scholarly journals Modelling baryonic physics in future weak lensing surveys

2019 ◽  
Vol 488 (2) ◽  
pp. 1652-1678 ◽  
Author(s):  
Hung-Jin Huang ◽  
Tim Eifler ◽  
Rachel Mandelbaum ◽  
Scott Dodelson
Keyword(s):  
Power Spectrum ◽  
Cosmological Parameters ◽  
Power Spectra ◽  
Principal Component ◽  
Weak Lensing ◽  
Survey Statistics ◽  
Simulated Likelihood ◽  
Pca Method ◽  
Hydrodynamical Simulations ◽  
Parameter Constraints

Abstract Modifications of the matter power spectrum due to baryonic physics are one of the major theoretical uncertainties in cosmological weak lensing measurements. Developing robust mitigation schemes for this source of systematic uncertainty increases the robustness of cosmological constraints, and may increase their precision if they enable the use of information from smaller scales. Here we explore the performance of two mitigation schemes for baryonic effects in weak lensing cosmic shear: the principal component analysis (PCA) method and the halo-model approach in hmcode. We construct mock tomographic shear power spectra from four hydrodynamical simulations, and run simulated likelihood analyses with cosmolike assuming LSST-like survey statistics. With an angular scale cut of ℓmax < 2000, both methods successfully remove the biases in cosmological parameters due to the various baryonic physics scenarios, with the PCA method causing less degradation in the parameter constraints than hmcode. For a more aggressive ℓmax = 5000, the PCA method performs well for all but one baryonic physics scenario, requiring additional training simulations to account for the extreme baryonic physics scenario of Illustris; hmcode exhibits tensions in the 2D posterior distributions of cosmological parameters due to lack of freedom in describing the power spectrum for $k \gt 10\ h^{-1}\, \mathrm{Mpc}$. We investigate variants of the PCA method and improve the bias mitigation through PCA by accounting for the noise properties in the data via Cholesky decomposition of the covariance matrix. Our improved PCA method allows us to retain more statistical constraining power while effectively mitigating baryonic uncertainties even for a broad range of baryonic physics scenarios.

scholarly journals Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys

2021 ◽  
Author(s):  
Robin E Upham ◽  
Michael L Brown ◽  
Lee Whittaker
Keyword(s):  
Power Spectrum ◽  
Random Noise ◽  
Power Spectra ◽  
Stage Iv ◽  
Wishart Distribution ◽  
Weak Lensing ◽  
Dependence Structure ◽  
Gaussian Fields ◽  
Non Gaussian ◽  
Parameter Constraints

Abstract We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid-like combined tomographic power spectrum analysis of weak lensing, galaxy clustering and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from Stage IV weak lensing surveys.

scholarly journals A hydrodynamical halo model for weak-lensing cross correlations

2020 ◽  
Vol 641 ◽  
pp. A130 ◽  
Author(s):  
A. J. Mead ◽  
T. Tröster ◽  
C. Heymans ◽  
L. Van Waerbeke ◽  
I. G. McCarthy
Keyword(s):  
Cosmological Parameters ◽  
Percent Level ◽  
Power Spectra ◽  
Weak Lensing ◽  
Electron Pressure ◽  
Wide Range ◽  
Cross Correlations ◽  
Dependent Model ◽  
Hydrodynamical Simulations ◽  
Gravitational Processes

On the scale of galactic haloes, the distribution of matter in the cosmos is affected by energetic, non-gravitational processes, the so-called baryonic feedback. A lack of knowledge about the details of how feedback processes redistribute matter is a source of uncertainty for weak-lensing surveys, which accurately probe the clustering of matter in the Universe over a wide range of scales. We developed a cosmology-dependent model for the matter distribution that simultaneously accounts for the clustering of dark matter, gas, and stars. We informed our model by comparing it to power spectra measured from the BAHAMAS suite of hydrodynamical simulations. In addition to considering matter power spectra, we also considered spectra involving the electron-pressure field, which directly relates to the thermal Sunyaev-Zel’dovich (tSZ) effect. We fitted parameters in our model so that it can simultaneously model both matter and pressure data and such that the distribution of gas as inferred from tSZ has an influence on the matter spectrum predicted by our model. We present two variants, one that matches the feedback-induced suppression seen in the matter–matter power spectrum at the percent level and a second that matches the matter–matter data to a slightly lesser degree (≃2%). However, the latter is able to simultaneously model the matter–electron pressure spectrum at the ≃15% level. We envisage our models being used to simultaneously learn about cosmological parameters and the strength of baryonic feedback using a combination of tSZ and lensing auto- and cross-correlation data.

