scholarly journals Self-calibration of weak lensing systematic effects using combined two- and three-point statistics

2021 ◽  
Author(s):  
Susan Pyne ◽  
Benjamin Joachimi
Keyword(s):  
Power Spectrum ◽  
Energy Equation ◽  
Cosmological Parameters ◽  
Weak Lensing ◽  
Calibration Data ◽  
Joint Power ◽  
Systematic Uncertainties ◽  
Systematic Effects ◽  
Two Parameters ◽  
Baseline Approach

Abstract We investigate the prospects for using the weak lensing bispectrum alongside the power spectrum to control systematic uncertainties in a Euclid-like survey. Three systematic effects are considered: the intrinsic alignment of galaxies, uncertainties in the means of tomographic redshift distributions, and multiplicative bias in the measurement of the shear signal. We find that the bispectrum is very effective in mitigating these systematic errors. Varying all three systematics simultaneously, a joint power spectrum and bispectrum analysis reduces the area of credible regions for the cosmological parameters Ωm and σ8 by a factor of 90 and for the two parameters of a time-varying dark energy equation of state by a factor of almost 20, compared with the baseline approach of using the power spectrum alone and of imposing priors consistent with the accuracy requirements specified for Euclid. We also demonstrate that including the bispectrum self-calibrates all three systematic effects to the stringent levels required by the forthcoming generation of weak lensing surveys, thereby reducing the need for external calibration data.

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 KiDS-450: the tomographic weak lensing power spectrum and constraints on cosmological parameters

2017 ◽  
Vol 471 (4) ◽  
pp. 4412-4435 ◽  
Author(s):  
F. Köhlinger ◽  
M. Viola ◽  
B. Joachimi ◽  
H. Hoekstra ◽  
E. van Uitert ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Cosmological Parameters ◽  
Weak Lensing

scholarly journals The self-similarity of weak lensing peaks

2019 ◽  
Vol 488 (4) ◽  
pp. 5833-5851 ◽  
Author(s):  
Christopher T Davies ◽  
Marius Cautun ◽  
Baojiu Li
Keyword(s):  
Signal To Noise Ratio ◽  
Cosmological Parameters ◽  
Weak Lensing ◽  
Self Similarity ◽  
Peak Separation ◽  
Wide Range ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Peak Abundance ◽  
Two Parameters

ABSTRACT We study the statistics of weak lensing convergence peaks, such as their abundance and two-point correlation function (2PCF), for a wide range of cosmological parameters Ωm and σ8 within the standard ΛCDM paradigm, focusing on intermediate-height peaks with signal-to-noise ratio (SNR) of 1.5–3.5. We find that the cosmology dependence of the peak abundance can be described by a one-parameter fitting formula that is accurate to within $\sim 3{{\ \rm per\ cent}}$. The peak 2PCFs are shown to feature a self-similar behaviour: if the peak separation is rescaled by the mean interpeak distance, catalogues with different minimum peak SNR values have identical clustering, which suggests that the peak abundance and clustering are closely interconnected. A simple fitting model for the rescaled 2PCF is given, which together with the peak abundance model above can predict peak 2PCFs with an accuracy better than $\sim 5{{\ \rm per\ cent}}$. The abundance and 2PCFs for intermediate peaks have very different dependencies on Ωm and σ8, implying that their combination can be used to break the degeneracy between these two parameters.

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.

Large‐Scale Power Spectrum and Cosmological Parameters from SFI Peculiar Velocities

1999 ◽  
Vol 523 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Wolfram Freudling ◽  
Idit Zehavi ◽  
Luiz N. da Costa ◽  
Avishai Dekel ◽  
Amiram Eldar ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Large Scale ◽  
Cosmological Parameters ◽  
Peculiar Velocities

scholarly journals Blending and obscuration in weak lensing magnification

2021 ◽  
Author(s):  
E Gaztanaga ◽  
S J Schmidt ◽  
M D Schneider ◽  
J A Tyson
Keyword(s):  
Systematic Errors ◽  
Weak Lensing ◽  
Wide Field ◽  
Photometric Redshifts ◽  
Field Surveys ◽  
Systematic Effects ◽  
The Impact ◽  
Close Pairs ◽  
Mass Profiles

