arXiv subjects

Lucas Porth

Publications and source records attributed to Lucas Porth.

At least 19 recordsLinked to original sources

arXiv2026

Fourth-order galaxy-galaxy-lensing: Theoretical framework and direct estimation

Traditional galaxy-galaxy lensing is a well-established method of probing the statistical properties of the Universe's matter and galaxy distribution. However, this measure does not carry all the statistical information, provided the matter and galaxy distribution contain non-Gaussian features. In order to study these non-Gaussianities, it is necessary to consider higher-order statistical measures. The aim of this work is to extend the analytical basis describing the statistical correlations between galaxies and shear to the fourth order, with special emphasis on the associated aperture statistics. In order to include fourth-order statistics in future analysis of the relation between mass and galaxies, we further investigate whether we can expect to detect these statistics from observations of stage IV surveys. We define the four-point correlation function (4PCF) between the shear and the positions of triplets of foreground galaxies and derive its relation to the respective trispectrum. We convert the 4PCF to aperture statistics and derive the analytical form of the respective filter function, which we then implement in a numerical integration pipeline. Furthermore, we develop a direct estimator that allows us to measure galaxy-mass aperture moments of arbitrary order on pixelized data using a Fast-Fourier-Transform (FFT) algorithm. We show that the corresponding aperture measure $\langle\mathcal{N}^3 M_\mathrm{ap}\rangle$ can be calculated with sub-percent accuracy on relevant aperture scales, $\theta$, by means of numerical integration. Furthermore, we apply the FFT-based direct estimator to a mock catalog with a realistic stage IV survey setup on a sky area of $2000~\mathrm{deg}^2$, and detect the connected part of the aperture statistics $\langle\mathcal{N}^3 M_\mathrm{ap}\rangle(\theta)$ with a signal-to-noise ratio of roughly nine on small aperture scales.

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arXiv2025

KiDS-Legacy: Constraints on Horndeski gravity from weak lensing combined with galaxy clustering and cosmic microwave background anisotropies

We present constraints on modified gravity from a cosmic shear analysis of the final data release of the Kilo-Degree Survey (KiDS-Legacy) in combination with DESI measurements of baryon acoustic oscillations, eBOSS observations of redshift space distortions, and cosmic microwave background anisotropies from Planck. We study the Horndeski class of modified gravity models in an effective field theory framework employing a parameterisation that satisfies stability conditions by construction and, for the first time, present a cosmological analysis in this inherently stable parameter basis. Cosmic shear constrains the Horndeski parameter space significantly, matching or surpassing the CMB contribution. Adopting the de-mixed kinetic term of the scalar field perturbation, $D_{\rm kin}$, and the deviation of the Planck mass from its fiducial value, $\Delta M_*^2\equiv M_*^2-1$, as model parameters, we constrain their present values to be $\Delta \hat{M}_*^2=0.32^{+0.07}_{-0.21}$ and $\hat{D}_{\rm kin} = 3.74^{+0.69}_{-1.92}$, which deviate from general relativity at $1.5\sigma$ and $1.9\sigma$, respectively. We derive constraints on the structure growth parameter $S_8=0.813^{+0.008}_{-0.011}$, which is compatible with the $\Lambda$CDM constraint at $0.54\sigma$. We obtain the deviation of the effective Newtonian coupling from the GR value as $\Delta \mu_{\infty,{\rm eff}}=0.066\pm0.023$, corresponding to a $2.9\sigma$ significance. Although modified gravity provides a slightly better fit to the data, a model comparison shows only a weak preference for modified gravity at the $1.4\sigma$ level. When adopting a dynamical dark energy model of the background cosmology, the inferred modified gravity parameter constraints are stable with respect to a $\Lambda$CDM background, while a mild preference at $1.57\sigma$ for dynamical dark energy remains.

