scholarly journals Weak lensing minima and peaks: Cosmological constraints and the impact of baryons

2020 ◽  
Vol 495 (3) ◽  
pp. 2531-2542 ◽  
Author(s):  
William R Coulton ◽  
Jia Liu ◽  
Ian G McCarthy ◽  
Ken Osato
Keyword(s):  
Power Spectrum ◽  
Neutrino Mass ◽  
Matter Density ◽  
Weak Lensing ◽  
Cosmological Constraints ◽  
Credible Intervals ◽  
Hydrodynamical Simulations ◽  
Non Gaussian ◽  
The Impact

ABSTRACT We present a novel statistic to extract cosmological information in weak lensing data: the lensing minima. We also investigate the effect of baryons on cosmological constraints from peak and minimum counts. Using the MassiveNuS simulations, we find that lensing minima are sensitive to non-Gaussian cosmological information and are complementary to the lensing power spectrum and peak counts. For an LSST-like survey, we obtain $95{{\ \rm per\ cent}}$ credible intervals from a combination of lensing minima and peaks that are significantly stronger than from the power spectrum alone, by $44{{\ \rm per\ cent}}$, $11{{\ \rm per\ cent}}$, and $63{{\ \rm per\ cent}}$ for the neutrino mass sum ∑mν, matter density Ωm, and amplitude of fluctuation As, respectively. We explore the effect of baryonic processes on lensing minima and peaks using the hydrodynamical simulations BAHAMAS and Osato15. We find that ignoring baryonic effects would lead to strong (≈4σ) biases in inferences from peak counts, but negligible (≈0.5σ) for minimum counts, suggesting lensing minima are a potentially more robust tool against baryonic effects. Finally, we demonstrate that the biases can in principle be mitigated without significantly degrading cosmological constraints when we model and marginalize the baryonic effects.

scholarly journals Cosmological model parameter dependence of the matter power spectrum covariance from the DEUS-PUR Cosmo simulations

2020 ◽  
Vol 500 (2) ◽  
pp. 2532-2542
Author(s):  
Linda Blot ◽  
Pier-Stefano Corasaniti ◽  
Yann Rasera ◽  
Shankar Agarwal
Keyword(s):  
Dark Energy ◽  
Power Spectrum ◽  
Cold Dark Matter ◽  
Matter Density ◽  
Density Fluctuations ◽  
Matrix Analysis ◽  
Model Parameter ◽  
Matter Power Spectrum ◽  
Non Gaussian ◽  
The Impact

ABSTRACT Future galaxy surveys will provide accurate measurements of the matter power spectrum across an unprecedented range of scales and redshifts. The analysis of these data will require one to accurately model the imprint of non-linearities of the matter density field. In particular, these induce a non-Gaussian contribution to the data covariance that needs to be properly taken into account to realize unbiased cosmological parameter inference analyses. Here, we study the cosmological dependence of the matter power spectrum covariance using a dedicated suite of N-body simulations, the Dark Energy Universe Simulation–Parallel Universe Runs (DEUS-PUR) Cosmo. These consist of 512 realizations for 10 different cosmologies where we vary the matter density Ωm, the amplitude of density fluctuations σ8, the reduced Hubble parameter h, and a constant dark energy equation of state w by approximately $10{{\ \rm per\ cent}}$. We use these data to evaluate the first and second derivatives of the power spectrum covariance with respect to a fiducial Λ-cold dark matter cosmology. We find that the variations can be as large as $150{{\ \rm per\ cent}}$ depending on the scale, redshift, and model parameter considered. By performing a Fisher matrix analysis we explore the impact of different choices in modelling the cosmological dependence of the covariance. Our results suggest that fixing the covariance to a fiducial cosmology can significantly affect the recovered parameter errors and that modelling the cosmological dependence of the variance while keeping the correlation coefficient fixed can alleviate the impact of this effect.

scholarly journals Tomographic weak lensing bispectrum: a thorough analysis towards the next generation of galaxy surveys

2019 ◽  
Vol 490 (4) ◽  
pp. 4688-4714 ◽  
Author(s):  
Matteo Rizzato ◽  
Karim Benabed ◽  
Francis Bernardeau ◽  
Fabien Lacasa
Keyword(s):  
Power Spectrum ◽  
High Performance ◽  
Large Scale ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
Weak Lensing ◽  
Galaxy Surveys ◽  
Point Correlation ◽  
Non Gaussian ◽  
The Impact

