ effect, a probe of the gas density and temperature. I will discuss the constraints on the strength of baryon feedback and cosmological parameters that we derive from this cross-correlation measurement, as well as the challenges in the modelling and treatment of systematics. Finally, we combine the cross-correlation measurement with KiDS-1000 cosmic shear to derive tight cosmological constraints consistent with other low-redshift probes but preferring a lower amplitude of clustering than that inferred from the comic microwave background by Planck.

### 10/9/2021: Adam Broussard

Using a Neural Network Classifier to Select Galaxies with the Most Accurate Photometric Redshifts

## Abstract

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will produce several billion photometric redshifts (photo-z’s), enabling cosmological analyses to select a subset of galaxies with the most accurate photo-z. We perform initial redshift fits on Subaru Strategic Program galaxies with deep grizy photometry using Trees for Photo-Z (TPZ) before applying a custom neural network classifier (NNC) tuned to select galaxies with (zphot - zspec)/(1+zspec) < 0.10. We consider four cases of training and test sets ranging from an idealized case to using data augmentation to increase the representation of dim galaxies in the training set. Selections made using the NNC yield significant further improvements in outlier fraction and photo-z scatter (σz) over those made with typical photo-z uncertainties. As an example, when selecting the best third of the galaxy sample, the NNC achieves a 35% improvement in outlier rate and a 23% improvement in σz compared to using uncertainties from TPZ. For cosmology and galaxy evolution studies, this method can be tuned to retain a particular sample size or to achieve a desired photo-z accuracy; our results show that it is possible to retain more than a third of an LSST-like galaxy sample while reducing σz by a factor of two compared to the full sample, with one-fifth as many photo-z outliers. For surveys like LSST that are not limited by shot noise, this method enables a larger number of tomographic redshift bins and hence a significant increase in the total signal-to-noise of galaxy angular power spectra.

### 30/7/2021: Michael Chapman

Measuring the growth rate using small-scale clustering in eBOSS

## Abstract

Galaxy clustering measurements of the growth rate of cosmic structure provide important constraints on theories of modified gravity on cosmological scales. These measurements are typically made on large scales where the effect on the clustering is linear, however recent attempts to extract information on the growth rate using quasi-linear and non-linear scales have found a significant improvement in precision. I will present our measurement of the growth rate from the small-scale clustering of the eBOSS Luminous Red Galaxy sample with fibre-collisions corrected by an unbiased statistical method (pairwise-inverse probability weighting) and fit with a model based on the Aemulus cosmological emulator. Using the quasi-linear scales we measure the growth rate with nearly a factor of two improvement in precision over the large-scale analysis of the same sample, continuing the trend of galaxy clustering measurements yielding low values of the growth rate compared to LCDM+Planck2018 predictions and giving greater consistency with recent weak-lensing measurements of S_8. We also perform a consistency test with LCDM using the full separation range of the emulator and find a 4.5-sigma tension with the LCDM expectation, with the greatest tension coming from the non-linear scales. Our analysis also provides important insights for planning similar measurements using upcoming large surveys.

### 16/7/2021: Alex Amon

Dark Energy Survey Year 3 Results: Cosmology from Cosmic Shear and Robustness to Data Calibration

## Abstract

### 18/6/2021: Niall Jeffrey

DES Year 3: curved-sky weak lensing mass map reconstruction and applications

## Abstract

### 21/5/2021: Sihao Cheng

A new vocabulary for patterns and its cosmological applications, or, CNN without training

## Abstract

Textures and patterns are ubiquitous in astronomical data but challenging for quantitative analysis. I will present a new statistic, called the “scattering transform”, which borrows ideas from convolutional neural nets but requires no training. I will discuss its intuitive understandings. As an example, I will also show its application to information extraction from weak lensing maps, where it outperforms classic statistics and is on a par with neural nets. It is a powerful new approach in cosmology and beyond.

### 7/5/2021: Pablo Lemos

Cosmological tensions and how to find them

## Abstract

Cosmological tensions are of fundamental importance. Despite the increase in the precision and amount of data, the theory of Cosmology remains essentially the same as it has been for the last two decades. These tensions between measurements of the early and late Universe are at present the only existing hint of new physics in Cosmology. I will discuss methods to quantify tension. I will propose the `Suspiciousness’ statistic as the best metric of tension for cosmological problems, as it consists of fully Bayesian quantities, and does not depend on the prior volume. I will also discuss how this metric can be used for internal consistency tests, which are fundamental for present and future cosmological surveys. I will then apply this statistic to current cosmological data, and use it to quantify the consistency between Planck and the Dark Energy Survey Y1 data, as well as between three different Cosmic Microwave Background experiments (Planck, SPT and ACT).