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arXiv2025

KiDS-Legacy: Constraining dark energy, neutrino mass, and curvature

We constrained minimally extended cosmological models with the cosmic shear analysis of the final data release from the Kilo-Degree Survey (KiDS-Legacy) in combination with external probes. Due to the consistency of the KiDS-Legacy analysis with the cosmic microwave background (CMB), we could combine these datasets reliably for the first time. Additionally, we used CMB lensing, galaxy redshift-space distortions, and baryon acoustic oscillations. We assessed, in turn, the effects of spatial curvature, varying neutrino masses, and an evolving dark energy component on cosmological constraints from KiDS-Legacy alone and from KiDS-Legacy combined with external probes. We find KiDS-Legacy to be consistent with the fiducial flat $\Lambda$-cold dark matter ($\Lambda$CDM) analysis with $c^2 \sum m_\nu\leq 1.5\,$eV, $w_0 = -1.0\pm 0.7$, and $w_a = -1.3^{+1.9}_{-2.0}$ while $\Omega_K = 0.08^{+0.16}_{-0.17}$ (1$\sigma$ bounds) with an almost equal goodness of fit. The $w_0w_a$CDM model is not a significant improvement over $\Lambda$CDM when cosmic shear and CMB lensing are combined, yielding a Bayes factor $B = 0.07$. If all probes are combined, however, $B$ increases to 2.73, corresponding to a $2.6\sigma$ suspiciousness tension. The constraint on $S_8 = \sigma_8\sqrt{\Omega_\mathrm{m}/0.3}$ is robust to opening up the parameter space for cosmic shear. Adding all external datasets to KiDS-Legacy, we find $S_8 = 0.816 \pm 0.006$ in $\Lambda$CDM and $S_8 = 0.837 \pm 0.008$ in $w_0 w_a$CDM for all probes combined.

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arXiv2025

A roadmap to cosmological parameter analysis with third-order shear statistics IV. Analytic cross-covariance between second- and third-order aperture masses

Weak gravitational lensing is a powerful probe of cosmology, with second-order shear statistics commonly used to constrain parameters such as the matter density $\Omega_\mathrm{m}$ and the clustering amplitude $S_8$. However, parameter degeneracies remain and can be reduced by including higher-order statistics such as the third-order aperture mass. To jointly analyse second- and third-order statistics, an accurate model of their cross-covariance is essential. We derive and validate a non-tomographic analytical model for the cross-covariance between second- and third-order aperture mass statistics. Analytical models are computationally efficient and enable cosmological parameter inference across a range of models, in contrast to numerical covariances derived from simulations or resampling, which are costly or biased. Our derivation is based on real-space estimators of the aperture mass. Substituting the Halofit power spectrum, BiHalofit bispectrum, and a halo-model tetraspectrum, we validate the model against numerical covariances from the $N$-body Scinet LIghtCone Simulations (SLICS) using shear catalogues and convergence maps. We perform a Markov chain Monte Carlo analysis with both analytical and numerical covariances for several filter scale combinations. The cross-covariance separates into three terms governed by the power spectrum, bispectrum, and tetraspectrum, with the latter dominating. The analytical model qualitatively reproduces simulations, though differences arise from modelling approximations and numerical evaluation. Analytical contours are systematically tighter, with a combined figure of merit 72% of the numerical case, rising to 80% when small-scale information is excluded. This work completes the analytical covariance framework for second- and third-order aperture mass statistics, enabling joint parameter inference without large simulation suites.

