arXiv subjects

Takahiro Nishimichi

Publications and source records attributed to Takahiro Nishimichi.

At least 19 recordsLinked to original sources

arXiv2026

A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $Λ$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented.

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arXiv2026

The Environmental Dependence of Halo Intrinsic Alignments: Stronger Signals in Underdense Regions

The intrinsic alignment (IA) of galaxies and the dark matter haloes that host them is one of the leading astrophysical systematics for weak-lensing cosmology, yet how the IA signal depends on the large-scale environment in which haloes reside is not yet fully characterised. We use the high-resolution $N$-body simulations of the Dark Quest suite to measure the environmental dependence of the IA of dark matter haloes over the redshift range $z=0.1$--$1.5$. We quantify each halo's environment through the overdensity $δ_8$, defined from the number of neighbouring haloes within $8\, h^{-1}Mpc$, and we isolate the environmental effect from its degeneracy with the halo-mass dependence by comparing the most overdense and most underdense haloes constructed to share the same halo-mass distribution. We find that haloes in underdense environments exhibit systematically larger IA amplitudes $A_{\rm IA}$ than haloes of the same mass in overdense environments, by a factor of $\sim1.5$--$1.8$, and that this trend persists across the mass and redshift ranges probed, strengthening towards low redshift. Using an orientation-only (unit-ellipticity) estimator, we further show that this environmental contrast is driven by a combination of two effects: haloes in underdense regions are both intrinsically less spherical and more strongly aligned with the large-scale tidal field than their overdense counterparts of the same mass. These results indicate that the large-scale environment is a non-negligible variable in modelling halo and galaxy alignments, and may be a particularly important factor for beyond-two-point weak-lensing analyses.

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arXiv2026

GINKAKU: Scalable Cosmological Structure Formation Simulation Code and Post-processing Pipeline

We introduce GINKAKU, a new cosmological $N$-body code developed for the Dark Quest II (DQ2) simulation campaign and designed for controlled ensemble production across the cosmological model space required by next-generation galaxy surveys, including massive neutrinos and clustering dark energy. Built on the FDPS framework, GINKAKU couples a TreePM gravity solver with a linear-response treatment of external source terms for components not evolved as $N$-body particles, formulated in the $N$-body gauge. This design incorporates massive-neutrino perturbations, general-relativistic corrections, early-time radiation perturbations, and dark-energy clustering with non-unit effective sound speed at the linear level, while preserving Newtonian particle dynamics on subhorizon scales. The code is validated through internal convergence studies and cross-comparisons with GADGET, PKDGRAV3, and RAMSES on shared initial conditions: code-to-code differences in the nonlinear power spectrum can be reduced below $\sim1\%$ level by tuning internal accuracy parameters, and we identify a production-grade fiducial setting achieving this control at modest cost. We apply GINKAKU to an initial set of DQ2 production runs -- eight cosmological models with $3,000^3$ particles in boxes up to $4\,h^{-1}\mathrm{Gpc}$ -- processed by a renewed post-processing pipeline that reduces the inter-resolution spread of the halo mass function to $\sim 1\%$ and includes halo-shape measurements for intrinsic-alignment statistics. The scale-dependent-growth cosmologies reproduce the expected nonlinear signatures of massive neutrinos and clustering dark energy, demonstrating suitability for emulator-scale production. A total matter power spectrum emulator from these runs is presented in an accompanying paper. (abridged)

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arXiv2026

Dark Quest II: A Wide-Coverage Neural Network Emulator of the Nonlinear Matter Power Spectrum Across Extended Cosmologies