### 23/4/2021: Susan Pyne

Self-calibration of weak lensing systematic effects using combined two- and three-point statistics

## Abstract

Estimation of cosmological parameters from next-generation weak-lensing surveys will be hampered mainly by systematic uncertainties, with statistical errors relatively well under control. This makes it worthwhile to explore novel ways to mitigate systematics. In the context of a Euclid-like survey, I will present results which suggest that three-point statistics have great potential in this respect. Looking at three major systematics - intrinsic alignments, photometric redshift uncertainties and multiplicative shear bias - I will show that a combined power spectrum-bispectrum analysis can be much more effective than the alternative of using two-point statistics with tight priors on nuisance parameters. On top of this, three-point statistics can self-calibrate the systematic effects, reducing the need for external calibration data.

### 12/3/2021: Vanessa Böhm

Inference from weak gravitational lensing with fast forward models (the MADLens code)

## Abstract

Upcoming experiments such as the LSST survey (Vera Rubin Observatory) or the EUCLID satellite will probe the weak cosmic shear signal far into the non-gaussian regime. These new datasets mark the end of an era in which power spectra analyses and linear models were close to optimal for extracting cosmological information from weak lensing data. New datasets require non-linear models and inference schemes that can accurately extract information from non-Gaussian signals. In my talk I will explore new avenues for weak gravitational lensing analysis and argue that they all rely on fast and differentiable data models. I will show how automatic differentiation which lies at the heart of deep neural networks can be exploited to develop differentiable N-body simulations and present MADLens, a fully differentiable weak gravitational lensing simulator that produces non-Gaussian convergence maps at unprecedented accuracy and low computational cost.

### 26/2/2021: Alexie Leauthaud

Lensing Without Borders

## Abstract

Lensing without borders is a cross-survey collaborative effort to test for the consistency of lensing signals across multiple lensing data sets and to play empirical constraints on the level of systematic errors. In this seminar, I will show results from Lensing Without Borders and will present empirical estimates for systematic errors. Lensing without borders uses tests based on galaxy-galaxy lensing and is based on the premise that the lensing signal around galaxies drawn from the BOSS survey should be independent of which survey is performing the measurement.

### 12/2/2021: Marco Gatti

Clustering Redshifts in DES Y3 and the DES Y3 photo-z calibration strategy

## Abstract

Clustering redshift methods exploit the two-point correlation signal between a photometric “unknown” sample and a “reference” sample of high fidelity redshift galaxies divided into thin bins to infer the redshift distributions of the photometric sample. In this seminar I will present the calibration of the Dark Energy Survey Year 3 (DES Y3) weak lensing source galaxy redshift distributions \uD835\uDC5B(\uD835\uDC67) from clustering measurements. Two distinct methods for using the clustering statistics will be described. The first uses the clustering information independently to estimate the mean redshift of the source galaxies within a redshift window. The second method establishes a likelihood of the clustering data as a function of \uD835\uDC5B(\uD835\uDC67), which can be incorporated into schemes for generating samples of \uD835\uDC5B(\uD835\uDC67) subject to combined clustering and photometric constraints. I will discuss the application of the two methods to data, and the role of clustering redshift in the overall DES Y3 photo-z calibration strategy.

### 29/1/2021: Kate Storey-Fisher

Binning is sinning: Clustering estimation without bins

## Abstract

The primary statistic for extracting cosmological information from large-scale structure is the two-point correlation function. It is typically measured in hard-edged bins of separation between tracer pairs (in redshift space or sky angle, for example). In this talk I will present a new estimator for the correlation function, the Continuous-Function Estimator, which generalizes the standard binned method to any basis function representation; it performs a least-squares fit of the pairs to this basis. This estimator can produce a continuous correlation function estimate with a small number of components; this is more scientifically appropriate and is critical for precise covariance matrix estimation. I will demonstrate the estimator with a basis designed to directly measure the baryon acoustic scale. I will discuss other potential applications of the Continuous-Function Estimator, such as investigating the dependence of clustering on galaxy properties and searching for anisotropies in large-scale structure.

### 15/1/2021: Joachim Harnois Deraps

## Abstract

### 11/12/2020: Ziang Yan

Galaxy cluster mass estimation with deep learning and hydrodynamical simulations

## Abstract

We evaluate the ability of Convolutional Neural Networks (CNNs) to predict galaxy cluster masses in the BAHAMAS hydrodynamical simulations. We train four separate single-channel networks using: stellar mass, soft X-ray flux, bolometric X-ray flux, and the Compton y parameter as observational tracers, respectively. Our training set consists of ∼4800 synthetic cluster images generated from the simulation, while an additional ∼3200 images form a validation set and a test set, each with 1600 images. In order to mimic real observation, these images also contain uncorrelated structures located within 50 Mpc in front and behind clusters and seen in projection, as well as instrumental systematics including noise and smoothing. In addition to CNNs for all the four observables, we also train a `multi-channel’ CNN by combining the four observational tracers. The learning curves of all the five CNNs converge within 1000 epochs. The resulting predictions are especially precise for halo masses in the range 10^13.25M⊙<M<10^14.5M⊙, where all five networks produce mean mass biases of order ≈1% with a scatter of ≲20%. The network trained with Compton y parameter maps yields the most precise predictions. We interpret the network’s behaviour using two diagnostic tests to determine which features are used to predict cluster mass. The CNN trained with stellar mass images detect galaxies (not surprisingly), while CNNs trained with gas-based tracers utilise the shape of the signal to estimate cluster mass.