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arXiv2025

Matter power spectrum reconstruction with KiDS-Legacy: Improved internal $\Lambda$CDM consistency and preference for strong baryonic feedback

Direct measurements of the matter power spectrum, $P_\mathrm{m}(k,z)$, provide a powerful tool to investigate observed tensions between models of structure growth while also testing the internal consistency of cosmological probes. We analyse cosmic shear data from the final data release of the Kilo-Degree Survey (KiDS), presenting a deprojected $P_\mathrm{m}(k,z)$, measured in up to three redshift bins. Compared to analyses using previous KiDS releases, we find improved internal consistency in the $z\lesssim0.7$ regime. At large scales, $k\lesssim0.1\,h\,\rm Mpc^{-1}$, our power spectrum reconstruction aligns with $\Lambda$CDM predictions with a density fluctuation amplitude $\sigma_8=0.81$. Furthermore, at small scales, $k=3$-$20\,h\,\rm Mpc^{-1}$, the average matter power spectrum is suppressed by $30\%\pm10\%\,{\rm (stat.)}\pm4\%\,{\rm (sys.)}$ with $2.8\sigma$ significance relative to a dark-matter-only model, consistent with expectations of strong baryonic feedback.

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arXiv2025

Towards an application of fourth-order shear statistics II: Efficient estimation of fourth-order shear correlation functions and an application to the DES Y3 data

Higher-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. Stage-III lensing surveys have sufficient statistical power to significantly detect cumulant-based statistics up to fourth order. We derive and validate an efficient estimation procedure for the four-point correlation function (4PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 4PCF and the fourth-order aperture mass statistics in the DES Y3 survey. We construct an efficient estimator for fourth-order shear statistics which builds on the multipole decomposition of the shear 4PCF. We then validate our estimator on mock ellipticity catalogues obtained from Gaussian random fields and on realistic $N$-body simulations. Finally, we apply our estimator to the DES Y3 data and present a measurement of the fourth-order aperture statistics in a non-tomographic setup. Due to its quadratic scaling, our estimator provides a significant speed-up over hypothetical brute force or tree-based estimation methods of the shear 4PCF. We report a significant detection of the connected part of the fourth-order aperture mass in the DES Y3 data. We find the sampling distribution of the fourth-order aperture mass to be significantly skewed. We make our estimator code available on GitHub as part of the orpheus package.

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arXiv2025

Towards an application of fourth-order shear statistics I. The information content of $\langle M_\mathrm{ap}^4 \rangle $

Higher-order shear statistics contain part of the non-Gaussian information of the projected matter field and therefore can provide additional constraints on the cosmological parameters when combined with second-order statistics. We aim to provide the theoretical framework for studying shear four-point correlation functions (4PCF) using fourth-order aperture statistics and develop a numerical integration pipeline to compute them. Finally, we forecast the information content of fourth-order aperture statistics. We begin by giving the relation of the $n$-th order aperture statistics, $\langle M_\mathrm{ap}^n\rangle$, to the shear $n$PCF and to the convergence polyspectra. We then focus on the fourth-order case, where we derive the functional form of their filters and test the behavior of these filters by numerically integrating over the 4PCF of a Gaussian random shear field (GRF). Finally, we perform a Fisher forecast on the constraining power of $\langle M_\mathrm{ap}^4\rangle_\rm{c}$, where we develop a novel method to estimate derivatives from a simulation suite with arbitrarily distributed cosmological sets. By analyzing and mitigating numerical effects within the integration pipeline, we achieve a two-percent-level precision on the fourth-order aperture statistics for a GRF, which remains well below the noise budget of Stage IV surveys. We report a minimal improvement in the constraining power of the aperture statistics when including fourth-order statistics to a $\langle M_\mathrm{ap}^2\rangle + \langle M_\mathrm{ap}^3\rangle$ joint analysis for a DES-Y3-like setup, using non-tomographic equal-scale aperture statistics.