Abstract We test the impact of some systematic errors in weak lensing magnification measurements with the COSMOS 30-band photo-z Survey flux limited to Iauto < 25.0 using correlations of both source galaxy counts and magnitudes. Systematic obscuration effects are measured by comparing counts and magnification correlations. We use the ACS-HST catalogs to identify potential blending objects (close pairs) and perform the magnification analyses with and without blended objects. We find that blending effects start to be important (∼ 0.04 mag obscuration) at angular scales smaller than 0.1 arcmin. Extinction and other systematic obscuration effects can be as large as 0.10 mag (U-band) but are typically smaller than 0.02 mag depending on the band. After applying these corrections, we measure a 3.9σ magnification signal that is consistent for both counts and magnitudes. The corresponding projected mass profiles of galaxies at redshift z ≃ 0.6 (MI ≃ −21) is Σ = 25 ± 6M⊙h3/pc2 at 0.1 Mpc/h, consistent with NFW type profile with M200 ≃ 2 × 1012M⊙h/pc2. Tangential shear and flux-size magnification over the same lenses show similar mass profiles. We conclude that magnification from counts and fluxes using photometric redshifts has the potential to provide complementary weak lensing information in future wide field surveys once we carefully take into account systematic effects, such as obscuration and blending.

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 The unequal-time matter power spectrum: impact on weak lensing observables

2021 ◽  
Vol 2021 (08) ◽  
pp. 001
Author(s):  
Lucia F. de la Bella ◽  
Nicolas Tessore ◽  
Sarah Bridle
Keyword(s):  
Power Spectrum ◽  
Weak Lensing ◽  
Matter Power Spectrum

scholarly journals HUBBLE SPACE TELESCOPECOMBINED STRONG AND WEAK LENSING ANALYSIS OF THE CLASH SAMPLE: MASS AND MAGNIFICATION MODELS AND SYSTEMATIC UNCERTAINTIES

2015 ◽  
Vol 801 (1) ◽  
pp. 44 ◽  
Author(s):  
Adi Zitrin ◽  
Agnese Fabris ◽  
Julian Merten ◽  
Peter Melchior ◽  
Massimo Meneghetti ◽  
...  
Keyword(s):  
Weak Lensing ◽  
Sample Mass ◽  
Systematic Uncertainties

scholarly journals Kinetic field theory: Non-linear cosmic power spectra in the mean-field approximation

2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Matthias Bartelmann ◽  
Johannes Dombrowski ◽  
Sara Konrad ◽  
Elena Kozlikin ◽  
Robert Lilow ◽  
...  
Keyword(s):  
Field Theory ◽  
Power Spectrum ◽  
Mean Field ◽  
Power Spectra ◽  
Field Approximation ◽  
Density Fluctuations ◽  
Mean Field Approximation ◽  
Non Linear ◽  
Two Parameters ◽  
Kinetic Field

We use the recently developed Kinetic Field Theory (KFT) for cosmic structure formation to show how non-linear power spectra for cosmic density fluctuations can be calculated in a mean-field approximation to the particle interactions. Our main result is a simple, closed and analytic, approximate expression for this power spectrum. This expression has two parameters characterising non-linear structure growth which can be calibrated within KFT itself. Using this self-calibration, the non-linear power spectrum agrees with results obtained from numerical simulations to within typically \lesssim10\,\%≲10% up to wave numbers k\lesssim10\,h\,\mathrm{Mpc}^{-1}k≲10hMpc−1 at redshift z = 0z=0. Adjusting the two parameters to optimise agreement with numerical simulations, the relative difference to numerical results shrinks to typically \lesssim 5\,\%≲5%. As part of the derivation of our mean-field approximation, we show that the effective interaction potential between dark-matter particles relative to Zel’dovich trajectories is sourced by non-linear cosmic density fluctuations only, and is approximately of Yukawa rather than Newtonian shape.

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