### 13/10/2020: Harry Johnston

Systematic errors in weak lensing surveys and the utility of random galaxy catalogues

## Abstract

In this talk I will discuss the potential for galaxy intrinsic alignments (IA), photometric redshifts and variable observational conditions to introduce systematic biases into analyses of weak lensing by the large-scale structure. IA introduce correlations between galaxy shapes, and between shapes and the density field, that are not sourced by gravitational lensing; these correlations have the potential to pollute measurable cosmic shear signals, and thus bias cosmological inference. Moreover, cross-talk between IA and photo-z complicates the self-calibration of IA in 3x2-point analyses which attempt to use galaxy positional information to constrain nuisance parameterisations. The positional statistics utilised in such analyses are also prone to biases, as deep photometric surveys suffer from observational conditions that can impede the detection of galaxies, resulting in inhomogeneous selection functions in RA/DEC, and redshift. I will discuss: the difficulties inherent to characterising the intrinsic alignments of galaxies; forecasts for their mitigation with various models/priors; and methods for constructing random galaxy catalogues that are able to mitigate the impacts of photo-z and variable selection functions in the estimation of 2-point statistics.

### 30/10/2020: Tomasz Kacprzak

Cosmology with Artificial Intelligence

## Abstract

In recent years Artificial Intelligence methods have found multiple applications in cosmology. These methods are particularly well suited for the analysis of large scale structure, as they are capable of creating rich and complex models of non-linear data. In this talk I will present the first cosmology constraints derived using deep convolutional neural networks, using the KiDS-450 dataset, achieving more constraining power than the equivalent analysis with conventional methods. This analysis relies on the training sets consisting of grids of precise simulations. Generative AI models can also be used to create simulations of various observables, considerably speeding up simulation time. I will discuss the current and future directions in the AI-oriented cosmological analysis.

### 16/10/2020: Mathew Madhavacheril

The Atacama Cosmology Telescope: Weighing distant clusters with the most ancient light

## Abstract

We use gravitational lensing of the cosmic microwave background (CMB) to measure the mass of the most distant blindly-selected sample of galaxy clusters on which a lensing measurement has been performed to date. In CMB data from the the Atacama Cosmology Telescope (ACT) and the Planck satellite, we detect the stacked lensing effect from 677 near-infrared-selected galaxy clusters from the Massive and Distant Clusters of WISE Survey (MaDCoWS), which have a mean redshift of ⟨z⟩=1.08. There are no current optical weak lensing measurements of clusters that match the distance and average mass of this sample. We detect the lensing signal with a significance of 4.2σ. We model the signal with a halo model framework to find the mean mass of the population from which these clusters are drawn. Assuming that the clusters follow Navarro-Frenk-White density profiles, we infer a mean mass of ⟨M500c⟩=(1.7±0.4)×1014M⊙. We consider systematic uncertainties from cluster redshift errors, centering errors, and the shape of the NFW profile. These are all smaller than 30% of our reported uncertainty. This work highlights the potential of CMB lensing to enable cosmological constraints from the abundance of distant clusters populating ever larger volumes of the observable Universe, beyond the capabilities of optical weak lensing measurements.

### 4/10/2020: Mijin Yoon

Toward Solving the Puzzle: Dissecting the Complex Merger A521 with Multi-wavelength Data

## Abstract

A521 has been a subject of extensive panchromatic studies from X-ray to radio. The cluster possesses a number of remarkable features including a bright radio relic with a steep spectrum, more than three distinct galaxy groups forming a filament, and two disturbed X-ray peaks at odds with the distant position and tilted orientation of the radio relic. These several lines of evidence indicate a complex merger. In this paper, we present a multi-wavelength study of A521 based on Subaru optical, Hubble Space Telescope infrared, Chandra X-ray, GMRT radio, and MMT optical spectroscopic observations. Our weak-lensing (WL) analysis with improved systematics control reveals that A521 is mainly composed of three substructures aligned in the northwest to southeast orientation. These WL mass substructures are remarkably well-aligned with the cluster optical luminosity distribution constructed from our new enhanced cluster member catalog. These individual substructure masses are determined by simultaneously fitting three NFW profiles. We find that the total mass of A521 modeled by the superposition of the three halos is 13.0+1.0−1.3×1014M⊙, a factor of two higher than the previous WL measurement. With these WL mass constraints combined with X-ray and radio features, we consider two merging scenarios, carry out the corresponding numerical simulations, and discuss strengths and weaknesses of each case.