scholarly journals Planck 2018 results

2020 ◽  
Vol 641 ◽  
pp. A8 ◽  
Author(s):  
◽  
N. Aghanim ◽  
Y. Akrami ◽  
M. Ashdown ◽  
J. Aumont ◽  
...  
Keyword(s):  
Power Spectrum ◽  
High Redshift ◽  
Cosmological Parameters ◽  
Power Spectra ◽  
Acoustic Oscillation ◽  
Minimum Variance ◽  
Baryon Density ◽  
Small Scale ◽  
Individual Parameter ◽  
Parameter Constraints

We present measurements of the cosmic microwave background (CMB) lensing potential using the final Planck 2018 temperature and polarization data. Using polarization maps filtered to account for the noise anisotropy, we increase the significance of the detection of lensing in the polarization maps from 5σ to 9σ. Combined with temperature, lensing is detected at 40σ. We present an extensive set of tests of the robustness of the lensing-potential power spectrum, and construct a minimum-variance estimator likelihood over lensing multipoles 8 ≤ L ≤ 400 (extending the range to lower L compared to 2015), which we use to constrain cosmological parameters. We find good consistency between lensing constraints and the results from the Planck CMB power spectra within the ΛCDM model. Combined with baryon density and other weak priors, the lensing analysis alone constrains σ8Ωm0.25 = 0.589 ± 0.020 (1σ errors). Also combining with baryon acoustic oscillation data, we find tight individual parameter constraints, σ8 = 0.811 ± 0.019, H0 = 67.9−1.3+1.2 km s−1 Mpc−1, and Ωm = 0.303−0.018+0.016. Combining with Planck CMB power spectrum data, we measure σ8 to better than 1% precision, finding σ8 = 0.811 ± 0.006. CMB lensing reconstruction data are complementary to galaxy lensing data at lower redshift, having a different degeneracy direction in σ8 − Ωm space; we find consistency with the lensing results from the Dark Energy Survey, and give combined lensing-only parameter constraints that are tighter than joint results using galaxy clustering. Using the Planck cosmic infrared background (CIB) maps as an additional tracer of high-redshift matter, we make a combined Planck-only estimate of the lensing potential over 60% of the sky with considerably more small-scale signal. We additionally demonstrate delensing of the Planck power spectra using the joint and individual lensing potential estimates, detecting a maximum removal of 40% of the lensing-induced power in all spectra. The improvement in the sharpening of the acoustic peaks by including both CIB and the quadratic lensing reconstruction is detected at high significance.

scholarly journals New constraints on the mass bias of galaxy clusters from the power spectra of the thermal Sunyaev–Zeldovich effect and cosmic shear

2020 ◽  
Vol 72 (2) ◽  
Author(s):  
Ryu Makiya ◽  
Chiaki Hikage ◽  
Eiichiro Komatsu
Keyword(s):  
Power Spectrum ◽  
Galaxy Clusters ◽  
Cosmological Parameters ◽  
Power Spectra ◽  
Matter Density ◽  
Density Fluctuations ◽  
Microwave Background ◽  
Mass Bias ◽  
Cosmic Shear ◽  
Hydrodynamical Simulations

