arXiv subjects

Konrad Kuijken

Publications and source records attributed to Konrad Kuijken.

At least 19 recordsLinked to original sources

arXiv2026

The FLAMINGO Project: Exploring the X-ray--cosmic-shear cross-correlation as a probe of large-scale structure

Baryonic feedback processes associated with galaxy formation directly influence the large-scale structure by redistributing gas. Recent measurements of the kinetic Sunyaev-Zel'dovich effect and stacks of X-ray emission from optically selected galaxy clusters suggest that feedback from Active Galactic Nuclei (AGN) is more efficient at expelling gas from low-mass clusters than previously thought. The measurement of the cross-correlation between cosmic shear and diffuse X-ray emission provides a new probe of the distribution of gas in groups and clusters. We use the FLAMINGO cosmological, hydrodynamical simulations to examine the X-ray--cosmic-shear cross-correlation. The cross-correlation is most sensitive to the distribution of gas in haloes with masses $10^{14}\leq M_{200\mathrm{c}}/\mathrm{M}_{\odot}\leq10^{15}$. It is sensitive to the strength of feedback, but the effects of variations in cosmology and baryonic physics are largely degenerate. We compare the FLAMINGO predictions with the cross-correlation between cosmic shear from the Dark Energy Survey and ROSAT all-sky X-ray maps. We find that, if we neglect the X-ray emission from AGN that would remain unresolved by ROSAT, then the fiducial FLAMINGO model is in excellent agreement with the data, while models with stronger or weaker feedback are ruled out. However, if we account for unresolved AGN, either using the direct FLAMINGO predictions or by abundance matching to the observed (extrapolated) AGN luminosity function, then models with stronger feedback are preferred. We conclude that to exploit the potential of the X-ray--lensing cross-correlation, it will be necessary to resolve fainter AGN, and to use external constraints to break the degeneracy between baryonic feedback and cosmology.

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arXiv2026

Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks

Weak gravitational lensing (WL) peaks probe non-Gaussian information of the large-scale distribution of matter that is not captured by two-point lensing statistics. We study the cosmological potential of the height distribution, redshift distribution, and angular clustering of high-valued WL peaks using a Bayesian inference approach that mimics a $\textit{Euclid}$ analysis. We use a forthcoming dark-matter-only hypercube, which varies cosmology in a ten-dimensional space, including evolving dark energy, neutrino mass, decaying dark matter, and the running of the scalar spectral index. We find the individual WL peak statistics to be complementary, as the redshift distribution best constrains the matter density, $Ω_\mathrm{m}$, and the dark energy equation-of-state parameters, $w_0$, and $w_a$; the height distribution and angular clustering are most sensitive to the amplitude of the primordial power spectrum, $\ln(10^{10}A_\mathrm{s})$; while combining the three statistics allows us to also probe the baryon density, $Ω_\mathrm{b}$, and the Hubble parameter, $h$. A comparison to the shear two-point correlation function demonstrates that WL peaks alone outperform the commonly used statistics, while even tighter constraints are obtained when combining all. Considering the 2-dimensional $Ω_\mathrm{m}-\ln(10^{10}A_\mathrm{s})$ and $w_0-w_a$ parameter planes, we find that the redshift distribution outperforms the angular clustering and peak-height distributions. We study the impact of the smoothing scale and find that, typically, the smallest scales yield the best results and the figure of merit improves by a factor $\approx2$ when combining multiple scales.

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arXiv2026

KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions

Tomographic redshift distributions from photometric data are crucial ingredients in cosmic shear analysis, since they are required for the theoretical calculation of the signal based on the redshift distribution of the galaxies where the shear field is sampled. In this paper, we develop as a proof of concept Leistedt et al.'s template-based Bayesian Hierarchical Model framework into an application to weak lensing data by sampling the redshift distributions of the galaxies in the KiDS+VIKING-450 survey. We also use a principal component analysis to provide a set of representative templates drawn from a large superset. For computational tractability, subsets of $10^5$ galaxies are chosen to determine the redshift distributions, and we test the sensitivity of the cosmological inference to the subset chosen, finding it to be subdominant compared to the statistical error. We marginalise over the inferred redshift distributions and find that the Bayesian method increases the clustering parameter compared with previous studies, alleviating the $S_8$ tension with Planck, where $S_{8}\equivσ_{8}\sqrt{Ω_{\tm{m}}/0.3}=0.756\pm 0.039$, assuming flat $Λ$CDM. The tension with Planck for this survey is reduced from $2.3σ$ to $1.9σ$. We also infer a value for the matter density, $Ω_{\tm{m}}=0.31\pm 0.10$.