### 18/9/2020: Yi-Kuan Chiang

The Cosmic Thermal History Probed by Sunyaev-Zeldovich Effect Tomography

## Abstract

The cosmic thermal history, quantified by the evolution of the mean thermal energy density in the universe, is driven by the growth of structures as baryons get shock heated in collapsing dark matter halos. This process can be probed by redshift-dependent amplitudes of the thermal Sunyaev-Zeldovich (SZ) effect background. To do so, we cross-correlate eight sky intensity maps in the Planck and Infrared Astronomical Satellite missions with two million spectroscopic redshift references in the Sloan Digital Sky Surveys. This delivers snapshot spectra for the far-infrared to microwave background light as a function of redshift up to z∼3. We decompose them into the SZ and thermal dust components. Our SZ measurements directly constrain ⟨bPe⟩, the halo bias-weighted mean electron pressure, up to z∼1. This is the highest redshift achieved to date, with uncorrelated redshift bins thanks to the spectroscopic references. We detect a threefold increase in the density-weighted mean electron temperature T¯e from 7×105 K at z=1 to 2×106 K today. Over z=1-0, we witness the build-up of nearly 70% of the present-day mean thermal energy density ρth, with the corresponding density parameter Ωth reaching 1.5×10−8. We find the mass bias parameter of Planck’s universal pressure profile of B=1.27 (or 1−b=1/B=0.79), consistent with the magnitude of non-thermal pressure in gas motion and turbulence from mass assembly. We estimate the redshift-integrated mean Compton parameter y∼1.2×10−6, which will be tested by future spectral distortion experiments. More than half of which originates from the large-scale structure at z<1, which we detect directly.

### 4/9/2020: Eva-Maria Mueller

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

## Abstract

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Lyα forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, rd, from eight different samples and six measurements of the growth rate parameter, fσ8, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, ΛCDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a ΛCDM model. Regardless of cosmological model, the precision on ΩΛ, H0, and σ8, remains at roughly 1%, showing changes of less than 0.6% in the central values between models. The inverse distance ladder measurement under a ow0waCDM yields H0=68.20±0.81kms−1Mpc−1, remaining in tension with several direct determination methods. (abridged)

### 17/7/2020: Jessie Muir

Blinding multi-probe cosmological experiments

## Abstract

The goal of blinding is to hide an experiment’s critical results – here the inferred cosmological parameters – until all decisions affecting its analysis have been finalised. This is especially important in the current era of precision cosmology, when the results of any new experiment are closely scrutinised for consistency or tension with previous results. In analyses that combine multiple observational probes, like the combination of galaxy clustering and weak lensing in the Dark Energy Survey (DES), it is challenging to blind the results while retaining the ability to check for (in)consistency between different parts of the data. We propose a simple new blinding transformation that works by modifying the summary statistics that are input to parameter estimation, such as two-point correlation functions. The transformation shifts the measured statistics to new values that are consistent with (blindly) shifted cosmological parameters, while preserving internal (in)consistency. We apply the blinding transformation to simulated data for the projected DES Year 3 galaxy clustering and weak lensing analysis, demonstrating that practical blinding is achieved without significant perturbation of internal-consistency checks, as measured here by degradation of the χ2 between data and best-fitting model. Our blinding method conserves χ2 more precisely as experiments evolve to higher precision.

### 3/7/2020: Alessio Spurio Mancini

KiDS + GAMA: constraints on horndeski gravity from combined large-scale structure probes

## Abstract

We present constraints on Horndeski gravity from a combined analysis of cosmic shear, galaxy-galaxy lensing and galaxy clustering from 450deg2 of the Kilo-Degree Survey (KiDS) and the Galaxy And Mass Assembly (GAMA) survey. The Horndeski class of dark energy/modified gravity models includes the majority of universally coupled extensions to ΛCDM with one scalar field in addition to the metric. We study the functions of time that fully describe the evolution of linear perturbations in Horndeski gravity. Our results are compatible throughout with a ΛCDM model. By imposing gravitational wave constraints, we fix the tensor speed excess to zero and consider a subset of models including e.g. quintessence and f(R) theories. Assuming proportionality of the Horndeski functions αB and αM (kinetic braiding and the Planck mass run rate, respectively) to the dark energy density fraction ΩDE(a)=1−Ωm(a), we find for the proportionality coefficients α̂B=0.20+0.20−0.33 and α̂M=0.25+0.19−0.29. Our value of S8 is in better agreement with the Planck estimate when measured in the enlarged Horndeski parameter space than in a pure ΛCDM scenario. In our joint three-probe analysis we report a downward shift of the S8 best fit value from the Planck measurement of ΔS8=0.016+0.048−0.046 in Horndeski gravity, compared to ΔS8=0.059+0.040−0.039 in ΛCDM. Our constraints are robust to the modelling uncertainty of the non-linear matter power spectrum in Horndeski gravity.

