Enrique Paillas - Overview of beyond-2pt statistics Room: Lecture Hall, 1F Large-scale structure data contain a wealth of cosmological information on small scales that is difficult to model with theoretical approaches based on perturbation theory. I will present progress on our efforts to construct simulation-based emulators for galaxy clustering within the context of the Dark Energy Spectroscopic Instrument. These emulators encompass a wide variety of summary statistics, including standard two-point measurements (projected galaxy correlation function and multipole decompositions), as well as the bispectrum and other beyond-2PT alternative clustering statistics, such as cosmic voids, density-split statistics, wavelets, and Minkowski functionals.

Chihway Chang - Overview of photometric surveys and systematics Room: Lecture Hall, 1F

Ilaria Risso - Overview of spectroscopic surveys and systematics Room: Lecture Hall, 1F

Sunao Sugiyama - Cosmology with third-order shear statistics Room: Lecture Hall, 1F Third-order shear statistics, e.g. three-point correlation function of shear or mass skewness, is one of the most natural extensions of the standard two-point correlation function, and one of the few examples that has an analytic expression in terms of the underlying power spectrum (at PT regime) or bispectrum of large-scale structure. Because of its nice nature, 3pt has been studied for a long time, while its application to real data was limited until recently due to the challenges in the computational cost of measurement and theoretical prediction. In this talk, I will present a novel analysis method based on the Multipole expansion of shear 3PCF that enables the joint analysis of 2+3pt shear statistics, along with its applications to the DES and HSC data. We also present the mock analysis as a validation of the analysis method against the observational or astrophysical systematics, e.g. baryonic feedback effect or photometric redshift uncertainties.

Benjamin Giblin - Overcoming systematics in a beyond-two-point cosmic shear analysis with the Kilo-Degree Survey Room: Lecture Hall, 1F The probability density function of convergence maps (the lensing PDF) has been demonstrated to improve the precision of cosmological constraints over standard two-point (2pt) statistics by tens of percent. I will demonstrate how the cosmological dependence and impact of survey systematics on this statistic can be forward modelled using Gaussian process regression trained on N-body simulations. In particular, I will illustrate how intrinsic alignments, baryonic feedback, redshift distribution uncertainties, survey geometry, and galaxy shape noise can all be accounted for without sacrificing the gains in constraining power offered by this novel cosmic shear statistic. This work, undertaken with real data from the Kilo-Degree Survey (KiDS), sets the stage for overcoming the barriers posed by systematics in future beyond-2pt analyses with Stage-IV surveys such as Euclid and LSST.

Yin Li - TBD Room: Lecture Hall, 1F

Alan Zhou Room: Lecture Hall, 1F Map-level baryonification: unified treatment of weak lensing two-point and higher-order statistics Precision cosmology benefits from extracting maximal information from cosmic structure, motivating the use of higher-order statistics (HOS) at small spatial scales. However, predicting how baryonic processes modify matter statistics at these scales has been challenging. The baryonic correction model (BCM) addresses this by modifying dark-matter-only simulations to mimic baryonic effects, providing a flexible simulation-based framework for predicting both two-point and HOS. We show that a 3-parameter version of the BCM can jointly fit weak lensing maps' two-point statistics, wavelet phase harmonics coefficients, scattering coefficients, and the third and fourth moments to within 2\% accuracy across all scales $\ell < 2000$ and tomographic bins for a DES-Y3-like redshift distribution ($z \lesssim 2$) using the FLAMINGO simulations. These results demonstrate the viability of BCM-assisted simulation-based weak lensing inference of two-point and HOS, paving the way for robust cosmological constraints that fully exploit non-Gaussian information on small spatial scales.