Abstract The thermal Sunyaev–Zeldovich (tSZ) power spectrum is a powerful probe of the present-day amplitude of matter density fluctuations, and has been measured up to $\ell \approx 10^3$ from the Planck data. The largest systematic uncertainty in the interpretation of this data is the so-called “mass bias” parameter B, which relates the true halo mass to the mass proxy used by the Planck team as $M\,_{\rm 500c}^{\rm Planck}=M\,_{\rm 500c}^{\rm true}/B$. Since the power spectrum of the cosmic weak lensing shear is also sensitive to the amplitude of matter density fluctuations via $S_8\equiv \sigma _8 \Omega _{\rm m}^{\alpha }$ with $\alpha \sim 0.5$, we can break the degeneracy between the mass bias and the cosmological parameters by combining the tSZ and cosmic shear power spectra. In this paper, we perform a joint likelihood analysis of the tSZ power spectrum from Planck and the cosmic shear power spectrum from Subaru Hyper Suprime-Cam. Our analysis does not use the primordial cosmic microwave background (CMB) information. We obtain a new constraint on the mass bias as $B = 1.37 ^{+0.15}_{-0.23}$ or $(1-b) = B^{-1}=0.73^{+0.08}_{-0.13}$ ($68\%$ confidence limit), for $\sigma _8 < 0.9$. This value of B is lower than that needed to reconcile the tSZ data with the primordial CMB and CMB lensing data, i.e., $B = 1.64 \pm 0.19$, but is consistent with the mass bias expected from hydrodynamical simulations, $B = 1.28 \pm 0.20$. Thus our results indicate that the mass bias is consistent with the non-thermal pressure support from mass accretion of galaxy clusters via the cosmic structure formation, and that the cosmologies inferred from the tSZ and the cosmic shear are consistent with each other.

scholarly journals The anisotropy of the power spectrum in periodic cosmological simulations

2021 ◽  
Vol 503 (4) ◽  
pp. 5638-5645
Author(s):  
Gábor Rácz ◽  
István Szapudi ◽  
István Csabai ◽  
László Dobos
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Large Scale ◽  
Cold Dark Matter ◽  
Initial Conditions ◽  
Power Spectra ◽  
Cosmological Simulations ◽  
Spherical Collapse ◽  
Lower Amplitude ◽  
Hydrodynamical Simulations

ABSTRACT The classical gravitational force on a torus is anisotropic and always lower than Newton’s 1/r2 law. We demonstrate the effects of periodicity in dark matter only N-body simulations of spherical collapse and standard Lambda cold dark matter (ΛCDM) initial conditions. Periodic boundary conditions cause an overall negative and anisotropic bias in cosmological simulations of cosmic structure formation. The lower amplitude of power spectra of small periodic simulations is a consequence of the missing large-scale modes and the equally important smaller periodic forces. The effect is most significant when the largest mildly non-linear scales are comparable to the linear size of the simulation box, as often is the case for high-resolution hydrodynamical simulations. Spherical collapse morphs into a shape similar to an octahedron. The anisotropic growth distorts the large-scale ΛCDM dark matter structures. We introduce the direction-dependent power spectrum invariant under the octahedral group of the simulation volume and show that the results break spherical symmetry.

scholarly journals Testing the impact of satellite anisotropy on large- and small-scale intrinsic alignments using hydrodynamical simulations

2019 ◽  
Vol 491 (4) ◽  
pp. 5330-5350 ◽  
Author(s):  
S Samuroff ◽  
R Mandelbaum ◽  
T Di Matteo
Keyword(s):  
Power Spectra ◽  
Theoretical Description ◽  
Small Scale ◽  
Spherically Symmetric ◽  
Number Density ◽  
Simulated Likelihood ◽  
Hydrodynamical Simulation ◽  
Likelihood Analysis ◽  
Hydrodynamical Simulations ◽  
The Impact