### 19/6/2020: Benjamin Bose

Game of Gravities: Disputing the dark with galaxy surveys

## Abstract

Upcoming large-scale structure surveys will be able to measure the galaxy distribution to an unprecedented degree of accuracy, putting us in a position to learn a lot more about our Universe and the forces that have formed it. The amount we are able to learn though depends on how reliably we can model the physics we assume we are observing. Further, if we relax our assumptions about the physics, then the reliability and even availability of current predictive methods breaks down. In the first part of this talk I will present a promising method of accurately modelling non-standard physics in the matter power spectrum on linear to very non-linear scales. The second part will present a publicly available code, ReACT, that employs this method and can be directly applied to cosmic shear observations. Finally, I will present some applications of the code, including modified gravity forecasts for LSST and applications to galaxy clustering analyses.

### 5/6/2020: Joseph DeRose

The Buzzard Flock: Dark Energy Survey Synthetic Sky Catalogs

## Abstract

We present a suite of 18 synthetic sky catalogs designed to support science analysis of galaxies in the Dark Energy Survey Year 1 (DES Y1) data. For each catalog, we use a computationally efficient empirical approach, ADDGALS, to embed galaxies within light-cone outputs of three dark matter simulations that resolve halos with masses above ~5x10^12 h^-1 m_sun at z <= 0.32 and 10^13 h^-1 m_sun at z~2. The embedding method is tuned to match the observed evolution of galaxy counts at different luminosities as well as the spatial clustering of the galaxy population. Galaxies are lensed by matter along the line of sight — including magnification, shear, and multiple images — using CALCLENS, an algorithm that calculates shear with 0.42 arcmin resolution at galaxy positions in the full catalog. The catalogs presented here, each with the same LCDM cosmology (denoted Buzzard), contain on average 820 million galaxies over an area of 1120 square degrees with positions, magnitudes, shapes, photometric errors, and photometric redshift estimates. We show that the weak-lensing shear catalog, redMaGiC galaxy catalogs and redMaPPer cluster catalogs provide plausible realizations of the same catalogs in the DES Y1 data by comparing their magnitude, color and redshift distributions, angular clustering, and mass-observable relations, making them useful for testing analyses that use these samples. We make public the galaxy samples appropriate for the DES Y1 data, as well as the data vectors used for cosmology analyses on these simulations.

### 22/5/2020: Federico Bianchini

Constraints on Cosmological Parameters from the 500 deg^2 SPTpol Lensing Power Spectrum

## Abstract

We present cosmological constraints based on the cosmic microwave background (CMB) lensing potential power spectrum measurement from the recent 500 deg2 SPTpol survey, the most precise CMB lensing measurement from the ground to date. We fit a flat ΛCDM model to the reconstructed lensing power spectrum alone and in addition with other data sets: baryon acoustic oscillations (BAO) as well as primary CMB spectra from Planck and SPTpol. The cosmological constraints based on SPTpol and Planck lensing band powers are in good agreement when analysed alone and in combination with Planck full-sky primary CMB data. With weak priors on the baryon density and other parameters, the CMB lensing data alone provide a 4% constraint on σ8Ω0.25m=0.0593±0.025.. Jointly fitting with BAO data, we find σ8=0.779±0.023, Ωm=0.368+0.032−0.037, and H0=72.0+2.1−2.5kms−1Mpc−1, up to 2σ away from the central values preferred by Planck lensing + BAO. However, we recover good agreement between SPTpol and Planck when restricting the analysis to similar scales. We also consider single-parameter extensions to the flat ΛCDM model. The SPTpol lensing spectrum constrains the spatial curvature to be ΩK=−0.0007±0.0025 and the sum of the neutrino masses to be ∑mν<0.23 eV at 95% C.L. (with Planck primary CMB and BAO data), in good agreement with the Planck lensing results. With the differences in the S/N of the lensing modes and the angular scales covered in the lensing spectra, this analysis represents an important independent check on the full-sky Planck lensing measurement.