ABSTRACT We address key points for an efficient implementation of likelihood codes for modern weak lensing large-scale structure surveys. Specifically, we focus on the joint weak lensing convergence power spectrum–bispectrum probe and we tackle the numerical challenges required by a realistic analysis. Under the assumption of (multivariate) Gaussian likelihoods, we have developed a high performance code that allows highly parallelized prediction of the binned tomographic observables and of their joint non-Gaussian covariance matrix accounting for terms up to the six-point correlation function and supersample effects. This performance allows us to qualitatively address several interesting scientific questions. We find that the bispectrum provides an improvement in terms of signal-to-noise ratio (S/N) of about 10 per cent on top of the power spectrum, making it a non-negligible source of information for future surveys. Furthermore, we are capable to test the impact of theoretical uncertainties in the halo model used to build our observables; with presently allowed variations we conclude that the impact is negligible on the S/N. Finally, we consider data compression possibilities to optimize future analyses of the weak lensing bispectrum. We find that, ignoring systematics, five equipopulated redshift bins are enough to recover the information content of a Euclid-like survey, with negligible improvement when increasing to 10 bins. We also explore principal component analysis and dependence on the triangle shapes as ways to reduce the numerical complexity of the problem.

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 Towards determining the neutrino mass hierarchy: weak lensing and galaxy clustering forecasts with baryons and intrinsic alignments

2020 ◽  
Vol 493 (2) ◽  
pp. 1640-1661 ◽  
Author(s):  
David Copeland ◽  
Andy Taylor ◽  
Alex Hall
Keyword(s):  
Neutrino Mass ◽  
Stage Iv ◽  
Double Beta Decay ◽  
Weak Lensing ◽  
Small Scale ◽  
Mass Hierarchy ◽  
Neutrino Mass Hierarchy ◽  
Galaxy Clustering ◽  
The Impact ◽  
Adiabatic Contraction

ABSTRACT The capacity of Stage IV lensing surveys to measure the neutrino mass sum and differentiate between the normal and inverted mass hierarchies depends on the impact of nuisance parameters describing small-scale baryonic astrophysics and intrinsic alignments. For a Euclid-like survey, we perform the first combined weak lensing and galaxy clustering Fisher analysis with baryons, intrinsic alignments, and massive neutrinos for both hierarchies. We use a matter power spectrum generated from a halo model that captures the impact of baryonic feedback and adiabatic contraction. For weak lensing, we find that baryons cause severe degradation to forecasts of the neutrino mass sum, Σ, approximately doubling σΣ. We show that including galaxy clustering constraints from Euclid and BOSS, and cosmic microwave background (CMB) Planck priors, can reduce this degradation to σΣ to 9 per cent and 16 per cent for the normal and inverted hierarchies, respectively. The combined forecasts, $\sigma _{\Sigma _{\rm {NH}}}=0.034\, \rm {eV}$ and $\sigma _{\Sigma _{\rm {IH}}}=0.034\, \rm {eV}$, preclude a meaningful distinction of the hierarchies but could be improved upon with future CMB priors on ns and information from neutrinoless double beta decay to achieve a 2σ distinction. The effect of intrinsic alignments on forecasts is shown to be minimal, with σΣ even experiencing mild improvements due to information from the intrinsic alignment signal. We find that while adiabatic contraction and intrinsic alignments will require careful calibration to prevent significant biasing of Σ, there is less risk presented by feedback from energetic events like AGN and supernovae.

scholarly journals The impact of the observed baryon distribution in haloes on the total matter power spectrum

2019 ◽  
Vol 492 (2) ◽  
pp. 2285-2307 ◽  
Author(s):  
Stijn N B Debackere ◽  
Joop Schaye ◽  
Henk Hoekstra
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Gas Content ◽  
Total Power ◽  
X Ray ◽  
Hot Gas ◽  
Matter Power Spectrum ◽  
Hydrodynamical Simulations ◽  
Halo Masses ◽  
The Impact

ABSTRACT The interpretation of upcoming weak gravitational lensing surveys depends critically on our understanding of the matter power spectrum on scales $k \lt 10\, {h\, {\rm Mpc}^{-1}}$, where baryonic processes are important. We study the impact of galaxy formation processes on the matter power spectrum using a halo model that treats the stars and gas separately from the dark matter distribution. We use empirical constraints from X-ray observations (hot gas) and halo occupation distribution modelling (stars) for the baryons. Since X-ray observations cannot generally measure the hot gas content outside r500c, we vary the gas density profiles beyond this radius. Compared with dark matter only models, we find a total power suppression of $1\, {\mathrm{per\ cent}}$ ($5\, {\mathrm{per\ cent}}$) on scales $0.2\!-\!1\, {h\, {\rm Mpc}^{-1}}$ ($0.5\!-\!2\, {h\, {\rm Mpc}^{-1}}$), where lower baryon fractions result in stronger suppression. We show that groups of galaxies ($10^{13} \lt m_{\mathrm{500c}} / (h^{-1}\, \mathrm{M}_{\odot }) \lt 10^{14}$) dominate the total power at all scales $k \lesssim 10\, {h\, {\rm Mpc}^{-1}}$. We find that a halo mass bias of $30\, {\mathrm{per\ cent}}$ (similar to what is expected from the hydrostatic equilibrium assumption) results in an underestimation of the power suppression of up to $4\, {\mathrm{per\ cent}}$ at $k=1\, {h\, {\rm Mpc}^{-1}}$, illustrating the importance of measuring accurate halo masses. Contrary to work based on hydrodynamical simulations, our conclusion that baryonic effects can no longer be neglected is not subject to uncertainties associated with our poor understanding of feedback processes. Observationally, probing the outskirts of groups and clusters will provide the tightest constraints on the power suppression for $k \lesssim 1\, {h\, {\rm Mpc}^{-1}}$.