Supranta Boruah Room: Lecture Hall, 1F Modeling astrophysical systematics for field-level weak lensing and galaxy clustering analysis I will present a novel field-level pipeline for the joint analysis of weak lensing and galaxy clustering data. Our method employs a "2.5-dimensional" field-level modeling approach, where the density field is represented in slabs of approximately 100 Mpc thickness. This strategy preserves the efficiency of 2D modeling while enabling flexible treatment of key astrophysical systematics. I will focus on modeling two critical systematics: galaxy bias and intrinsic alignment (IA). We show that field-level modeling of IA leads to more robust cosmological inference, achieving up to 5x tighter constraints on non-linear IA parameters. Additionally, I will discuss recent progress on modeling field-level galaxy bias, where we find that capturing small-scale clustering requires moving beyond the traditional Poisson likelihood to a non-Poissonian framework.

Biwei Dai Room: Lecture Hall, 1F Detecting Modeling Bias at the field level: Applications to HSC Y3 Simulation-based inference provides a powerful framework for extracting rich information from nonlinear scales in current and upcoming cosmological surveys, and ensuring its robustness requires stringent validation of forward models. In this talk, I frame forward model validation as an out-of-distribution (OoD) detection problem, where the field-level probability density serves as a diagnostic tool—analogous to a chi-squared test but applied at the field level. Using weak lensing maps, I demonstrate that the field-level likelihood density effectively identifies systematic modeling errors, such as baryonic feedback, and significantly outperforms summary statistics like the scattering transform (ST) or convolutional neural network (CNN)-learned statistics. Finally, I apply this framework to the HSC Y3 data to assess forward model validity and enhance simulation-based inference.

Lina Castiblanco Room: Lecture Hall, 1F Joint one-point analyses of weak lensing and galaxy clustering under the reign of systematics Next-generation galaxy surveys will provide vast datasets to improve our understanding of the Universe once we extract the maximum information content. However, the late-time matter distribution is non-Gaussian, limiting the information captured by two-point statistics. To fully exploit the cosmological signal, it is essential to incorporate beyond two-point statistics, such as one-point probability distribution functions (PDFs). One-point statistics capture key non-Gaussian information from galaxy clustering, and their combination with weak lensing offers a powerful way to jointly constrain galaxy bias and cosmology. In particular, the weak lensing convergence PDF is sensitive to the physics of the dark Universe, including dark matter and dark energy. Crucially, neglecting systematic effects such as shape noise, intrinsic alignments, photometric redshift errors, and mass-mapping can lead to biased cosmological parameter estimates. In the talk, I will present our analysis using the theoretical modelling of joint weak lensing–galaxy clustering PDF, focusing on the inclusion of systematic effects in a tomographic framework. Our approach is validated using lensing and clustering catalogues from N-body simulations that replicate the characteristics of Stage-IV galaxy surveys, paving the way toward robust cosmological inference with next-generation data.

Jessica Cowell Room: Lecture Hall, 1F First Constraints from Marked Angular Power Spectra with Subaru Hyper Suprime-Cam survey first-year data I will present the first application of marked angular power spectra to weak lensing data, using maps from the Subaru Hyper Suprime- Cam Year 1 (HSC-Y1) survey. Marked statistics, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. We test three mark functions that up/down-weight different density environments and evaluate their performance using simulations across 100 cosmologies. Our results show that combining marked auto- and cross-spectra improves constraints on the clustering amplitude parameter 𝑆8 by 50% compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on 𝑆8 ≡ 𝜎8√︁ Ω𝑚/0.3 = 0.808+0.023 −0.020. We assess the sensitivity of the marked power spectra to systematics including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias, and find that appropriate choices of smoothing scale mitigate small-scale leakage. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

Hironao Miyatake - Systematics in HSC 3x2pt analysis Room: Lecture Hall, 1F Cosmological constraints with cosmic shear, galaxy-galaxy lensing, and galaxy-galaxy clustering, which is the so-called 3x2pt analysis have become a standard probe in recent weak lensing surveys. I will explain details of systematics specifically in the HSC 3x2pt analysis, including galaxy shapes, photometric redshift, baryonic effect, and assembly bias, which could provide a good starting point to think about systematics in beyond two-point statistics.