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arXiv2025

The fifth data release of the Kilo Degree Survey: Multi-epoch optical/NIR imaging covering wide and legacy-calibration fields

We present the final data release of the Kilo-Degree Survey (KiDS-DR5), a public European Southern Observatory (ESO) wide-field imaging survey optimised for weak gravitational lensing studies. We combined matched-depth multi-wavelength observations from the VLT Survey Telescope and the VISTA Kilo-degree INfrared Galaxy (VIKING) survey to create a nine-band optical-to-near-infrared survey spanning $1347$ deg$^2$. The median $r$-band $5\sigma$ limiting magnitude is 24.8 with median seeing $0.7^{\prime\prime}$. The main survey footprint includes $4$ deg$^2$ of overlap with existing deep spectroscopic surveys. We complemented these data in DR5 with a targeted campaign to secure an additional $23$ deg$^2$ of KiDS- and VIKING-like imaging over a range of additional deep spectroscopic survey fields. From these fields, we extracted a catalogue of $126\,085$ sources with both spectroscopic and photometric redshift information, which enables the robust calibration of photometric redshifts across the full survey footprint. In comparison to previous releases, DR5 represents a $34\%$ areal extension and includes an $i$-band re-observation of the full footprint, thereby increasing the effective $i$-band depth by $0.4$ magnitudes and enabling multi-epoch science. Our processed nine-band imaging, single- and multi-band catalogues with masks, and homogenised photometry and photometric redshifts can be accessed through the ESO Archive Science Portal.

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arXiv2025

KiDS-Legacy: Consistency of cosmic shear measurements and joint cosmological constraints with external probes

We present a cosmic shear consistency analysis of the final data release from the Kilo-Degree Survey (KiDS-Legacy). By adopting three tiers of consistency metrics, we compare cosmological constraints between subsets of the KiDS-Legacy dataset split by redshift, angular scale, galaxy colour and spatial region. We also review a range of two-point cosmic shear statistics. With the data passing all our consistency metric tests, we demonstrate that KiDS-Legacy is the most internally consistent KiDS catalogue to date. In a joint cosmological analysis of KiDS-Legacy and DES Y3 cosmic shear, combined with data from the Pantheon+ Type Ia supernovae compilation and baryon acoustic oscillations from DESI Y1, we find constraints consistent with Planck measurements of the cosmic microwave background with $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.814^{+0.011}_{-0.012}$ and $\sigma_8 = 0.802^{+0.022}_{-0.018}$.

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arXiv2025

KiDS-Legacy: Cosmological constraints from cosmic shear with the complete Kilo-Degree Survey

We present cosmic shear constraints from the completed Kilo-Degree Survey (KiDS), where the cosmological parameter $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.815^{+0.016}_{-0.021}$, is found to be in agreement ($0.73\sigma$) with results from the Planck Legacy cosmic microwave background experiment. The final KiDS footprint spans $1347$ square degrees of deep nine-band imaging across the optical and near-infrared, along with an extra $23$ square degrees of KiDS-like calibration observations of deep spectroscopic surveys. Improvements in our redshift distribution estimation methodology, combined with our enhanced calibration data and multi-band image simulations, allow us to extend our lensed sample out to a photometric redshift of $z_{\rm B}\leq2.0$. Compared to previous KiDS analyses, the increased survey area and redshift depth results in a $\sim32\%$ improvement in constraining power in terms of $\Sigma_8\equiv\sigma_8\left(\Omega_{\rm m}/0.3\right)^\alpha = 0.821^{+0.014}_{-0.016}$, where $\alpha = 0.58$ has been optimised to match the revised degeneracy direction of $\sigma_8$ and $\Omega_{\rm m}$. We adopt a new physically motivated intrinsic alignment model that depends jointly on the galaxy sample's halo mass and spectral type distributions, and that is informed by previous direct alignment measurements. We also marginalise over our uncertainty on the impact of baryon feedback on the non-linear matter power spectrum. Comparing to previous KiDS analyses, we conclude that the increase seen in $S_8$ primarily results from our improved redshift distribution estimation and calibration, as well as new survey area and improved image reduction. Our companion paper St\"olzner et al. (submitted) presents a full suite of internal and external consistency tests, finding the KiDS-Legacy data set to be the most internally robust sample produced by KiDS to date.