\textsc{DarkEmulator2} is a neural network emulator of the nonlinear matter power spectrum in a nine-dimensional $w_0 w_a νo \mathrm{CDM}$ parameter space, developed as the emulator component of the \textsc{Dark Quest II} (DQ2) program. It is trained on simulations generated with the \textsc{Ginkaku} code, whose numerical implementation, accuracy tests, and post-processing pipeline are described in the companion paper. The design follows a unified strategy: in addition to the cosmological parameter vector, we supplement the neural network's inputs with three families of physically motivated auxiliary quantities -- the linear matter power spectrum, descriptors of the simulation resolution, and a low-dimensional summary of the initial Gaussian random field -- that are expected to improve generalization across the parameter space. Training a single network jointly across three simulation resolution tiers allows the emulator to exploit a small number of high-resolution simulations while retaining broad coverage from lower-resolution simulations. For a $L_{\mathrm{box}}=1\,\hiGpc$ box with $N=3000^{3}$ particles, the emulator reproduces the simulated matter power spectrum to subpercent accuracy up to the particle Nyquist scale, $k_{\mathrm{Ny}}\simeq 10\,\hMpci$. The emulator remains accurate over the calibrated wavenumber range, while its highest-$k$ predictions depend on the simulation resolution and shot noise. We validate the emulator on independent test suites and, through a cross-comparison with several public emulators and widely used fitting formulas, characterize the inter-model consistency and the parameter-dependent trends in their residuals.

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arXiv2026

Nonlinear Information from DESI Luminous Red Galaxies: An Emulator-Based Analysis of Pre- and Post-Reconstruction Power Spectra

We present joint measurements of the pre- and post-reconstruction power spectra, $P_{\rm pre}$ and $P_{\rm post}$, together with their cross-power spectrum, $P_{\rm cross}$, for the Luminous Red Galaxies (LRGs) in the DESI Data Release 1 (DR1). We jointly analyse these observables with an emulator-based full-shape modeling framework, thereby, for the first time, we extract complementary nonlinear information from the galaxy density field before and after reconstruction in real survey data. Specifically, including $P_{\rm post}$ and $P_{\rm cross}$ in addition to $P_{\rm pre}$ (hereafter $P_{\rm all}$) yields an improvement of approximately $18$-$27\%$ in the $σ_8$ constraint in both $Λ$CDM and $w$CDM, depending on the redshift bin, relative to the $P_{\rm pre}$-only analysis with the cosmic microwave background distance priors (hereafter CMB). In $w$CDM, the joint CMB+$P_{\rm all}$ analysis can tighten the constraints on $w$ by approximately $5$-$15\%$ across the two LRG redshift bins, compared to the CMB+$P_{\rm pre}$ combination. Further incorporating the Type Ia supernova dataset and comparing the cosmological constraints in $w$CDM from each individual power-spectrum component with those from the full combination, we find that $P_{\rm all}$ consistently provides the tightest constraints. From the joint CMB+$P_{\rm all}$+DES-Dovekie dataset, we obtain $Ω_m = 0.314 \pm 0.0048$ and $w = -0.988 \pm 0.023$ for the \texttt{LRG1} sample, and $Ω_m = 0.318 \pm 0.0046$ and $w = -0.988 \pm 0.025$ for \texttt{LRG2}. These results demonstrate that combining pre- and post-reconstruction power spectra with their cross-correlation enables DESI to harvest additional nonlinear information, leading to tighter constraints on cosmological parameters.

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arXiv2026

Large-scale halo velocity correlations and the impact of finite simulation volumes

The velocity correlation functions directly measured from the peculiar velocity field of dark matter in numerical simulations are known to have an amplitude lower than that predicted by theoretical models at large scales. The trend persists for dark-matter halos or galaxies that are more closely related to the observables. We investigate the impact of the finite simulation box sizes on the measured velocity correlation functions of halos, utilizing N-body simulations with different box sizes. We measure the halo velocity correlations from N-body simulations with side lengths of $1{\rm Gpc}/h$ and $2{\rm Gpc}/h$, confirming the former is more suppressed compared to the linear theory prediction on large scales due to the lack of large-scale modes beyond the box size. In contrast, even though we subdivide the larger-box simulations into those with side lengths of $1{\rm Gpc}/h$, the amount of the suppression is the same as that from the original boxes, as the large-scale modes are already imprinted. Introducing the lower limit of the integral in the Hankel transform, $k_{\rm min}$, as a free parameter and marginalizing it over, we find that the constrained growth rate parameter, $f(z)σ_8(z)$, returns the correct value assumed in the simulations. However, when we ignore the effect and set $k_{\rm min}=0$, the constraint on $fσ_8$ is significantly biased if the correlation between different separation bins is also ignored. Furthermore, we find that the suppression of the velocity correlation amplitude on large scales depends on halo mass, with more massive halos exhibiting a systematically stronger suppression. These results highlight the importance of accounting for missing long-wavelength modes when developing simulation-based modeling of velocity statistics, such as emulators.