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arXiv2026

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 $Λ$-cold dark matter ($Λ$CDM) analysis with $c^2 \sum m_ν\leq 1.5\,$eV, $w_0 = -1.0\pm 0.7$, and $w_a = -1.3^{+1.9}_{-2.0}$ while $Ω_K = 0.08^{+0.16}_{-0.17}$ (1$σ$ bounds) with an almost equal goodness of fit. The $w_0w_a$CDM model is not a significant improvement over $Λ$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 $2.6σ$ suspiciousness tension. The constraint on $S_8 = σ_8\sqrt{Ω_\mathrm{m}/0.3}$ 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 $Λ$CDM and $S_8 = 0.837 \pm 0.008$ in $w_0 w_a$CDM for all probes combined.

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arXiv2026

Kinematically cold and warm planetary nebulae samples, HII regions and supernovae remnants in the disc of the face-on spiral galaxy NGC 628 (M74) -- The Planetary Nebulae Spectrograph with the H$α$ arm

We present the results for the galaxy NGC 628 observed with the Planetary Nebulae Spectrograph (PN.S) equipped with the H$α$ arm. With the third PN.S arm, the H$α$ arm, we measure the H$α$ fluxes, in addition to fluxes and line-of-sight velocities (LOSV) of monochromatic spatially unresolved [OIII] 5007Å sources. The narrow band color ([OIII] 5007Å-H$α$) vs m5007 magnitude diagram separates planetary nebulae (PNe) from single compact ionized HII regions and supernovae remnants (SNRs), which also emit in [OIII]5007 Å. The goals are to detect bona-fide PNe in the face-on spiral galaxy NGC 628 (M74) so that we can measure the velocity dispersion of the stars perpendicular to the main plane of the disc. This study validates the empirical selection criteria for PNe with the PN.S in star forming discs. We classified 442 PNe and 251 spatially isolated, unresolved HII regions: the PN.S with the H$α$ arm increased the number of known PNe by a factor 4. We find evidence for two kinematically distinct PN populations in the NGC 628 disc. The kinematically cold PN population dominates the PN luminosity function close to the bright cut-off magnitude, indicating that the PN massive, short-lived progenitors dominate the PNLF bright cut-off in NGC 628. The warmer PN component increasingly dominates at fainter magnitudes. The velocity dispersion orthogonal to the disc plane are σz,cold = 8.8 kms-1 and σz,warm =26.1 kms-1 respectively, over a range of radii 80 to 425 arcsec. These components contribute with the ratio 46% (cold) and 54% (warm). Once the velocity dispersion of the old component is matched with the population's scale height, the decomposition of the rotation curve for NGC 628 leads to a maximal disc, with the rotation of the baryonic component accounting for 78% of the total rotational velocity in NGC 628.

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arXiv2026

Improved photometric redshift estimations through self-organising map-based data augmentation

We introduce a framework for the enhanced estimation of photometric redshifts using Self-Organising Maps (SOMs). Our method projects galaxy Spectral Energy Distributions (SEDs) onto a two-dimensional map, identifying regions that are sparsely sampled by existing spectroscopic observations. These under-sampled areas are then augmented with simulated galaxies, yielding a more representative spectroscopic training dataset. To assess the efficacy of this SOM-based data augmentation in the context of the forthcoming Legacy Survey of Space and Time (LSST), we employ mock galaxy catalogues from the OpenUniverse2024 project and generate synthetic datasets that mimic the expected photometric selections of LSST after one (Y1) and ten (Y10) years of observation. We construct 501 degraded realisations by sampling galaxy colours, magnitudes, redshifts and spectroscopic success rates, in order to emulate the compilation of a wide array of realistic spectroscopic surveys. Augmenting the degraded mock datasets with simulated galaxies from the independent CosmoDC2 catalogues has markedly improved the performance of our photometric redshift estimates compared to models lacking this augmentation, particularly for high-redshift galaxies ($z_\mathrm{true} \gtrsim 1.5$). This improvement is manifested in notably reduced systematic biases and a decrease in catastrophic failures by up to approximately a factor of 2, along with a reduction in information loss in the conditional density estimations. These results underscore the effectiveness of SOM-based augmentation in refining photometric redshift estimation, thereby enabling more robust analyses in cosmology and astrophysics for the NSF-DOE Vera C. Rubin Observatory.