Tanveer Karim - Modeling foreground systematics for cross-correlation analysis Room: Lecture Hall, 1F The advent of Stage-IV spectroscopic surveys such as DESI and photometric surveys such as LSST has provided a unique opportunity to study the temporal evolution of cosmological parameters using tomographic binning via cross-correlation. Cross-correlation, especially when considering two particularly dissimilar tracers such as galaxy surveys and CMB lensing, have been largely considered to be systematics free. However, the demands of ultra-precise measurements imply that we have to consider systematics that were previously hidden under statistical uncertainties or assumptions of independence. In this talk, I will use DESI Emission-Line Galaxies and LSST Lyman-Break Galaxies as case studies to underpin new sources of foreground systematics. I will also discuss possible new simulation requirements necessary to report unbiased and precise cosmological parameter measurements.

Eduardo Rozo - Dust-Reddening Self-Calibration in Photometric Survey Data Sets Room: Lecture Hall, 1F We will demonstrate how photometric survey data can be used to self-calibrate the impact of dust-reddening on galaxy magnitudes and colors. We will also discuss prospects for simultaneous forward-modeling of dust and the tomographic galaxy density field.

Carolyn Mill Room: Lecture Hall, 1F Photometric Redshift Uncertainties Meet Intrinsic Alignments The combined power of weak lensing, galaxy clustering, and galaxy-galaxy lensing (3x2pt) is a promising method to help us probe the underlying structure of our universe. This method helps us address key questions like the S8 tension and the nature of dark energy. Its statistical power relies on photometric redshifts, which allow us to build a vast and detailed evolutionary history of our universe. However, the uncertainty in the redshifts derived from this method and contamination from intrinsic alignments introduce significant systematic biases. The interacting effects of these systematics can degrade cosmological constraints and bias results, potentially causing us to misidentify the nature of our universe. I will be discussing the interplay of these systematics in a 3x2pt context and their effects on cosmology, as well as a look towards HOS and their response to these effects.

Maximilian von Wietersheim-Kramsta Room: Lecture Hall, 1F Weak Lensing Cosmology Beyond Two Points: Propagating Systematics through Forward Modelling and Simulation-Based Inference Weak gravitational lensing is a powerful probe of cosmic shear as it traces the large-scale structure of the Universe. The cosmic shear data from galaxy surveys is typically reduced to two-point correlation functions. These only contain a fraction of the constraining power on the cosmological model of the Universe present in the whole cosmic shear data measured by galaxy surveys. These surveys are limited by an assortment of instrumental, observational and astrophysical systematic effects which can be non-trivial to include in the modelling of the data and its uncertainty, especially, for higher-order statistics of the shear field. Such effects can be incorporated within accurate cosmological simulations to propagate them fully simulation-based inference (SBI). In this talk, I will present my work on forward modelling systematics in weak lensing data for both ground- and space-based weak lensing surveys, such as the Kilo-Degree Survey (KiDS) and Euclid, respectively. I will show how the spatially varying selection of galaxies, their redshifts and their shapes can be forward-modelled at the level of the catalogue. Since the systematics are simulated at the same stage as they would enter the real data, their impact is naturally incorporated in the higher-order statistics of the cosmic shear field. At the same time, this approach also accounts for the correlations between the selection function and other contaminant signals such as variations in the point-spread function or the clustering of sources. The inclusion of such anisotropic and correlated systematics, while subdominant in the two-point correlation functions, becomes more significant in the higher-order correlations of the shear field. This biases the signal of n-point correlation functions and the shear field as a whole, while also severely impacting the accuracy of the uncertainty estimates for two-point statistics. I will demonstrate how biases in the cosmological inference can be avoided through sequential neural likelihood estimation SBI from forward simulations of the KiDS-1000 and KiDS-Legacy data. I will also highlight my ongoing work on forward modelling systematic effects in Euclid, the unique challenges of a space mission (such as radiation damage of the detector) and how simulation-based inference can address the challenges when conducting cosmological parameter inference with higher-order statistics of cosmic shear observables as measured by Euclid.