### 8/5/2020: William Hartley

## Abstract

Obtaining accurate distributions of galaxy redshifts is a critical aspect of weak lensing cosmology experiments. One of the methods used to estimate and validate redshift distributions is apply weights to a spectroscopic sample so that their weighted photometry distribution matches the target sample. In this work we estimate the \textit{selection bias} in redshift that is introduced in this procedure. We do so by simulating the process of assembling a spectroscopic sample (including observer-assigned confidence flags) and highlight the impacts of spectroscopic target selection and redshift failures. We use the first year (Y1) weak lensing analysis in DES as an example data set but the implications generalise to all similar weak lensing surveys. We find that using colour cuts that are not available to the weak lensing galaxies can introduce biases of Δ z∼0.015 in the weighted mean redshift of different redshift intervals. To assess the impact of incompleteness in spectroscopic samples, we select only objects with high observer-defined confidence flags and compare the weighted mean redshift with the true mean. We find that the mean redshift of the DES Y1 weak lensing sample is typically biased at the Δ z=0.005−0.05 level after the weighting is applied. The bias we uncover can have either sign, depending on the samples and redshift interval considered. For the highest redshift bin, the bias is larger than the uncertainties in the other DES Y1 redshift calibration methods, justifying the decision of not using this method for the redshift estimations. We discuss several methods to mitigate this bias.

### 17/4/2020: Matteo Costanzi

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing

## Abstract

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for S8=σ8(Ωm/0.3)0.5=0.65±0.04, driven by a low matter density parameter, Ωm=0.179+0.031−0.038, with σ8−Ωm posteriors in 2.4σ tension with the DES Y1 3x2pt results, and in 5.6σ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable-mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold (λ≥30) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.

### 3/4/2020: Andrina Nicola

Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release

## Abstract

We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be acquired by LSST, and are therefore an ideal test bed for the analysis methods being implemented by the LSST DESC. We select a magnitude limited sample with i<24.5 and analyze it in four redshift bins covering 0.15≲z≲1.5. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations. We demonstrate the use of map-level deprojection methods to account for fluctuations in the galaxy number density caused by observational systematics. Through an HOD analysis, we place constraints on the characteristic halo masses of this sample, finding a good fit up to scales kmax=1/Mpc, including both auto- and cross-correlations. Our results show monotonically decreasing average halo masses, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample. In terms of photometric redshift systematics, we show that additional care is needed in order to marginalize over uncertainties in the redshift distribution in galaxy clustering, and that these uncertainties can be constrained by including cross-correlations. We are able to make a ∼3σ detection of lensing magnification in the HSC data. Our results are stable to variations in σ8 and Ωc and we find constraints that agree well with measurements from Planck and low-redshift probes. Finally, we use our pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift.

### 20/3/2020: Maria Cristina Fortuna

The halo model as a versatile tool to predict intrinsic alignments

## Abstract

Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for a Stage III cosmic shear survey. We account for the different IA signatures at large and small scales as well for the different contribution from central/satellite and red/blue galaxies. We inform our model using the most recent observational findings: we include a luminosity dependence at both large and small scales and a radial dependence of the signal within the halo. We predict the impact of the total IA signal on the lensing angular power spectra, including the current uncertainties from the IA best-fits to illustrate the range of possible impact on the lensing signal: the lack of constraints for fainter galaxies is the main source of uncertainty for our predictions of the IA signal. We investigate how well the widely used non-linear alignment model can capture the complexity of the IA signal and find that while for Stage III surveys it is flexible enough, in the case of a Stage IV survey, this can lead to 1σ bias on Ωm.

### 6/3/2020: Angus Wright

Photometric Redshift Calibration with Self Organising Maps

## Abstract

Accurate photometric redshift calibration is central to the robustness of all cosmology constraints from cosmic shear surveys. Analyses of the Kilo-Degree Survey, KiDS, re-weighted training samples from all overlapping spectroscopic surveys to provide a direct redshift calibration. Using self-organising maps (SOMs) we demonstrate that this spectroscopic compilation is sufficiently complete for KiDS, representing 99% of the effective 2D cosmic shear sample. We use the SOM to define a 100% represented ‘gold’ cosmic shear sample, per tomographic bin. Using mock simulations of KiDS and the spectroscopic training set, we demonstrate that the mean redshift of the ‘gold’ sample can be recovered by the SOM with an accuracy better than |Δ⟨z⟩|<0.004, with the exception of the 0.7<z_B<0.9 tomographic bin with |Δ⟨z⟩|=0.011. Photometric noise, sample variance, and spectroscopic selection effects induce a combined maximal scatter of σ_{Δ⟨z⟩}<0.007 in all tomographic bins. We demonstrate that the previous direct redshift calibration method applied to the full cosmic shear sample is accurate to |Δ⟨z⟩|<0.025. We find that photometric noise dominates the calibration dispersion, and that neither sampling variance nor a realistic fraction of spectroscopic misidentifications in the training set introduce significant bias.