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arXiv2026

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, $ΔM_*^2\equiv M_*^2-1$, as model parameters, we constrain their present values to be $Δ\hat{M}_*^2=0.32^{+0.07}_{-0.21}$ and $\hat{D}_{\rm kin} = 3.74^{+0.69}_{-1.92}$, which deviate from general relativity at $1.5σ$ and $1.9σ$, respectively. We derive constraints on the structure growth parameter $S_8=0.813^{+0.008}_{-0.011}$, which is compatible with the $Λ$CDM constraint at $0.54σ$. We obtain the deviation of the effective Newtonian coupling from the GR value as $Δμ_{\infty,{\rm eff}}=0.066\pm0.023$, corresponding to a $2.9σ$ 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 $1.4σ$ level. When adopting a dynamical dark energy model of the background cosmology, the inferred modified gravity parameter constraints are stable with respect to a $Λ$CDM background, while a mild preference at $1.57σ$ for dynamical dark energy remains.

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arXiv2026

pop-cosmos: Forward modeling KiDS-1000 redshift distributions using realistic galaxy populations

The accuracy of the cosmological constraints from Stage~IV galaxy surveys will be limited by how well the galaxy redshift distributions can be inferred. We have addressed this challenging problem for the Kilo-Degree Survey (KiDS) cosmic shear sample by developing a forward-modeling framework with two main ingredients: (1) the \texttt{pop-cosmos} generative model for the evolving galaxy population, calibrated on \textit{Spitzer} IRAC $\textit{Ch.\,1}<26$ galaxies from COSMOS2020; and (2) a data model for noise and selection, machine-learned from the SURFS-based KiDS-Legacy-Like Simulations (SKiLLS). Applying KiDS tomographic binning to our synthetic photometric data, we infer redshift distributions in each of five bins directly from the population and data models, bypassing the need for spectroscopic reweighting. Keeping the data model fixed, we compare results using two different galaxy population models: \texttt{pop-cosmos}; and \texttt{shark}, the semi-analytic galaxy formation model used in SKiLLS. In the first ($0.1<z<0.3$) and last ($0.9<z<1.2$) tomographic bins we find systematic differences in the mean redshifts of $Δz\sim0.05$-$0.1$, comparable to the reported uncertainties from spectroscopic reweighting methods. This work paves the way for accurate redshift distribution calibration for Stage~IV surveys directly through forward modeling, thus providing an independent cross-check on spectroscopic-based calibrations which avoids their selection biases and incompleteness. We will use the \texttt{pop-cosmos} redshift distributions in an upcoming full KiDS cosmology reanalysis.

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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 $S_8\equivσ_8\sqrt{Ω_{\rm m}/0.3} = 0.815^{+0.016}_{-0.021}$, is found to be in agreement ($0.73σ$) 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 $Σ_8\equivσ_8\left(Ω_{\rm m}/0.3\right)^α= 0.821^{+0.014}_{-0.016}$, where $α= 0.58$ has been optimised to match the revised degeneracy direction of $σ_8$ and $Ω_{\rm m}$. 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 Stölzner 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 $2σ$ in all tomographic bins.

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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 $S_8\equiv σ_8\sqrt{Ω_{\rm m}/0.3} = 0.814^{+0.011}_{-0.012}$ and $σ_8 = 0.802^{+0.022}_{-0.018}$.

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arXiv2025

Matter power spectrum reconstruction with KiDS-Legacy: Improved internal $Λ$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 $Λ$CDM predictions with a density fluctuation amplitude $σ_8=0.81$. 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 $2.8σ$ significance relative to a dark-matter-only model, consistent with expectations of strong baryonic feedback.

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arXiv2025

KiDS-1000 cosmic shear reanalysis using MetaCalibration

A number of cosmic shear studies have reported results that are in mild tension with the Planck cosmic microwave measurement. To explore if this can be caused by biases in the shear estimation, we revisit the analysis of data from the Kilo-Degree Survey (KiDS) using an alternative shape measurement pipeline that is more robust to uncertainties in the calibration. To this end, we present an implementation of MetaCalibration, and compare its performance to that of lensfit, which has been used in previous analyses of these data. We find that the multiplicative bias is reduced, especially for the most distant redshifts, as derived from multi-band image simulations designed to match the KiDS data (SURFS-based KiDS-Legacy-Like Simulations: SKiLLS). For all tomographic bins we obtain a multiplicative bias $|m|<0.017$, with negligible additive bias. Importantly, the calibration has a negligible sensitivity to key galaxy properties. The resulting robust shear estimates were used to obtain cosmological parameter constraints. We find that the parameter $S_8\equiv σ_8 \sqrt{Ω_\mathrm{m}/0.3} =0.789_{-0.024}^{+0.020}$ is consistent with the previous KiDS-1000 lensfit constraint of $S_8=0.776^{+0.029 +0.002}_{-0.027-0.003}$ (statistical + systematic errors). Thanks to the higher effective source density, the constraining power is improved by about 28%. The difference in $S_8$ with the Planck value remains at a similar level, 1.8$σ$, implying that it is not caused by the shear measurements.

