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Benjamin Joachimi

Publications and source records attributed to Benjamin Joachimi.

At least 91 records · Page 5Linked to original sources

Target Neutrino Mass Precision for Determining the Neutrino Hierarchy

Recent works combining neutrino oscillation and cosmological data to determine the neutrino hierarchy found a range of odds in favour of the normal hierarchy. These results arise from differing approaches to incorporating prior knowledge about neutrinos. We develop a hierarchy-agnostic prior and show that the hierarchy cannot be conclusively determined with current data. The determination of the hierarchy is limited by the neutrino mass scale $Σ_ν$ measurement. We obtain a target precision of $σ(Σ_ν) = 0.014$ eV, necessary for conclusively establishing the normal hierarchy with future data.

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KiDS+VIKING-450 and DES-Y1 combined: Mitigating baryon feedback uncertainty with COSEBIs

We present cosmological constraints from a joint cosmic shear analysis of the Kilo-Degree Survey (KV450) and the Dark Energy Survey (DES-Y1), conducted using Complete Orthogonal Sets of E/B-Integrals (COSEBIs). With COSEBIs we isolate any B-modes which have a non-cosmic shear origin and demonstrate the robustness of our cosmological E-mode analysis as no significant B-modes are detected. We highlight how COSEBIs are fairly insensitive to the amplitude of the non-linear matter power spectrum at high $k$-scales, mitigating the uncertain impact of baryon feedback in our analysis. COSEBIs, therefore, allow us to utilise additional small-scale information, improving the DES-Y1 joint constraints on $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}$ and $Ω_{\rm m}$ by $20\%$. Adopting a flat $Λ$CDM model we find $S_8=0.755^{+0.019}_{-0.021}$, which is in $3.2σ$ tension with the Planck Legacy analysis of the cosmic microwave background.

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Cosmology from large-scale structure: Constraining $Λ$CDM with BOSS

We reanalyse the anisotropic galaxy clustering measurement from the Baryon Oscillation Spectroscopic Survey (BOSS), demonstrating that using the full shape information provides cosmological constraints that are comparable to other low-redshift probes. We find $Ω_\mathrm{m} = 0.317^{+0.015}_{-0.019}$, $σ_8 = 0.710\pm 0.049$, and $h = 0.704\pm 0.024$ for flat $Λ$CDM cosmologies using uninformative priors on $Ω_\mathrm{c}h^2$, $100θ_\mathrm{MC}$, $\ln 10^{10} A_{s}$, and $n_{s}$, and a prior on $Ω_\mathrm{b}h^2$ that is much wider than current constraints. We quantify the agreement between the Planck 2018 constraints from the cosmic microwave background and BOSS, finding the two data sets to be consistent within a flat $Λ$CDM cosmology using the Bayes factor as well as the prior-insensitive suspiciousness statistic. Combining two low-redshift probes, we jointly analyse the clustering of BOSS galaxies with weak lensing measurements from the Kilo-Degree Survey (KV450). The combination of BOSS and KV450 improves the measurement by up to 45%, constraining $σ_8 = 0.702\pm 0.029$ and $S_8 = σ_8\sqrt{Ω_\mathrm{m}/0.3} = 0.728\pm 0.026$. Over the full 5D parameter space, the odds in favour of single cosmology describing galaxy clustering, lensing, and the cosmic microwave background are $7\pm2$. The suspiciousness statistic signals a $2.1\pm0.3σ$ tension between the combined low-redshift probes and measurements from the cosmic microwave background.

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The effects of varying depth in cosmic shear surveys

We present a semi-analytic model for the shear two-point correlation function of a cosmic shear survey with non-uniform depth. Ground-based surveys are subject to depth variations that primarily arise through varying atmospheric conditions. For a survey like the Kilo-Degree Survey (KiDS), we find that the measured depth variation increases the amplitude of the observed shear correlation function at the level of a few percent out to degree-scales, relative to the assumed uniform-depth case. The impact on the inferred cosmological parameters is shown to be insignificant for a KiDS-like survey. For next-generation cosmic shear experiments, however, we conclude that variable depth should be accounted for.