scholarly journals The impact of baryonic physics and massive neutrinos on weak lensing peak statistics

2019 ◽  
Vol 488 (3) ◽  
pp. 3340-3357 ◽  
Author(s):  
Matthew Fong ◽  
Miyoung Choi ◽  
Victoria Catlett ◽  
Brandyn Lee ◽  
Austin Peel ◽  
...  
Keyword(s):  
Neutrino Mass ◽  
Large Scale ◽  
Cosmological Parameters ◽  
Mass Function ◽  
Weak Lensing ◽  
The Bahamas ◽  
Massive Neutrinos ◽  
Evolution Of Structure ◽  
The Impact ◽  
The Universe

ABSTRACT We study the impact of baryonic processes and massive neutrinos on weak lensing peak statistics that can be used to constrain cosmological parameters. We use the BAHAMAS suite of cosmological simulations, which self-consistently include baryonic processes and the effect of massive neutrino free-streaming on the evolution of structure formation. We construct synthetic weak lensing catalogues by ray tracing through light-cones, and use the aperture mass statistic for the analysis. The peaks detected on the maps reflect the cumulative signal from massive bound objects and general large-scale structure. We present the first study of weak lensing peaks in simulations that include both baryonic physics and massive neutrinos (summed neutrino mass Mν = 0.06, 0.12, 0.24, and 0.48 eV assuming normal hierarchy), so that the uncertainty due to physics beyond the gravity of dark matter can be factored into constraints on cosmological models. Assuming a fiducial model of baryonic physics, we also investigate the correlation between peaks and massive haloes, over a range of summed neutrino mass values. As higher neutrino mass tends to suppress the formation of massive structures in the Universe, the halo mass function and lensing peak counts are therefore modified as a function of Mν. Over most of the S/N range, the impact of fiducial baryonic physics is greater (less) than neutrinos for 0.06 and 0.12 (0.24 and 0.48) eV models. Both baryonic physics and massive neutrinos should be accounted for when deriving cosmological parameters from weak lensing observations.

scholarly journals Weak lensing cosmology with convolutional neural networks on noisy data

2019 ◽  
Vol 490 (2) ◽  
pp. 1843-1860 ◽  
Author(s):  
Dezső Ribli ◽  
Bálint Ármin Pataki ◽  
José Manuel Zorrilla Matilla ◽  
Daniel Hsu ◽  
Zoltán Haiman ◽  
...  
Keyword(s):  
Neural Networks ◽  
Correlation Function ◽  
Power Spectrum ◽  
Convolutional Neural Networks ◽  
Higher Order ◽  
Weak Lensing ◽  
Noise Levels ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Non Gaussian

ABSTRACT Weak gravitational lensing is one of the most promising cosmological probes of the late universe. Several large ongoing (DES, KiDS, HSC) and planned (LSST, Euclid, WFIRST) astronomical surveys attempt to collect even deeper and larger scale data on weak lensing. Due to gravitational collapse, the distribution of dark matter is non-Gaussian on small scales. However, observations are typically evaluated through the two-point correlation function of galaxy shear, which does not capture non-Gaussian features of the lensing maps. Previous studies attempted to extract non-Gaussian information from weak lensing observations through several higher order statistics such as the three-point correlation function, peak counts, or Minkowski functionals. Deep convolutional neural networks (CNN) emerged in the field of computer vision with tremendous success, and they offer a new and very promising framework to extract information from 2D or 3D astronomical data sets, confirmed by recent studies on weak lensing. We show that a CNN is able to yield significantly stricter constraints of (σ8, Ωm) cosmological parameters than the power spectrum using convergence maps generated by full N-body simulations and ray-tracing, at angular scales and shape noise levels relevant for future observations. In a scenario mimicking LSST or Euclid, the CNN yields 2.4–2.8 times smaller credible contours than the power spectrum, and 3.5–4.2 times smaller at noise levels corresponding to a deep space survey such as WFIRST. We also show that at shape noise levels achievable in future space surveys the CNN yields 1.4–2.1 times smaller contours than peak counts, a higher order statistic capable of extracting non-Gaussian information from weak lensing maps.

Sign in / Sign up

Export Citation Format

Share Document