### 21/2/2020: Anna Niemiec

## Abstract

We present a new galaxy cluster lens modeling approach, hybrid-Lenstool, that is implemented in the publicly available modeling software Lenstool. hybrid-Lenstool combines a parametric approach to model the core of the cluster, and a non-parametric (free-form) approach to model the outskirts. hybrid-Lenstool optimizes both strong- and weak-lensing constraints simultaneously (Joint-Fit), providing a self-consistent reconstruction of the cluster mass distribution on all scales. In order to demonstrate the capabilities of the new algorithm, we tested it on a simulated cluster. hybrid-Lenstool yields more accurate reconstructed mass distributions than the former Sequential-Fit approach where the parametric and the non-parametric models are optimized successively. Indeed, we show with the simulated cluster that the mass density profile reconstructed with a Sequential-Fit deviates form the input by 2−3σ at all scales while the Joint-Fit gives a profile that is within 1−1.5σ of the true value. This gain in accuracy is consequential for recovering mass distributions exploiting cluster lensing and therefore for all applications of clusters as cosmological probes. Finally we found that the Joint-Fit approach yields shallower slope of the inner density profile than the Sequential-Fit approach, thus revealing possible biases in previous lensing studies.

### 7/2/2020: Hao-Yi (Heidi) Wu

## Abstract

Next-generation optical imaging surveys will revolutionise the observations of weak gravitational lensing by galaxy clusters and provide stringent constraints on growth of structure and cosmic acceleration. In these experiments, accurate modelling of covariance matrices of cluster weak lensing plays the key role in obtaining robust measurements of the mean mass of clusters and cosmological parameters. We use a combination of analytical calculations and high-resolution N-body simulations to derive accurate covariance matrices that span from the virial regime to linear scales of the cluster-matter cross-correlation. We validate this calculation using a public ray-tracing lensing simulation and provide a software package for calculating covariance matrices for a wide range of cluster and source sample choices. We discuss the relative importance of shape noise and density fluctuations, the impact of radial bin size, and the impact of off-diagonal elements. For a weak lensing source density 10 per square arcmin, shape noise typically dominates the variance on comoving scales less than 5 Mpc/h. However, for 60 per square arcmin, potentially achievable with future weak lensing experiments, density fluctuations typically dominate the variance at scales greater than 1 Mpc/h and remain comparable to shape noise on smaller scales.

### 17/1/2020: Alex Barreira

The Accuracy of Weak Lensing Simulations

## Abstract

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 ℓ≈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.

### 20/12/2020: Sandra Unruh

The importance of magnification effects in weak gravitational lensing

## Abstract

Magnification changes the observed number counts of galaxies on the sky. This biases the observed tangential shear profiles around galaxies, the so-called galaxy-galaxy lensing (GGL) signal, and the related excess mass profile. Correspondingly, inference of physical quantities, such as the mean mass profile of halos around galaxies, are affected by magnification effects. We use simulated shear and galaxy data of the Millennium Simulation to quantify the effect on shear and mass estimates from magnified lens and source number counts. The former are due to the large-scale matter distribution in the foreground of the lenses, the latter are caused by magnification of the source population by the matter associated with the lenses. The GGL signal is calculated from the simulations by an efficient fast-Fourier transform that can also be applied to real data. The numerical treatment is complemented by a leading-order analytical description of the magnification effects, which is shown to fit the numerical shear data well. We find the magnification effect is strongest for steep galaxy luminosity functions and high redshifts. For a lens redshift of zd=0.83, a limiting magnitude of 22mag in the r-band and a source redshift of zs=0.99, we find that a magnification correction changes the shear profile up to 45% and the mass is biased by up to 55%. For medium-redshift galaxies the relative change in shear and mass is typically a few percent. As expected, the sign of the bias depends on the local slope of the lens luminosity function αd, where the mass is biased low for αd<1 and biased high for αd>1. Whereas the magnification effect of sources is rarely than more 1%, the statistical power of future weak lensing surveys warrants correction for this effect.

### 6/12/2019: Aurel Schneider

Baryonic effects for weak lensing

## Abstract

I: Baryonic feedback effects lead to a suppression of the weak-lensing angular power spectrum on small scales. The poorly constrained shape and amplitude of this suppression is an important source of uncertainties for upcoming cosmological weak-lensing surveys such as Euclid or LSST. In this first paper in a series of two, we use simulations to build a Euclid-like tomographic mock data-set for the cosmic shear power spectrum and the corresponding covariance matrix, which are both corrected for baryons following the baryonification method of Schneider et al. (2019). In addition, we develop an emulator to obtain fast predictions of the baryonic suppression effects, allowing us to perform a likelihood inference analysis for a standard ΛCDM cosmology with both cosmological and astrophysical parameters. Our main findings are the following: (i) ignoring baryonic effects leads to a greater than 5σ bias on the cosmological parameters Ωm and σ8; (ii) restricting the analysis to the largest scales, that are mostly unaffected by baryons, makes the bias disappear, but results in a blow-up of the Ωm-σ8 contour area by more than a factor of 10; (iii) ignoring baryonic effects on the covariance matrix does not significantly affect cosmological parameter estimates; (iv) while the baryonic suppression is mildly cosmology dependent, this effect does not noticeably modify the posterior contours. Overall, we conclude that including baryonic uncertainties in terms of nuisance parameters allows us to obtain unbiased and surprisingly tight constraints on cosmological parameters.