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Cosmic Shear Covariance Matrix in $w$CDM: Cosmology Matters

We present here the cosmo-SLICS, a new suite of simulations specially designed for the analysis of current and upcoming weak lensing data beyond the standard two-point cosmic shear. We sample the $[Ω_{\rm m}, σ_8, h, w_0]$ parameter space at 25 points organised in a Latin hyper-cube, spanning a range that contains most of the $2σ$ posterior distribution from ongoing lensing surveys. At each of these nodes we evolve a pair of $N$-body simulations in which the sampling variance is highly suppressed, and ray-trace the volumes 800 times to further increase the effective sky coverage. We extract a lensing covariance matrix from these pseudo-independent light-cones and show that it closely matches a brute-force construction based on an ensemble of 800 truly independent $N$-body runs. More precisely, a Fisher analysis reveals that both methods yield marginalized two-dimensional constraints that vary by less than 6% in area, a result that holds under different survey specifications and that matches to within 15% the area obtained from an analytical covariance calculation. Extending this comparison with our 25 $w$CDM models, we probe the cosmology dependence of the lensing covariance directly from numerical simulations, reproducing remarkably well the Fisher results from the analytical models at most cosmologies. We demonstrate that varying the cosmology at which the covariance matrix is evaluated in the first place might have an order of magnitude greater impact on the parameter constraints than varying the choice of covariance estimation technique. We present a test case in which we generate fast predictions for both the lensing signal and its associated variance with a flexible Gaussian process regression emulator, achieving an accuracy of a few percent on the former and 10% on the latter.

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KiDS+GAMA: Constraints on Horndeski gravity from combined large-scale structure probes

We present constraints on Horndeski gravity from a combined analysis of cosmic shear, galaxy-galaxy lensing and galaxy clustering from $450\,\mathrm{deg}^2$ of the Kilo-Degree Survey (KiDS) and the Galaxy And Mass Assembly (GAMA) survey. The Horndeski class of dark energy/modified gravity models includes the majority of universally coupled extensions to $Λ$CDM with one scalar field in addition to the metric. We study the functions of time that fully describe the evolution of linear perturbations in Horndeski gravity. Our results are compatible throughout with a $Λ$CDM model. By imposing gravitational wave constraints, we fix the tensor speed excess to zero and consider a subset of models including e.g. quintessence and $f(R)$ theories. Assuming proportionality of the Horndeski functions $α_B$ and $α_M$ (kinetic braiding and the Planck mass run rate, respectively) to the dark energy density fraction $Ω_{\mathrm{DE}}(a) = 1 - Ω_{\mathrm{m}}(a)$, we find for the proportionality coefficients $\hatα_B = 0.20_{-0.33}^{+0.20} \,$ and $\, \hatα_M = 0.25_{-0.29}^{+0.19}$. Our value of $S_8 \equiv σ_8 \sqrt{Ω_{\mathrm{m}}/0.3}$ is in better agreement with the $Planck$ estimate when measured in the enlarged Horndeski parameter space than in a pure $Λ$CDM scenario. In our joint three-probe analysis we report a downward shift of the $S_8$ best fit value from the $Planck$ measurement of $ΔS_8 = 0.016_{-0.046}^{+0.048}$ in Horndeski gravity, compared to $ΔS_8 = 0.059_{-0.039}^{+0.040}$ in $Λ$CDM. Our constraints are robust to the modelling uncertainty of the non-linear matter power spectrum in Horndeski gravity. Our likelihood code for multi-probe analysis in both $Λ$CDM and Horndeski gravity is publicly available at http://github.com/alessiospuriomancini/KiDSHorndeski .

astro-ph.CO↗

Quantifying Suspiciousness Within Correlated Data Sets

We propose a principled Bayesian method for quantifying tension between correlated datasets with wide uninformative parameter priors. This is achieved by extending the Suspiciousness statistic, which is insensitive to priors. Our method uses global summary statistics, and as such it can be used as a diagnostic for internal consistency. We show how our approach can be combined with methods that use parameter space and data space to identify the existing internal discrepancies. As an example, we use it to test the internal consistency of the KiDS-450 data in 4 photometric redshift bins, and to recover controlled internal discrepancies in simulated KiDS data. We propose this as a diagnostic of internal consistency for present and future cosmological surveys, and as a tension metric for data sets that have non-negligible correlation, such as LSST and Euclid.