Taisei Terawaki Room: Lecture Hall, 1F A survey-window free estimator of cosmic shear bispectrum The distortion of galaxy shapes caused by weak gravitational lensing due to foreground large-scale structures is a powerful tool for probing the spatial distribution of dark matter and the evolution of structure formation. Cosmic shear encodes information about the matter distribution in both the linear and nonlinear regimes. In this context, commonly used two-point statistics are not sufficient, and higher-order statistics are needed to fully capture the available information. The lowest-order higher-statistics is the bispectrum, the Fourier-transformed counterpart of the three-point correlation function. Therefore, utilizing the cosmic shear bispectrum enables to obtain tighter constraints on cosmological parameters, and also enables to investigate the parity violation in our universe and unknown systematics. However, straightforward Fourier analyses of survey data suffer from complications introduced by complex survey geometries and masked regions (e.g., due to bright stars). These effects mix Fourier modes, preventing a clean separation of the E/B modes and complicating the theoretical interpretation of the measured bispectrum. We have developed a new method to estimate the cosmic shear bispectrum that is free from the survey window effects, extending the maximum likelihood method, used in CMB and galaxy clustering analyses, to cosmic shear.

Ryo Terasawa Room: Lecture Hall, 1F Evaluation of baryonic feedback systematics and mitigation strategy: Insights from HSC-Y3 cosmic shear and prospects for HSC final year analysis and stage IV surveys Cosmic shear is a powerful probe of matter distribution, especially on small scales. Although the small scale data has a high signal-to-noise ratio, accurately modeling matter distribution on these scales is still challenging due to possible contamination from baryonic physics. These baryonic effects have garnered attention as potential contributors to alleviating the S8 tension observed between weak-lensing cosmology and the cosmology inferred from Planck data. As an alternative to pursuing an accurate or flexible baryonic physics model, our approach involves assessing the performance of a dark matter (DM)-only model prediction. We measured the correlation functions at scales below the fiducial scale cuts, reaching the scales where large k-modes (k ~ 10 h/Mpc) significantly contribute. Using this data, we evaluate the goodness-of-fit of DM-only model predictions. This model can fit the cosmic shear correlation functions measured from the HSC-Y3 data, even at scales below the fiducial scale cuts. The inferred cosmological parameters, especially S8, are not significantly biased compared to those from Li et al. (2023), which marginalize over a baryonic physics parameter and apply scale cuts to discard the scales where baryonic physics could largely affect the signal. From these findings, we conclude that we do not find a clear signature of baryonic effects in the HSC-Y3 cosmic shear data, considering its associated uncertainties. We further discuss the possibility of distinguishing an extreme baryonic effect for HSC final-year data and the Stage IV surveys such as Roman, LSST, and Euclid. Thanks to the statistical power of those future surveys, we will be able to reject an extreme feedback scenario at high significance using the cosmic shear data on small scales. Finally, we present the strategy for mitigating the baryonic feedback systematics in the upcoming HSC final-year cosmic shear analysis.

Andres Salcedo Room: Lecture Hall, 1F The Beyond Two Point Galaxy Clustering Challenge The last decade has seen significant improvements in the statistical power of galaxy survey data and in the methods for modeling such data. These improvements have motivated the development of a variety of novel techniques for analyzing this data either down to non-linear scales or beyond standard two-point statistics. We present the results of a masked "Beyond-2pt" community data challenge testing and benchmarking these techniques. The challenge dataset consists of HOD-based mock galaxy catalogues in real-space, redshift-space and on a light cone. Eight teams participated in this challenge, developing end-to-end pipelines to analyze the challenge mocks in order to constrain their unknown cosmological parameters. All teams were able to produce unbiased cosmology constraints, lending credibility to their various Beyond-2pt methods. Additionally we will present the outlook for a next generation of the Beyond-2pt challenge focused on constraints from surveys of emission line galaxies.