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arXiv2025

On priors and scale cuts in EFT-based full-shape analyses

Parameter estimation from galaxy survey data from the full-shape method depends on scale cuts and priors on EFT parameters. The effects of priors, including the so-called ''prior volume'' phenomenon have been originally studied in Ivanov et al. (2019) and subsequent works. In this note, we repeat and extend these tests and also apply them to other priors used in the literature. We point out that in addition to the ''prior volume'' effect there is a more dangerous effect that is largely overlooked: a systematic bias on cosmological parameters due to overoptimistic scale cuts. Unlike the ''prior volume'' effect, this is a genuine systematic bias due to two-loop corrections that does not vanish with better priors or with larger data volumes. Our study is based on the high fidelity BOSS-like PT Challenge simulation data which offer many advantages over analyses based on synthetic data generated with fitting pipelines. We show that some analysis choices associated with the PyBird code, especially the scale cuts, significantly bias parameter recovery, overestimating $σ_8$ by over $5\%$ (equivalent to $1σ$). The bias on measured EFT parameters is even more significant. In contrast, the analysis choices associated with the CLASS-PT code lead to much smaller ($\lesssim 1\%$) shifts in cosmological parameters based on their best-fit values.

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arXiv2025

Constraining cosmology with N-body simulations for future spectroscopic galaxy surveys at $2\leq z\leq 3$

Determining the spatial curvature ($Ω_k$) independent of cosmic microwave background observations plays a key role in revealing the physics of the early universe. The Hubble tension is one of the most serious issues in modern cosmology. We investigate halo catalogs identified from $N$-body simulations at $z=2$ and 3, mimicking high-redshift galaxy surveys. We measure redshift-space correlation functions of halos from the two snapshots. We detect clear features of baryon acoustic oscillations and redshift-space distortions. We find that we can obtain a few percent constraints on both the geometric distances and growth of structure at the distant universe in future surveys. By taking into account the information of the underlying matter power spectrum, we demonstrate that we can also achieve constraint on the Hubble constant $H_0$ with a few percent as well as the spatial curvature with $|Ω_k|\lesssim 0.1$ by observing galaxies with the number density with $\bar{n}_{\rm g}\simeq 10^{-4} (~h^3{\rm ~Mpc}^{-3})$. Our analysis provides a timely forecast for the upcoming spectroscopic surveys, which target emission line galaxy or dusty star-forming galaxy samples.

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arXiv2025

Modelling Galaxy Clustering and Tomographic Galaxy-Galaxy Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model and Redshift Self-Calibration

The combination of galaxy-galaxy weak lensing and galaxy clustering is a powerful probe of the cosmological model, and exploration of how to best model and extract this information from the signals is essential. We present the measurement of the galaxy-galaxy weak lensing signals using the SDSS DR11 spectroscopic galaxies as lens galaxies, and the HSC Y3 shear catalog as source galaxies, binned into four tomographic bins by their photometric redshift. The SDSS DR11 galaxies, with a redshift range $0.15<z<0.7$, are binned into three redshift bins, each as a probe for measuring the projected correlation function, $w_p(R_p)$. We measure the galaxy-galaxy lensing signal $ΔΣ(R_p)$ in 12 lens-source bin pairs and show that there is no evidence for significant systematic biases in the measurement with null testing. We combine our $w_p(R_p)$ and $ΔΣ(R_p)$ ($2\times2$pt) data vectors and perform likelihood inference with a flat $Λ$CDM model. For $ΔΣ(R_p)$, we extend the lower limit of the scale cut compared to previous HSC Y3 analyses to $2 h^{-1}$Mpc by including a point-mass correction term in addition to the minimal bias model. We present various tests to validate our model and provide extended consistency tests. In the $Λ$CDM context, our fiducial model yields $S_8 = 0.804^{+0.051}_{-0.051}$. The $2\times2$pt data vector provides redshift parameter constraints for the third and fourth redshift bins $Δz_3 = -0.079^{+0.074}_{-0.084}$, and $Δz_4 = -0.203^{+0.167}_{-0.206}$, which is consistent with results from the previous tomographic cosmic shear studies, and serves as the foundation for a future $3\times 2$pt analysis.