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CosmoDC2: A Synthetic Sky Catalog for Dark Energy Science with LSST

This paper introduces cosmoDC2, a large synthetic galaxy catalog designed to support precision dark energy science with the Large Synoptic Survey Telescope (LSST). CosmoDC2 is the starting point for the second data challenge (DC2) carried out by the LSST Dark Energy Science Collaboration (LSST DESC). The catalog is based on a trillion-particle, 4.225 Gpc^3 box cosmological N-body simulation, the `Outer Rim' run. It covers 440 deg^2 of sky area to a redshift of z=3 and is complete to a magnitude depth of 28 in the r-band. Each galaxy is characterized by a multitude of properties including stellar mass, morphology, spectral energy distributions, broadband filter magnitudes, host halo information and weak lensing shear. The size and complexity of cosmoDC2 requires an efficient catalog generation methodology; our approach is based on a new hybrid technique that combines data-driven empirical approaches with semi-analytic galaxy modeling. A wide range of observation-based validation tests has been implemented to ensure that cosmoDC2 enables the science goals of the planned LSST DESC DC2 analyses. This paper also represents the official release of the cosmoDC2 data set, including an efficient reader that facilitates interaction with the data.

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GAMA+KiDS: Alignment of galaxies in galaxy groups and its dependence on galaxy scale

Intrinsic galaxy alignments are a source of bias for weak lensing measurements as well as a tool for understanding galaxy formation and evolution. In this work, we measure the alignment of shapes of satellite galaxies, in galaxy groups, with respect to the brightest group galaxy (BGG), as well as alignments of the BGG shape with the satellite positions, using the highly complete Galaxy And Mass Assembly (GAMA) spectroscopic survey and deep imaging from the Kilo Degree Survey. We control systematic errors with dedicated image simulations and measure accurate shapes using the DEIMOS shape measurement method. We find a significant satellite radial alignment signal, which vanishes at large separations from the BGG. We do not identify any strong trends of the signal with galaxy absolute magnitude or group mass. The alignment signal is dominated by red satellites. We also find that the outer regions of galaxies are aligned more strongly than their inner regions, by varying the radial weight employed during the shape measurement process. This behaviour is evident for both red and blue satellites. BGGs are also found to be aligned with satellite positions, with this alignment being stronger when considering the innermost satellites, using red BGGs and the shape of the outer region of the BGG. Lastly, we measure the global intrinsic alignment signal in the GAMA sample for two different radial weight functions and find no significant difference.

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KiDS+GAMA: Intrinsic alignment model constraints for current and future weak lensing cosmology

We directly constrain the non-linear alignment (NLA) model of intrinsic galaxy alignments, analysing the most representative and complete flux-limited sample of spectroscopic galaxies available for cosmic shear surveys. We measure the projected galaxy position-intrinsic shear correlations and the projected galaxy clustering signal using high-resolution imaging from the Kilo Degree Survey (KiDS) overlapping with the GAMA spectroscopic survey, and data from the Sloan Digital Sky Survey. Separating samples by colour, we make no significant detection of blue galaxy alignments, constraining the blue galaxy NLA amplitude $A_{\textrm{IA}}^{\textrm{B}}=0.21^{+0.37}_{-0.36}$ to be consistent with zero. We make robust detections ($\sim9σ$) for red galaxies, with $A_{\textrm{IA}}^{\textrm{R}}=3.18^{+0.47}_{-0.46}$, corresponding to a net radial alignment with the galaxy density field, and we find no evidence for any scaling of alignments with galaxy luminosity. We provide informative priors for current and future weak lensing surveys, an improvement over de facto wide priors that allow for unrealistic levels of intrinsic alignment contamination. For a colour-split cosmic shear analysis of the final KiDS survey area, we forecast that our priors will improve the constraining power on $S_{8}$ and the dark energy equation of state $w_{0}$, by up to $62\%$ and $51\%$, respectively. Our results indicate, however, that the modelling of red/blue-split galaxy alignments may be insufficient to describe samples with variable central/satellite galaxy fractions.

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A Bayesian quantification of consistency in correlated datasets

We present three tiers of Bayesian consistency tests for the general case of $correlated$ datasets. Building on duplicates of the model parameters assigned to each dataset, these tests range from Bayesian evidence ratios as a global summary statistic, to posterior distributions of model parameter differences, to consistency tests in the data domain derived from posterior predictive distributions. For each test we motivate meaningful threshold criteria for the internal consistency of datasets. Without loss of generality we focus on mutually exclusive, correlated subsets of the same dataset in this work. As an application, we revisit the consistency analysis of the two-point weak lensing shear correlation functions measured from KiDS-450 data. We split this dataset according to large vs. small angular scales, tomographic redshift bin combinations, and estimator type. We do not find any evidence for significant internal tension in the KiDS-450 data, with significances below $3\, σ$ in all cases. Software and data used in this analysis can be found at http://kids.strw.leidenuniv.nl/sciencedata.php