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arXiv2025

KiDS-Legacy: Redshift distributions and their calibration

We present the redshift calibration methodology and bias estimates for the cosmic shear analysis of the fifth and final data release (DR5) of the Kilo-Degree Survey (KiDS). KiDS-DR5 includes a greatly expanded compilation of calibrating spectra, drawn from $27$ square degrees of dedicated optical and near-IR imaging taken over deep spectroscopic fields. The redshift distribution calibration leverages a range of new methods and updated simulations to produce the most precise $N(z)$ bias estimates used by KiDS to date. Improvements to our colour-based redshift distribution measurement method (SOM) mean that we are able to use many more sources per tomographic bin for our cosmological analyses, and better estimate the representation of our source sample given the available spec-$z$. We validate our colour-based redshift distribution estimates with spectroscopic cross-correlations (CC). We find that improvements to our cross-correlation redshift distribution measurement methods mean that redshift distribution biases estimated between the SOM and CC methods are fully consistent on simulations, and the data calibration is consistent to better than $2\sigma$ in all tomographic bins.

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arXiv2025

KiDS-1000: Detection of deviations from a purely cold dark matter power spectrum with tomographic weak gravitational lensing

Model uncertainties in the non-linear structure growth limit current probes of cosmological parameters. To shed more light on the physics of non-linear scales, we reconstructed the finely binned three-dimensional power-spectrum from lensing data of the Kilo-Degree Survey (KiDS), relying solely on the background cosmology, the source redshift distributions, and the intrinsic alignment (IA) amplitude of sources (and their uncertainties). The adopted Tikhonov regularisation stabilises the deprojection, enabling a Bayesian reconstruction in separate $z$-bins. Following a detailed description of the algorithm and performance tests with mock data, we present our results for the power spectrum as relative deviations from a $\Lambda\rm CDM$ reference spectrum that includes only structure growth by cold dark matter. Averaged over the full range $z\lesssim1$, a \emph{Planck}-consistent reference then requires a significant suppression on non-linear scales, $k=0.05$--$10\,h\,\rm Mpc^{-1}$, of up to $20\%$--$30\%$ to match KiDS-1000 ($68\%$ credible interval, CI). Conversely, a reference with a lower $S_8\approx0.73$ avoids suppression and matches the KiDS-1000 spectrum within a $20\%$ tolerance. When resolved into three $z$-bins, however, and regardless of the reference, we detect structure growth only in the range $z\approx0.4$--$0.13$, but not in the range $z\approx0.7$--$0.4$. This could indicate spurious systematic errors in KiDS-1000, inaccuracies in the intrinsic alignment (IA) model, or potentially a non-standard cosmological model with delayed structure growth. In the near future, analysing data from Stage IV surveys with our algorithm promises a substantially more precise reconstruction of the power spectrum.

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arXiv2024

KiDS-Legacy: Covariance validation and the unified OneCovariance framework for projected large-scale structure observables

We introduce OneCovariance, an open-source software designed to accurately compute covariance matrices for an arbitrary set of two-point summary statistics across a variety of large-scale structure tracers. Utilising the halo model, we estimated the statistical properties of matter and biased tracer fields, incorporating all Gaussian, non-Gaussian, and super-sample covariance terms. The flexible configuration permits user-specific parameters, such as the complexity of survey geometry, the halo occupation distribution employed to define each galaxy sample, or the form of the real-space and/or Fourier space statistics to be analysed. We illustrate the capabilities of OneCovariance within the context of a cosmic shear analysis of the final data release of the Kilo-Degree Survey (KiDS-Legacy). Upon comparing our estimated covariance with measurements from mock data and calculations from independent software, we ascertain that OneCovariance achieves accuracy at the per cent level. When assessing the impact of ignoring complex survey geometry in the cosmic shear covariance computation, we discover misestimations at approximately the $10\%$ level for cosmic variance terms. Nonetheless, these discrepancies do not significantly affect the KiDS-Legacy recovery of cosmological parameters. We derive the cross-covariance between real-space correlation functions, bandpowers, and COSEBIs, facilitating future consistency tests among these three cosmic shear statistics. Additionally, we calculate the covariance matrix of photometric-spectroscopic galaxy clustering measurements, validating the jackknife covariance estimates for calibrating KiDS-Legacy redshift distributions. The OneCovariance can be found on GitHub, together with comprehensive documentation and examples.