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arXiv2025

Cosmology and Source Redshift Constraints from Galaxy Clustering and Tomographic Weak Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model

The combination of galaxy clustering and weak lensing is a powerful probe of the cosmology model. We present a joint analysis of galaxy clustering and weak lensing cosmology using SDSS data as the tracer of dark matter (lens sample) and the HSC Y3 dataset as source galaxies. The analysis divides HSC Y3 galaxies into four tomographic bins for both galaxy-galaxy lensing and cosmic shear measurements, and employs a point-mass correction model to utilize galaxy-galaxy lensing signals down to 2$h^{-1}$Mpc, extending up to 70$h^{-1}$Mpc. These strategies enhance the signal-to-noise ratio of the galaxy-galaxy lensing data vector. Using a flat $Λ$CDM model, we find $S_8 = 0.780^{+0.029}_{-0.030}$, and using a $w$CDM model, we obtain $S_8 = 0.756^{+0.038}_{-0.036}$ with $w = -1.176^{+0.310}_{-0.346}$. We apply uninformative priors on the redshift mean-shift parameters for the third and fourth tomographic bins. Leveraging the self-calibration power of tomographic weak lensing, we measure $Δz_3 = -0.112^{+0.046}_{-0.049}$ and $Δz_4 = -0.185^{+0.071}_{-0.081}$, in agreement with previous HSC Y3 results. This demonstrates that weak lensing self-calibration can achieve redshift constraints comparable to other methods such as photometric and clustering redshift calibration.

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arXiv2025

Renormalized Perturbation Theory at Field-level: the LSS bootstrap in GridSPT

We present a first step toward field-level cosmological inference beyond the standard $Λ$CDM model, focusing on optimizing precision tests in the nonlinear regime of large-scale structure (LSS). As an illustrative case, we study the model-independent ``bootstrap'' coefficient of the second-order perturbation theory (PT) kernel for matter in real space, which we use as a proxy for new physics effects in the nonlinear sector. We discuss in details the ultraviolet (UV) cutoff dependence induced by discretizing fields on a grid, which requires proper renormalization to eliminate grid artifacts. We formulate a Wilsonian perturbative framework in which the evolution from a UV theory defined at a high cutoff $Λ_\text{uv}$ down to lower cutoffs is computed analytically, even beyond the validity of a derivative expansion. Within this framework, we develop an extended version of the GridSPT code incorporating the bootstrap parameterization and demonstrate how cutoff-independent predictions can be achieved through the inclusion of appropriate counterterms. We validate our approach at third- and fifth-order in PT, emphasizing the importance of higher-derivative contributions for unbiased parameter extraction. Our framework is readily extendable to biased tracers and redshift-space distortions.

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arXiv2025

First confirmation of anisotropic halo bias from statistically anisotropic matter distributions

We confirm for the first time the existence of distinctive halo bias associated with the quadrupolar type of statistical anisotropy (SA) of the linear matter density field using cosmological $N$-body simulations. We find that the coefficient of the SA-induced bias for cluster-sized halos takes negative values and exhibits a decreasing trend with increasing halo mass. This results in the quadrupole halo power spectra in a statistically anisotropic universe being less amplified compared to the monopole spectra. The anisotropic feature in halo bias that we found presents a promising new tool for testing the hypothesis of a statistically anisotropic universe, with significant implications for the precise verification of anisotropic inflation scenarios and vector dark matter and dark energy models.