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The dependence of intrinsic alignment of galaxies on wavelength using KiDS and GAMA

The outer regions of galaxies are more susceptible to the tidal interactions that lead to intrinsic alignments of galaxies. The resulting alignment signal may therefore depend on the passband if the colours of galaxies vary spatially. To quantify this, we measured the shapes of galaxies with spectroscopic redshifts from the GAMA survey using deep gri imaging data from the KiloDegree Survey. The performance of the moment-based shape measurement algorithm DEIMOS was assessed using dedicated image simulations, which showed that the ellipticities could be determined with an accuracy better than 1% in all bands. Additional tests for potential systematic errors did not reveal any issues. We measure a significant difference of the alignment signal between the g,r and i-band observations. This difference exceeds the amplitude of the linear alignment model on scales below 2 Mpc/h. Separating the sample into central/satellite and red/blue galaxies, we find that that the difference is dominated by red satellite galaxies.

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Enhancing BOSS bispectrum cosmological constraints with maximal compression

We apply two compression methods to the galaxy power spectrum monopole/quadrupole and bispectrum monopole measurements from the BOSS DR12 CMASS sample. Both methods reduce the dimension of the original data-vector to the number of cosmological parameters considered, using the Karhunen-Loève algorithm with an analytic covariance model. In the first case, we infer the posterior through MCMC sampling from the likelihood of the compressed data-vector (MC-KL). The second, faster option, works by first Gaussianising and then orthogonalising the parameter space before the compression; in this option (G-PCA) we only need to run a low-resolution preliminary MCMC sample for the Gaussianization to compute our posterior. Both compression methods accurately reproduce the posterior distributions obtained by standard MCMC sampling on the CMASS dataset for a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The compression enables us to increase the number of bispectrum measurements by a factor of $\sim 23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available. This reduces the $68\%$ credible intervals for the parameters $\left(b_1,b_2,f,σ_8\right)$ by $\left(-24.8\%,-52.8\%,-26.4\%,-21\%\right)$, respectively. The best-fit values we obtain are $(b_1=2.31\pm0.17,b_2=0.77\pm0.19,$ $f(z_{\mathrm{CMASS}})=0.67\pm0.06,σ_8(z_{\mathrm{CMASS}})=0.51\pm0.03)$. Using these methods for future redshift surveys like DESI, Euclid and PFS will drastically reduce the number of simulations needed to compute accurate covariance matrices and will facilitate tighter constraints on cosmological parameters.

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Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints

We present a novel method to compress galaxy clustering three-point statistics and apply it to redshift space galaxy bispectrum monopole measurements from BOSS DR12 CMASS data considering a $k$-space range of $0.03-0.12\,h/\mathrm{Mpc}$. The method consists in binning together bispectra evaluated at sets of wave-numbers forming closed triangles with similar geometrical properties: the area, the cosine of the largest angle and the ratio between the cosines of the remaining two angles. This enables us to increase the number of bispectrum measurements for example by a factor of $23$ over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available to estimate the covariance matrix needed to derive parameter constraints. The $68\%$ credible intervals for the inferred parameters $\left(b_1,b_2,f,σ_8\right)$ are thus reduced by $\left(-39\%,-49\%,-29\%,-22\%\right)$, respectively. We find very good agreement with the posteriors recently obtained by alternative maximal compression methods. This new method does not require the a-priori computation of the data-vector covariance matrix and has the potential to be directly applicable to other three-point statistics (e.g. glaxy clustering, weak gravitational lensing, 21 cm emission line) measured from future surveys such as DESI, Euclid, PFS and SKA.