https://arxiv.org/abs/1910.11357

II: An accurate modelling of baryonic feedback effects is required to exploit the full potential of future weak-lensing surveys such as Euclid or LSST. In this second paper in a series of two, we combine Euclid-like mock data of the cosmic shear power spectrum with an eROSITA X-ray mock of the cluster gas fraction to run a combined likelihood analysis including both cosmological and baryonic parameters. Following the first paper of this series, the baryonic effects (based on the baryonic correction model of Schneider et al. 2019) are included in both the tomographic power spectrum and the covariance matrix. However, this time we assume the more realistic case of a ΛCDM cosmology with massive neutrinos and we consider several extensions of the currently favoured cosmological model. For the standard ΛCDM case, we show that including X-ray data reduces the uncertainties on the sum of the neutrino mass by ∼30 percent, while there is only a mild improvement on other parameters such as Ωm and σ8. As extensions of ΛCDM, we consider the cases of a dynamical dark energy model (wCDM), a f(R) gravity model (fRCDM), and a mixed dark matter model (ΛMDM) with both a cold and a warm/hot dark matter component. We find that combining weak-lensing with X-ray data only leads to a mild improvement of the constraints on the additional parameters of wCDM, while the improvement is more substantial for both fRCDM and ΛMDM. Ignoring baryonic effects in the analysis pipeline leads significant false-detections of either phantom dark energy or a light subdominant dark matter component. Overall we conclude that for all cosmologies considered, a general parametrisation of baryonic effects is both necessary and sufficient to obtain tight constraints on cosmological parameters.

### 22/11/2019: Elena Sellentin

A blinding solution for inference from astronomical data

## Abstract

This paper presents a joint blinding and deblinding strategy for inference of physical laws from astronomical data. The strategy allows for up to three blinding stages, where the data may be blinded, the computations of theoretical physics may be blinded, and –assuming Gaussianly distributed data– the covariance matrix may be blinded. We found covariance blinding to be particularly effective, as it enables the blinder to determine close to exactly where the blinded posterior will peak. Accordingly, we present an algorithm which induces posterior shifts in predetermined directions by hiding untraceable biases in a covariance matrix. The associated deblinding takes the form of a numerically lightweight post-processing step, where the blinded posterior is multiplied with deblinding weights. We illustrate the blinding strategy for cosmic shear from KiDS-450, and show that even though there is no direct evidence of the KiDS-450 covariance matrix being biased, the famous cosmic shear tension with Planck could easily be induced by a mischaracterization of correlations between ξ_ at the highest redshift and all lower redshifts. The blinding algorithm illustrates the increasing importance of accurate uncertainty assessment in astronomical inferences, as otherwise involuntary blinding through biases occurs.

### 8/11/2019: Sherry Suyu

The latest cosmological results from H0LiCOW

## Abstract

We present a measurement of the Hubble constant (H0) and other cosmological parameters from a joint analysis of six gravitationally lensed quasars with measured time delays. All lenses except the first are analyzed blindly with respect to the cosmological parameters. In a flat ΛCDM cosmology, we find H0=73.3+1.7−1.8, a 2.4% precision measurement, in agreement with local measurements of H0 from type Ia supernovae calibrated by the distance ladder, but in 3.1σ tension with Planckobservations of the cosmic microwave background (CMB). This method is completely independent of both the supernovae and CMB analyses. A combination of time-delay cosmography and the distance ladder results is in 5.3σ tension with Planck CMB determinations of H0 in flat ΛCDM. We compute Bayes factors to verify that all lenses give statistically consistent results, showing that we are not underestimating our uncertainties and are able to control our systematics. We explore extensions to flat ΛCDM using constraints from time-delay cosmography alone, as well as combinations with other cosmological probes, including CMB observations from Planck, baryon acoustic oscillations, and type Ia supernovae. Time-delay cosmography improves the precision of the other probes, demonstrating the strong complementarity. Allowing for spatial curvature does not resolve the tension with Planck. Using the distance constraints from time-delay cosmography to anchor the type Ia supernova distance scale, we reduce the sensitivity of our H0 inference to cosmological model assumptions. For six different cosmological models, our combined inference on H0 ranges from ∼73-78 km s−1 Mpc−1, which is consistent with the local distance ladder constraints.