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arXiv2025

SHAPE: cosmology with cluster halo intrinsic alignments from subhalo distributions

Galaxy clusters trace the most massive dark matter haloes, whose shapes and orientations reflect the imprint of the cosmic large-scale tidal field. This paper introduces the Subhalo-based Halo Alignment and Projected Ellipticity (SHAPE) technique, which reconstructs cluster halo shapes from the projected distribution of subhaloes, providing a novel approach to investigate intrinsic alignment (IA) correlations between cluster halo shapes and the surrounding density field. We measure halo shapes and orientations using different line-of-sight projection depths and find that, with modest projection depths, the shapes and orientations recovered by SHAPE show good agreement with those measured directly from the simulation particles. Using these SHAPE-derived shapes, we compute IA correlation functions from N-body simulations in both real and redshift space. The IA correlation multipoles exhibit features consistent with baryon acoustic oscillations around 100 Mpc/h and show redshift-space distortion (RSD) effects that agree well with predictions from a non-linear alignment model incorporating RSD. We further demonstrate that the structure growth rate parameter can be robustly estimated without bias from these IA correlations, providing a new avenue for cosmological parameter estimation. Expanding the IA correlations in an associated Legendre basis yields results consistent with those from the standard Legendre expansion, but with improved statistical significance. These results suggest that SHAPE may enhance cosmological parameter constraints in future galaxy surveys.

astro-ph.CO↗

arXiv2025

Inner structure of cold and warm dark matter halos from particle dynamics

Using the number of apocenter passages $p$ and the radial action $J_r$ of each particle, we characterize the phase-space structure within the multi-stream regions of cold and warm dark matter halos in cosmological $N$-body simulations. Building on previous work by Enomoto et al. (2024), we analyze the radial density profiles of particles classified by $p$ and $J_r$. We find that the profiles consistently follow a double power-law structure, independent of the dark matter model or halo mass. The inner profile exhibits a $ρ\propto r^{-1}$ behavior, which is consistent with previous studies. Notably, this characteristics persist across both classification schemes. In contrast, the outer power-law profiles display distinct behaviors depending on the classification. While particles classified by $p$ exhibit a steeper slope, ranging from $-6$ to $-8$, those classified by $J_r$ follow a common slope of approximately $-3.5$. Overall, the amplitude of the double power-law profiles varies between simulations for different dark matter models, but this variation can be attributed to statistical differences in the concentration of halos across the models.

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arXiv2024

Taming redshift-space distortion effects in the EFTofLSS and its application to data

Former analyses of the BOSS data using the Effective Field Theory of Large-Scale Structure (EFTofLSS) have measured that the largest counterterms are the redshift-space distortion ones. This allows us to adjust the power-counting rules of the theory, and to explicitly identify that the leading next-order terms have a specific dependence on the cosine of the angle between the line-of-sight and the wavenumber of the observable, $μ$. Such a specific $μ$-dependence allows us to construct a linear combination of the data multipoles, $\slashed{P}$, where these contributions are effectively projected out, so that EFTofLSS predictions for $\slashed{P}$ have a much smaller theoretical error and so a much higher $k$-reach. The remaining data are organized in wedges in $μ$ space, have a $μ$-dependent $k$-reach because they are not equally affected by the leading next-order contributions, and therefore can have a higher $k$-reach than the multipoles. Furthermore, by explicitly including the highest next-order terms, we define a `one-loop+' procedure, where the wedges have even higher $k$-reach. We study the effectiveness of these two procedures on several sets of simulations and on the BOSS data. The resulting analysis has identical computational cost as the multipole-based one, but leads to an improvement on the determination of some of the cosmological parameters that ranges from $10\%$ to $100\%$, depending on the survey properties.

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arXiv2024

Dark matter halos of luminous AGNs from galaxy-galaxy lensing with the HSC Subaru Strategic Program

We assess the dark matter halo masses of luminous AGNs over the redshift range 0.2 to 1.2 using galaxy-galaxy lensing based on imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We measure the weak lensing signal of a sample of 48907 AGNs constructed using HSC and WISE photometry. %The lensing detection around AGNs has a signal to noise ratio of \textbf{29}. As expected, we find that the lensing mass profile of total AGN sample is consistent with that of massive galaxies ($\rm log(M_{*}/h^{-2}M_\odot)\sim$ 10.61). Surprisingly, the lensing signal remains unchanged when the AGN sample is split into four stellar mass bins of host galaxies. Specifically, we find that the excess surface density (ESD) of AGNs, residing in galaxies with high stellar masses, significantly differs from that of the control sample. We further fit a halo occupation distribution model to the data to infer the posterior distribution of parameters including the average halo mass. We find that the characteristic halo mass of the full AGN population lies near the knee ($\rm log(M_h/h^{-1}M_{\odot})=12.0$) of the stellar-to-halo mass relation (SHMR). Illustrative of the results given above, the halo masses of AGNs residing in host galaxies with high stellar masses (i.e., above the knee of the SHMR) falls below the calibrated SHMR while the halo mass of the low stellar mass sample is more consistent with the established SHMR. These results indicate that massive halos with higher clustering bias tends to suppress AGN activity, probably due to the lack of available gas.