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Flat-Sky Pseudo-Cls Analysis for Weak Gravitational Lensing

We investigate the use of estimators of weak lensing power spectra based on a flat-sky implementation of the Pseudo-Cl (PCl) technique, where the masked shear field is transformed without regard for masked regions of sky. This masking mixes power, and E-convergence and B-modes. To study the accuracy of forward-modelling and full-sky power spectrum recovery we consider both large-area survey geometries, and small-scale masking due to stars and a checkerboard model for field-of-view gaps. The power spectrum for the large-area survey geometry is sparsely-sampled and highly oscillatory, which makes modelling problematic. Instead, we derive an overall calibration for large-area mask bias using simulated fields. The effects of small-area star masks can be accurately corrected for, while the checkerboard mask has oscillatory and spiky behaviour which leads to percent biases. Apodisation of the masked fields leads to increased biases and a loss of information. We find that we can construct an unbiased forward-model of the raw PCls, and recover the full-sky convergence power to within a few percent accuracy for both Gaussian and lognormal-distributed shear fields. Propagating this through to cosmological parameters using a Fisher-Matrix formalism, we find we can make unbiased estimates of parameters for surveys up to 1,200 deg$^2$ with 30 galaxies per arcmin$^2$, beyond which the percent biases become larger than the statistical accuracy. This implies a flat-sky PCl analysis is accurate for current surveys but a Euclid-like survey will require higher accuracy.

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KiDS-450: Enhancing cosmic shear with clipping transformations

We present the first "clipped" cosmic shear measurement using data from the Kilo-Degree Survey (KiDS-450). "Clipping" transformations suppress the signal from the highest density, non-linear regions of cosmological fields. We demonstrate that these transformations improve constraints on $S_8=σ_8(Ω_{\rm{m}}/0.3)^{0.5}$ when used in combination with conventional two-point statistics. For the KiDS-450 data, we find that the combined measurements improve the constraints on $S_8$ by 17%, compared to shear correlation functions alone. We determine the expectation value of the clipped shear correlation function using a suite of numerical simulations, and develop methodology to mitigate the impact of masking and shot noise. Future improvements in numerical simulations and mass reconstruction methodology will permit the precise calibration of clipped cosmic shear statistics such that clipping can become a standard tool in weak lensing analyses.

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KiDS+GAMA: Cosmology constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing and angular clustering

We present cosmological parameter constraints from a joint analysis of three cosmological probes: the tomographic cosmic shear signal in $\sim$450 deg$^2$ of data from the Kilo Degree Survey (KiDS), the galaxy-matter cross-correlation signal of galaxies from the Galaxies And Mass Assembly (GAMA) survey determined with KiDS weak lensing, and the angular correlation function of the same GAMA galaxies. We use fast power spectrum estimators that are based on simple integrals over the real-space correlation functions, and show that they are practically unbiased over relevant angular frequency ranges. We test our full pipeline on numerical simulations that are tailored to KiDS and retrieve the input cosmology. By fitting different combinations of power spectra, we demonstrate that the three probes are internally consistent. For all probes combined, we obtain $S_8\equiv σ_8 \sqrt{Ω_{\rm m}/0.3}=0.800_{-0.027}^{+0.029}$, consistent with Planck and the fiducial KiDS-450 cosmic shear correlation function results. Marginalising over wide priors on the mean of the tomographic redshift distributions yields consistent results for $S_8$ with an increase of $28\%$ in the error. The combination of probes results in a $26\%$ reduction in uncertainties of $S_8$ over using the cosmic shear power spectra alone. The main gain from these additional probes comes through their constraining power on nuisance parameters, such as the galaxy intrinsic alignment amplitude or potential shifts in the redshift distributions, which are up to a factor of two better constrained compared to using cosmic shear alone, demonstrating the value of large-scale structure probe combination.

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Morpho-z: improving photometric redshifts with galaxy morphology

We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of photometric redshifts when galaxy size, ellipticity, Sérsic index and surface brightness are included in training on galaxy samples from the SDSS and the CFHT Stripe-82 Survey (CS82). We show that by adding galaxy morphological parameters to full $ugriz$ photometry, only mild improvements are obtained, while the gains are substantial in cases where fewer passbands are available. For instance, the combination of $grz$ photometry and morphological parameters almost fully recovers the metrics of $5$-band photometric redshifts. We demonstrate that with morphology it is possible to determine useful redshift distribution $N(z)$ of galaxy samples without any colour information. We also find that the inclusion of quasar redshifts and associated object sizes in training improves the quality of photometric redshift catalogues, compensating for the lack of a good star-galaxy separator. We further show that morphological information can mitigate biases and scatter due to bad photometry. As an application, we derive both point estimates and posterior distributions of redshifts for the official CS82 catalogue, training on morphology and SDSS Stripe-82 $ugriz$ bands when available. Our redshifts yield a 68th percentile error of $0.058(1+z)$, and a catastrophic outlier fraction of $5.2$ per cent. We further include a deep extension trained on morphology and single $i$-band CS82 photometry.

astro-ph.GA↗