ABSTRACT Galaxy intrinsic alignments (IAs) have long been recognized as a significant contaminant to weak lensing-based cosmological inference. In this paper we seek to quantify the impact of a common modelling assumption in analytic descriptions of IAs: that of spherically symmetric dark matter haloes. Understanding such effects is important as the current generation of IA models are known to be limited, particularly on small scales, and building an accurate theoretical description will be essential for fully exploiting the information in future lensing data. Our analysis is based on a catalogue of 113 560 galaxies between z = 0.06 and 1.00 from massiveblack-ii, a hydrodynamical simulation of box length $100 \, h^{-1}$ Mpc. We find satellite anisotropy contributes at the level of $\ge 30\!-\!40{{\ \rm per\ cent}}$ to the small-scale alignment correlation functions. At separations larger than $1 \, h^{-1}$ Mpc the impact is roughly scale independent, inducing a shift in the amplitude of the IA power spectra of $\sim 20{{\ \rm per\ cent}}$. These conclusions are consistent across the redshift range and between the massiveblack-ii and the illustris simulations. The cosmological implications of these results are tested using a simulated likelihood analysis. Synthetic cosmic shear data are constructed with the expected characteristics (depth, area, and number density) of a future LSST-like survey. Our results suggest that modelling alignments using a halo model based upon spherical symmetry could potentially induce cosmological parameter biases at the ∼1.5σ level for S8 and w.

scholarly journals Deep learning dark matter map reconstructions from DES SV weak lensing data

2020 ◽  
Vol 492 (4) ◽  
pp. 5023-5029 ◽  
Author(s):  
Niall Jeffrey ◽  
François Lanusse ◽  
Ofer Lahav ◽  
Jean-Luc Starck
Keyword(s):  
Dark Matter ◽  
Deep Learning ◽  
Power Spectrum ◽  
Cosmological Parameters ◽  
Simulated Data ◽  
Wiener Filtering ◽  
Weak Lensing ◽  
Gaussian Shape ◽  
Non Linear ◽  
Mass Mapping

ABSTRACT We present the first reconstruction of dark matter maps from weak lensing observational data using deep learning. We train a convolution neural network with a U-Net-based architecture on over 3.6 × 105 simulated data realizations with non-Gaussian shape noise and with cosmological parameters varying over a broad prior distribution. We interpret our newly created dark energy survey science verification (DES SV) map as an approximation of the posterior mean P(κ|γ) of the convergence given observed shear. Our DeepMass1 method is substantially more accurate than existing mass-mapping methods. With a validation set of 8000 simulated DES SV data realizations, compared to Wiener filtering with a fixed power spectrum, the DeepMass method improved the mean square error (MSE) by 11 per cent. With N-body simulated MICE mock data, we show that Wiener filtering, with the optimal known power spectrum, still gives a worse MSE than our generalized method with no input cosmological parameters; we show that the improvement is driven by the non-linear structures in the convergence. With higher galaxy density in future weak lensing data unveiling more non-linear scales, it is likely that deep learning will be a leading approach for mass mapping with Euclid and LSST.

scholarly journals Testing the reliability of fast methods for weak lensing simulations: wl-moka on pinocchio

2020 ◽  
Vol 496 (2) ◽  
pp. 1307-1324
Author(s):  
Carlo Giocoli ◽  
Pierluigi Monaco ◽  
Lauro Moscardini ◽  
Tiago Castro ◽  
Massimo Meneghetti ◽  
...  
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Mass Density ◽  
Cosmological Parameters ◽  
Power Spectra ◽  
Mass Function ◽  
Parametric Models ◽  
Weak Lensing ◽  
Approximate Methods ◽  
Percent Accuracy

ABSTRACT The generation of simulated convergence maps is of key importance in fully exploiting weak lensing by large-scale structure (LSS) from which cosmological parameters can be derived. In this paper, we present an extension of the pinocchio code that produces catalogues of dark matter haloes so that it is capable of simulating weak lensing by Modify LSS into Large Scale Structures (LSS). Like wl-moka, the method starts with a random realization of cosmological initial conditions, creates a halo catalogue and projects it on to the past light-cone, and paints in haloes assuming parametric models for the mass density distribution within them. Large-scale modes that are not accounted for by the haloes are constructed using linear theory. We discuss the systematic errors affecting the convergence power spectra when Lagrangian perturbation theory at increasing order is used to displace the haloes within pinocchio, and how they depend on the grid resolution. Our approximate method is shown to be very fast when compared to full ray-tracing simulations from an N-body run and able to recover the weak lensing signal, at different redshifts, with a few percent accuracy. It also allows for quickly constructing weak lensing covariance matrices, complementing pinocchio’s ability of generating the cluster mass function and galaxy clustering covariances and thus paving the way for calculating cross-covariances between the different probes. This work advances these approximate methods as tools for simulating and analysing survey data for cosmological purposes.