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arXiv2025

Using Deep Learning Methods to Detect for Ultra-diffuse Galaxies in KiDS

Ultra-diffuse Galaxies (UDGs) are a subset of Low Surface Brightness Galaxies (LSBGs), showing mean effective surface brightness fainter than $24\ \rm mag\ \rm arcsec^{-2}$ and a diffuse morphology, with effective radii larger than 1.5 kpc. Due to their elusiveness, traditional methods are challenging to be used over large sky areas. Here we present a catalog of ultra-diffuse galaxy (UDG) candidates identified in the full 1350 deg$^2$ area of the Kilo-Degree Survey (KiDS) using deep learning. In particular, we use a previously developed network for the detection of low surface brightness systems in the Sloan Digital Sky Survey \citep[LSBGnet,][]{su2024lsbgnet} and optimised for UDG detection. We train this new UDG detection network for KiDS (UDGnet-K), with an iterative approach, starting from a small-scale training sample. After training and validation, the UGDnet-K has been able to identify $\sim3300$ UDG candidates, among which, after visual inspection, we have selected 545 high-quality ones. The catalog contains independent re-discovery of previously confirmed UDGs in local groups and clusters (e.g NGC 5846 and Fornax), and new discovered candidates in about 15 local systems, for a total of 67 {\it bona fide} associations. Besides the value of the catalog {\it per se} for future studies of UDG properties, this work shows the effectiveness of an iterative approach to training deep learning tools in presence of poor training samples, due to the paucity of confirmed UDG examples, which we expect to replicate for upcoming all-sky surveys like Rubin Observatory, Euclid and the China Space Station Telescope.

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arXiv2025

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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arXiv2025

Weak lensing constraints on the stellar-to-halo mass relation of galaxy groups with simulation-informed scatter

Understanding the scaling relation between baryonic observables and dark matter halo properties is crucial not only for studying galaxy formation and evolution, but also for deriving accurate cosmological constraints from galaxy surveys. In this paper, we constrain the stellar-to-halo mass relation of galaxy groups identified by the Galaxy and Mass Assembly survey, using weak lensing signals measured by the Kilo-Degree Survey. We compare our measured scaling relation with predictions from the FLAMINGO hydrodynamical simulations and the L-Galaxies semi-analytical model. We find a general agreement between our measurements and simulation predictions for halos with masses ${\gtrsim}10^{13.5}\ h_{70}^{-1}{\rm M}_{\odot}$, but observe slight discrepancies with the FLAMINGO simulations at lower halo masses. We explore improvements to the current halo model framework by incorporating simulation-informed scatter in the group stellar mass distribution as a function of halo mass. We find that including a simulation-informed scatter model tightens the constraints on scaling relations, despite the current data statistics being insufficient to directly constrain the variable scatter. We also test the robustness of our results against different statistical models of miscentring effects from selected central galaxies. We find that accounting for miscentring is essential, but our current measurements do not distinguish among different miscentring models.

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arXiv2025

Prospects for radio weak lensing: studies using LOFAR observations in the ELAIS-N1 field

We carry out a shape and weak lensing analysis of Low Frequency Array (LOFAR) radio sources and Hyper Suprime-Cam (HSC) optical sources within the European Large Area Infrared Space Observatory Survey-North 1 (ELAIS-N1) field. Using HSC data alone, we detect a cosmic shear correlation signal at a significance of $\sim$$9σ$ over a $\sim$$6.4$ deg$^2$ region. For the radio dataset, we analyse observations from both the LOFAR Two Metre Sky Survey (LoTSS) and the International LOFAR Telescope (ILT). While LoTSS provides the deepest radio imaging of ELAIS-N1 with a central source density of $\sim$2.7 arcmin$^{-2}$, its $6^{\prime\prime}$ resolution limits the accuracy of shape measurements. But, using LoTSS-matched HSC sources, we show that accurate radio shape measurements would enable us to measure the amplitude of the shear correlation function at least at $\sim$2$σ$ significance. In contrast, ILT observation of the field offers a superior $0.3^{\prime\prime}$ resolution. By cross-matching HSC and ILT samples, we measure a position angle correlation of $R_{\cos(2α)} = 0.15 \pm 0.02$. This result highlights ILT's ability to resolve extended and diffuse emission. The current ILT observations lack the required depth for robust weak lensing measurements. To assess the potential of ILT, we use simulated data with increased observation hours. Our analysis indicates that with 3200 hours of ILT observations or deeper data, and assuming that statistical errors dominate over systematics, a shear correlation could be detected with moderate significance. To achieve this will require precise radio shear measurements and effective mitigation of point spread function (PSF) systematics.

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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 $Λ\rm CDM$ 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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