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arXiv2024

6x2pt: Forecasting gains from joint weak lensing and galaxy clustering analyses with spectroscopic-photometric galaxy cross-correlations

We explore the enhanced self-calibration of photometric galaxy redshift distributions, $n(z)$, through the combination of up to six two-point functions. Our $\rm 3\times2pt$ configuration is comprised of photometric shear, spectroscopic galaxy clustering, and spectroscopic-photometric galaxy-galaxy lensing (GGL). We further include spectroscopic-photometric cross-clustering; photometric GGL; and photometric auto-clustering, using the photometric shear sample as density tracer. We perform simulated likelihood forecasts of the cosmological and nuisance parameter constraints for Stage-III- and Stage-IV-like surveys. For the Stage-III-like case, we employ realistic but perturbed redshift distributions, and distinguish between "coherent" shifting in one direction, versus more internal scattering and full-shape errors. For perfectly known $n(z)$, a $\rm 6\times2pt$ analysis gains $\sim40\%$ in Figure of Merit (FoM) in the $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ and $\Omega_{\rm m}$ plane relative to the $\rm 3\times2pt$ analysis. If untreated, coherent and incoherent redshift errors lead to inaccurate inferences of $S_8$ and $\Omega_{\rm m}$, respectively. Employing bin-wise scalar shifts $\delta{z}_i$ in the tomographic mean redshifts reduces cosmological parameter biases, with a $\rm 6x2pt$ analysis constraining the shift parameters with $2-4$ times the precision of a photometric $\rm 3^{ph}\times2pt$ analysis. For the Stage-IV-like survey, a $\rm 6\times2pt$ analysis doubles the FoM($\sigma_8{-}\Omega_{\rm m}$) compared to any $\rm 3\times2pt$ or $\rm 3^{ph}\times2pt$ analysis, and is only $8\%$ less constraining than if the $n(z)$ were perfectly known. A Gaussian mixture model for the $n(z)$ reduces mean-redshift errors and preserves the $n(z)$ shape. It also yields the most accurate and precise cosmological constraints for any $N\rm\times2pt$ configuration given $n(z)$ biases.

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arXiv2023

KiDS-1000 cosmology: Combined second- and third-order shear statistics

This paper performs the first cosmological parameter analysis of the KiDS-1000 data with second- and third-order shear statistics. This work builds on a series of papers that describe the roadmap to third-order shear statistics. We derive and test a combined model of the second-order shear statistic, namely the COSEBIs and the third-order aperture mass statistics $\langle M_\mathrm{ap}^3\rangle$ in a tomographic set-up. We validate our pipeline with $N$-body simulations that mock the fourth Kilo Degree survey data release. To model the second- and third-order statistics, we use the latest version of \textsc{HMcode2020} for the power spectrum and \textsc{BiHalofit} for the bispectrum. Furthermore, we use an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering for the $\langle M_\mathrm{ap}^3\rangle$ part of the data vector only equal smoothing radii, making a data analysis of the fourth Kilo Degree survey data release using a combined analysis of COSEBIs third-order shear statistic possible. We first validate the accuracy of our modelling by analysing a noise-free mock data vector assuming the KiDS-1000 error budget, finding a shift in the maximum-a-posterior of the matter density parameter $\Delta \Omega_m< 0.02\, \sigma_{\Omega_m}$ and of the structure growth parameter $\Delta S_8 < 0.05\, \sigma_{S_8}$. Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained $\Omega_m=0.248^{+0.062}_{-0.055}$ and $S_8=\sigma_8\sqrt{\Omega_m/0.3}=0.772\pm0.022$. The geometric average on the errors of $\Omega_\mathrm{m}$ and $S_8$ of the combined statistics increased compared to the second-order statistic by 2.2.