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arXiv2024

Perturbation Theory Remixed II: Improved Modeling of Nonlinear Bispectrum

We present the application of the $n$-th order Eulerian Perturbation Theory ($n$EPT) for modeling the matter bispectrum in real space as an advancement over the Standard Perturbation Theory (SPT). The $n$EPT method, detailed in Wang et al. (2023) \cite{Wang2023nEPT}, sums up the density perturbations up to the $n$-th order before computing summary statistics such as bispectrum. Taking advantage of grid-based calculation of SPT (GridSPT), we make a realization-based comparison of the analytical nonlinear bispectrum predictions from $n$EPT and SPT against a suite of $N$-body simulations. Using a spherical-bispectrum visualization scheme, we show that $n$EPT bispectrum matches better than SPT bispectrum over a wide range of scales in general $w$CDM cosmologies. Like the power spectrum case, we find that $n$EPT bispectrum modeling accuracy is controlled by $σ_8(z) \equiv σ_8 D(z)$, where $D(z)$ is the linear growth factor at a redshift $z$. Notably, the 6EPT doubles the bispectrum model's validity range compared to the one-loop SPT for $σ_8(z) < 0.5$, corresponding to redshifts $z\ge1$ for the best-fitting Planck-2018 cosmology. For $n\ge5$, however, $n$EPT bispectrum depends sensitively on the cut-off scale or the grid resolution. The percent-level modeling accuracy achieved for the spherical bispectrum (where we average over all triangular configurations) becomes much degraded when fixing configurations. Thus, we show that the validity range of the field-level cosmological inferences must be different from that derived from averaged summary statistics such as $n$-point correlation functions.

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arXiv2024

KiDS-1000: Combined halo-model cosmology constraints from galaxy abundance, galaxy clustering and galaxy-galaxy lensing

We present constraints on the flat $Λ$CDM cosmological model through a joint analysis of galaxy abundance, galaxy clustering and galaxy-galaxy lensing observables with the Kilo-Degree Survey. Our theoretical model combines a flexible conditional stellar mass function, to describe the galaxy-halo connection, with a cosmological N-body simulation-calibrated halo model to describe the non-linear matter field. Our magnitude-limited bright galaxy sample combines 9-band optical-to-near-infrared photometry with an extensive and complete spectroscopic training sample to provide accurate redshift and stellar mass estimates. Our faint galaxy sample provides a background of accurately calibrated lensing measurements. We constrain the structure growth parameter $S_8=σ_8\sqrt{Ω_{\mathrm{m}}/0.3}=0.773^{+0.028}_{-0.030}$, and the matter density parameter $Ω_{\mathrm{m}}=0.290^{+0.021}_{-0.017}$. The galaxy-halo connection model adopted in the work is shown to be in agreement with previous studies. Our constraints on cosmological parameters are comparable to, and consistent with, joint $3\times2{\mathrm{pt}}$ clustering-lensing analyses that additionally include a cosmic shear observable. This analysis therefore brings attention to the significant constraining power in the often-excluded non-linear scales for galaxy clustering and galaxy-galaxy lensing observables. By adopting a theoretical model that accounts for non-linear halo bias, halo exclusion, scale-dependent galaxy bias and the impact of baryon feedback, this work demonstrates the potential and a way forward to include non-linear scales in cosmological analyses. Varying the width of the satellite galaxy distribution with an additional parameter yields a strong preference for sub-Poissonian variance, improving the goodness of fit by 0.18 in reduced $χ^{2}$ value compared to a fixed Poisson distribution.

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