Georgios Valogiannis Room: Lecture Hall, 1F Going beyond the galaxy power spectrum: an analysis of DESI clustering data using the wavelet scattering transform Optimal extraction of the non-Gaussian information encoded in the Large-Scale Structure (LSS) of the universe lies at the forefront of modern precision cosmology. In this talk, I plan to discuss recent efforts to achieve this task using the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, I will present recent progress towards the application of this technique to DESI galaxy clustering observations, moving beyond a past analysis of the precursory BOSS dataset. I will summarize the latest efforts to assess the robustness of this estimator through an emulator mock challenge within the DESI collaboration, before discussing a series of improvements for its application to the anisotropic redshift-space clustering traced by DESI Year 1/Year 3 spectroscopic observations. Finally, I will show first proof-of-concept results from the application of this novel technique to another key cosmological probe, the Lyman-alpha forest.

Jaide Swanson Room: Lecture Hall, 1F

Bernhard Vos Room: Lecture Hall, 1F Counts-in-Cells modelling in spectroscopic and HI intensity mapping surveys The modelling of beyond two-point statistics is essential to interpret non-linear data from current and upcoming spectroscopic, photometric or Intensity Mapping surveys. We simulate Counts-in-Cells in spectroscopic and HI Intensity Mapping surveys. For the spectroscopic side, we show that Counts-in-Cells are essential to constrain the scatter of galaxies of Halo Occupation Distribution models, using galaxy catalogues adapted to eBOSS Emission-Line Galaxies. For the HI Intensity Mapping side, we generate SKA1-like Intensity Maps affected by observational systematics such as foreground removal and the telescope beam. We explore how Counts-in-Cells are affected by those systematics and we provide a theoretical model for the Counts-in-Cells.

Léa Harscouët Room: Lecture Hall, 1F The Filtered-Squared Bispectrum: on recycling the Pseudo-Cl framework for the study of 3-point correlators The study of correlators beyond the power spectrum has been hampered by the increased complexity of bispectrum estimators: the high dimensionality of the data vector, complex covariance estimation, and difficult generalisation to incomplete-sky surveys, make its use prohibitive -- despite its potential for extracting non-Gaussian information from LSS fields. The Filtered-Squared Bispectrum (FSB) is a novel projected bispectrum estimator which addresses most of these issues. It consists in taking the power spectrum of a field and a version of the field filtered on a range of harmonic scales, then squared in configuration space. Because the FSB reinterprets the bispectrum as a power spectrum, we're able to recycle most of the infrastructure built around power spectrum measurements -- including corrections due to partial sky coverage, and covariance matrix estimation methods! The FSB estimator is robust to such mode-coupling effects, and we also provide a fully analytical and model-independent way to estimate its covariance, factoring in mode loss caused by incomplete observations.

Haruki Ebina Room: Lecture Hall, 1F Analytical modeling of the marked power spectrum The marked power spectrum has the potential to extract beyond-two-point information within the framework of a two-point function. This means that we could access valuable information in a computationally efficient way, while using much of the infrastructure already available for the power spectrum. In this talk I will present an analytical approach to modelling marked power spectra and show that by using low-order marks, we will be able to better control theoretical uncertainties. I will also show that the marked spectra is explicitly able to break degeneracies present in the power spectrum and share some recent progress.

Kevin Pardede Room: Lecture Hall, 1F Bispectrum and finite-volume effects Higher-order statistics, such as the galaxy bispectrum, provide complementary information to the power spectrum and are particularly sensitive to primordial non-Gaussianity (PnG). As upcoming galaxy surveys are expected to tighten constraints on PnG by an order of magnitude or more, it becomes crucial to account for sources of systematic contamination, especially those arising from finite-volume effects. In this talk, I will focus on the impact of survey geometry and wide-angle effects on the bispectrum multipoles. I will discuss recent progress in incorporating window function effects into bispectrum analyses, highlighting potential subtleties and challenges. In particular, I will show that wide-angle corrections can mimic a local PnG signal with an effective fNL∼0.1 in the bispectrum monopole and can induce a dipole component reaching a few percent of the flat-sky monopole amplitude. I will conclude by outlining future directions and possible applications of these works.