scholarly journals The lensing properties of subhaloes in massive elliptical galaxies in sterile neutrino cosmologies

2019 ◽  
Vol 491 (1) ◽  
pp. 1295-1310 ◽  
Author(s):  
Giulia Despali ◽  
Mark Lovell ◽  
Simona Vegetti ◽  
Robert A Crain ◽  
Benjamin D Oppenheimer
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Galaxy Formation ◽  
Cold Dark Matter ◽  
Distribution Density ◽  
Sterile Neutrino ◽  
Power Spectra ◽  
Mass Function ◽  
Elliptical Galaxies ◽  
Hydrodynamical Simulations

ABSTRACT We use high-resolution hydrodynamical simulations run with the EAGLE model of galaxy formation to study the differences between the properties of – and subsequently the lensing signal from – subhaloes of massive elliptical galaxies at redshift 0.2, in Cold and Sterile Neutrino (SN) Dark Matter models. We focus on the two 7 keV SN models that bracket the range of matter power spectra compatible with resonantly produced SN as the source of the observed 3.5 keV line. We derive an accurate parametrization for the subhalo mass function in these two SN models relative to cold dark matter (CDM), as well as the subhalo spatial distribution, density profile, and projected number density and the dark matter fraction in subhaloes. We create mock lensing maps from the simulated haloes to study the differences in the lensing signal in the framework of subhalo detection. We find that subhalo convergence is well described by a lognormal distribution and that signal of subhaloes in the power spectrum is lower in SN models with respect to CDM, at a level of 10–80 per cent, depending on the scale. However, the scatter between different projections is large and might make the use of power spectrum studies on the typical scales of current lensing images very difficult. Moreover, in the framework of individual detections through gravitational imaging a sample of ≃30 lenses with an average sensitivity of $M_{\rm {sub}} = 5 \times 10^{7}\, {\rm M}_{\odot}$ would be required to discriminate between CDM and the considered sterile neutrino models.

scholarly journals Computing the small-scale galaxy power spectrum and bispectrum in configuration space

2019 ◽  
Vol 492 (1) ◽  
pp. 1214-1242 ◽  
Author(s):  
Oliver H E Philcox ◽  
Daniel J Eisenstein
Keyword(s):  
Power Spectrum ◽  
Configuration Space ◽  
Fourier Transforms ◽  
Cosmological Parameters ◽  
Power Spectra ◽  
Small Scale ◽  
High K ◽  
Cross Covariance ◽  
Small Scales ◽  
Point Correlation

ABSTRACT We present a new class of estimators for computing small-scale power spectra and bispectra in configuration space via weighted pair and triple counts, with no explicit use of Fourier transforms. Particle counts are truncated at $R_0\sim 100\, h^{-1}\, \mathrm{Mpc}$ via a continuous window function, which has negligible effect on the measured power spectrum multipoles at small scales. This gives a power spectrum algorithm with complexity $\mathcal {O}(NnR_0^3)$ (or $\mathcal {O}(Nn^2R_0^6)$ for the bispectrum), measuring N galaxies with number density n. Our estimators are corrected for the survey geometry and have neither self-count contributions nor discretization artefacts, making them ideal for high-k analysis. Unlike conventional Fourier-transform-based approaches, our algorithm becomes more efficient on small scales (since a smaller R0 may be used), thus we may efficiently estimate spectra across k-space by coupling this method with standard techniques. We demonstrate the utility of the publicly available power spectrum algorithm by applying it to BOSS DR12 simulations to compute the high-k power spectrum and its covariance. In addition, we derive a theoretical rescaled-Gaussian covariance matrix, which incorporates the survey geometry and is found to be in good agreement with that from mocks. Computing configuration- and Fourier-space statistics in the same manner allows us to consider joint analyses, which can place stronger bounds on cosmological parameters; to this end we also discuss the cross-covariance between the two-point correlation function and the small-scale power spectrum.

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