astro-ph.CO↗

arXiv2023

A roadmap to cosmological parameter analysis with third-order shear statistics III: Efficient estimation of third-order shear correlation functions and an application to the KiDS-1000 data

Third-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. However, the computational effort for estimating such statistics on forthcoming stage IV surveys is prohibitively expensive. We derive and validate an efficient estimation procedure for the three-point correlation function (3PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 3PCF and the third-order aperture mass statistics on the KiDS-1000 survey. We construct an efficient estimator for third-order shear statistics which builds on the multipole decomposition of the 3PCF. We then validate our estimator on mock ellipticity catalogs obtained from $N$-body simulations. Finally, we apply our estimator to the KiDS-1000 data and present a measurement of the third-order aperture statistics in a tomographic setup. Our estimator provides a speedup of a factor of $\sim$ 100-1000 compared to the state-of-the-art estimation procedures. It is also able to provide accurate measurements for squeezed and folded triangle configurations without additional computational effort. We report a significant detection of the tomographic third-order aperture mass statistics in the KiDS-1000 data $(\mathrm{S/N}=6.69)$. Our estimator will make it computationally feasible to measure third-order shear statistics in forthcoming stage IV surveys. Furthermore, it can be used to construct empirical covariance matrices for such statistics.

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arXiv2023

What is the super-sample covariance? A fresh perspective for second-order shear statistics

Cosmological analyses of second-order weak lensing statistics require precise and accurate covariance estimates. These covariances are impacted by two sometimes neglected terms: A negative contribution to the Gaussian covariance due to finite survey area and the super-sample covariance (SSC) which for the power spectrum contains the impact by Fourier modes larger than the survey window. We show here that these two effects are connected and can be seen as correction terms to the "large-field-approximation", the asymptotic case of an infinitely large survey area. We describe the two terms collectively as "Finite-Field-Terms". We derive the covariance of second-order shear statistics from first principles. For this, we use an estimator in real space without relying on an estimator for the power spectrum. The resulting covariance does not scale inversely with the survey area, as naively assumed. This scaling is only correct under the large-field approximation when the contribution of the finite-field terms tends to zero. Furthermore, all parts of the covariance, not only the SSC, depend on the power- and trispectrum at all modes, including those larger than the survey. We also show that it is generally impossible to transform an estimate for the power spectrum covariance into the covariance of a real-space statistic. Such a transformation is only possible in the asymptotic case of the "large-field approximation". Additionally, we find that the total covariance of a real-space statistic can be calculated using correlation functions estimates on spatial scales smaller than the survey window. Consequently, estimating covariances of real-space statistics, in principle, does not require information on spatial scales larger than the survey area. We demonstrate that this covariance estimation method is equivalent to the standard sample covariance method.

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arXiv2022

The Information Content of Projected Galaxy Fields

The power spectrum of the nonlinearly evolved large-scale mass distribution recovers only a minority of the information available on the mass fluctuation amplitude. We investigate the recovery of this information in 2D "slabs" of the mass distribution averaged over $\approx100$~$h^{-1}$Mpc along the line of sight, as might be obtained from photometric redshift surveys. We demonstrate a Hamiltonian Monte Carlo (HMC) method to reconstruct the non-Gaussian mass distribution in slabs, under the assumption that the projected field is a point-transformed Gaussian random field, Poisson-sampled by galaxies. When applied to the \textit{Quijote} $N$-body suite at $z=0.5$ and at a transverse resolution of 2~$h^{-1}$Mpc, the method recovers $\sim 30$ times more information than the 2D power spectrum in the well-sampled limit, recovering the Gaussian limit on information. At a more realistic galaxy sampling density of $0.01$~$h^3$Mpc$^{-3}$, shot noise reduces the information gain to a factor of 5 improvement over the power spectrum at resolutions of 4~$h^{-1}$Mpc or smaller.

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