Claire Lamman Room: Lecture Hall, 1F Multiplet Alignment: bridging large and small-scale clustering The large-scale tidal field can be traced by the alignment of small groups, or "multiplets" of galaxies. Multiplets mostly consist of 2-4 galaxies within 1 Mpc/h of each other, and we measure their orientations relative to the galaxy-traced tidal field. Multiplet alignment has been detected in the DESI Survey out to projected separations 100 Mpc/h, demonstrating that small-scale clustering preserves an interpretable memory of large-scale structure. I will cover potential applications and a first look at multiplet alignment across cosmological simulations.

Hanyu Zhang Room: Lecture Hall, 1F Mitigating Projection Effects in Full-Shape Analyses Projection effects in full-shape analyses of galaxy clustering arise when nuisance parameters are degenerate with cosmological parameters and governed by weakly constrained or poorly defined priors. We outline three complementary mitigation strategies: employing simulation-based nuisance priors from realistic mock catalogs; applying non-linear reparameterizations to decorrelate nuisance and cosmological parameters; and leveraging frequentist inference methods to minimize explicit prior dependence. Together, these approaches enhance the reliability of cosmological constraints and offer complementary interpretations of the data.

Tomomi Sunayama - Systematics on Subaru PFS Cosmology program and beyond Room: Lecture Hall, 1F

Yi-Kuan Chiang - A Long Quest to Map the Full-Sky Dust Reddening Field Room: Lecture Hall, 1F

Pierluigi Monaco - Data systematics in the Euclid spectroscopic survey Room: Lecture Hall, 1F

Ni Emas Room: Lecture Hall, 1F TBD

Federico Rizzo Room: Lecture Hall, 1F Window Convolution & Interloper Modeling in the Euclid Data Analysis The power spectrum of the spectroscopic galaxy catalog is one of the main observables of the Euclid mission. I will discuss possible systematic errors directly related to the adopted estimator and its implementation. I will quantify their contribution to the overall error budget and compare it to the expected statistical error for the full mission. In addition, I will discuss the impact of line and noise interlopers that might be important for Euclid results.

Kevin McCarthy Room: Lecture Hall, 1F

Alberto Rosado-Marin Room: Lecture Hall, 1F Imaging Systematics Treatment for DESI ELGs: Effects on Constraining Primordial non-Gaussianity Angular imaging systematics can introduce non-trivial spurious large-scale correlations in the observed target density along the sky. Hence, the Dark Energy Spectroscopic Instrument (DESI) survey, like other surveys, has an ongoing imaging systematic mitigation effort. This effect is strongest for the Emission Line Galaxies (ELGs) sample, and its treatment requires non-linear mitigation techniques, such as machine learning. Such mitigation methods must be employed with care and require rigorous validation as they can over-fit and remove modes at large scales, especially hindering the accurate measurement of primordial non-Gaussianity (PNG). My talk will give an overview of the DESI imaging systematics on the two-point clustering statistics including the BAO measurements and how one can validate and robustly extract PNG information using cross-tracers of ELGs, LRGs, and QSOs.

Shengyu He Room: Lecture Hall, 1F DESI DR2 spectroscopic systematics The Dark Energy Spectroscopic Instrument (DESI) is conducting an extensive spectroscopic survey to map the large-scale structure of the universe with unprecedented precision. As part of the second data release (DR2), it is essential to quantify and mitigate spectroscopic systematics that could bias cosmological measurements. In this talk, I will present an overview of the spectroscopic systematics identified in the DESI DR2 data, with a particular focus on redshift uncertainties and catastrophic failures. I will discuss how repeat observations are utilized to estimate redshift error distributions and how these corrections are applied to simulated galaxy mocks. Additionally, I will explore the implications of these systematics for galaxy clustering analyses and the measurement of cosmological parameters. Understanding and correcting these biases is crucial not only for two-point statistics but also for advancing beyond-two-point statistics, like three-point-statistics in the analysis of large-scale structure.