arXiv subjects

Elisabeth Krause

Publications and source records attributed to Elisabeth Krause.

At least 55 records · Page 3Linked to original sources

arXiv2023

Growth and Geometry Split in Light of the DES-Y3 Survey

We test the smooth dark energy paradigm using Dark Energy Survey (DES) Year 1 and Year 3 weak lensing and galaxy clustering data. Within the $Λ$CDM and $w$CDM model we separate the expansion and structure growth history by splitting $Ω_\mathrm{m}$ (and $w$) into two meta-parameters that allow for different evolution of growth and geometry in the Universe. We consider three different combinations of priors on geometry from CMB, SNIa, BAO, BBN that differ in constraining power but have been designed such that the growth information comes solely from the DES weak lensing and galaxy clustering. For the DES-Y1 data we find no detectable tension between growth and geometry meta-parameters in both the $Λ$CDM and $w$CDM parameter space. This statement also holds for DES-Y3 cosmic shear and 3x2pt analyses. For the combination of DES-Y3 galaxy-galaxy lensing and galaxy clustering (2x2pt) we measure a tension between our growth and geometry meta-parameters of 2.6$σ$ in the $Λ$CDM and 4.48$σ$ in the $w$CDM model space, respectively. We attribute this tension to residual systematics in the DES-Y3 RedMagic galaxy sample rather than to new physics. We plan to investigate our findings further using alternative lens samples in DES-Y3 and future weak lensing and galaxy clustering datasets.

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arXiv2023

Cluster Cosmology Without Cluster Finding

We propose that observations of super-massive galaxies contain cosmological constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a fiducial spectroscopic and stellar mass complete sample of galaxies drawn from the Dark Energy Spectroscopic Survey (DESI) and forecast how constraints on Omega_m-sigma_8 from this sample will compare with those from number counts of clusters based on richness. At fixed number density, we find that massive galaxies offer similar constraints to galaxy clusters. However, a mass-complete galaxy sample from DESI has the potential to probe lower halo masses than standard optical cluster samples (which are typically limited to richness above 20 and halo mass above 10^13.5); additionally, it is straightforward to cleanly measure projected galaxy clustering for such a DESI sample, which we show can substantially improve the constraining power on Omega_m. We also compare the constraining power of stellar mass-limited samples to those from larger but mass-incomplete samples (e.g., the DESI Bright Galaxy Survey, BGS, Sample); relative to a lower number density stellar mass-limited samples, we find that a BGS-like sample improves statistical constraints by 60% for Omega_m and 40% for sigma_8, but this uses small scale information which will be harder to model for BGS. Our initial assessment of the systematics associated with supermassive galaxy cosmology yields promising results. The proposed samples have a 10% satellite fraction, but we show that cosmological constraints may be robust to the impact of satellites. These findings motivate future work to realize the potential of super-massive galaxies to probe lower halo masses than richness-based clusters and to avoid persistent systematics associated with optical cluster finding.

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arXiv2023

Primordial non-Gaussianity with Angular correlation function: Integral constraint and validation for DES

Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterised by $f_{\rm NL}^{\rm loc}$. We present the methodology to measure $f_{\rm NL}^{\rm loc}$ from the Dark Energy Survey (DES) data using the 2-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of the work is the integral constraint. This condition appears when estimating the mean number density of galaxies from the data and is key in obtaining unbiased $f_{\rm NL}^{\rm loc}$ constraints. The methods are analysed for two types of simulations: $\sim 246$ GOLIAT-PNG N-body small area simulations with $f_{\rm NL}$ equal to -100 and 100, and 1952 Gaussian ICE-COLA mocks with $f_{\rm NL}=0$ that follow the DES angular and redshift distribution. We use the ensemble of GOLIAT-PNG mocks to show the importance of the integral constraint when measuring PNG, where we recover the fiducial values of $f_{\rm NL}$ within the $1σ$ when including the integral constraint. In contrast, we found a bias of $Δf_{\rm NL}\sim 100$ when not including it. For a DES-like scenario, we forecast a bias of $Δf_{\rm NL} \sim 23$, equivalent to $1.8σ$, when not using the IC for a fiducial value of $f_{\rm NL}=100$. We use the ICE-COLA mocks to validate our analysis in a realistic DES-like setup finding it robust to different analysis choices: best-fit estimator, the effect of IC, BAO damping, covariance, and scale choices. We forecast a measurement of $f_{\rm NL}$ within $σ(f_{\rm NL})=31$ when using the DES-Y3 BAO sample, with the ACF in the $1\ {\rm deg}<θ<20\ {\rm deg}$ range.

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arXiv2023

Buzzard to Cardinal: Improved Mock Catalogs for Large Galaxy Surveys

We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including DES, DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of $z=2.35$ to a depth of $m_{\rm{r}}=27$. Compared to the Buzzard mocks, the Cardinal mocks include an updated subhalo abundance matching (SHAM) model that considers orphan galaxies and includes mass-dependent scatter between galaxy luminosity and halo properties. This model can simultaneously fit galaxy clustering and group--galaxy cross-correlations measured in three different luminosity threshold samples. The Cardinal mocks also feature a new color assignment model that can simultaneously fit color-dependent galaxy clustering in three different luminosity bins. We have developed an algorithm that uses photometric data to improve the color assignment model further and have also developed a novel method to improve small-scale lensing below the ray-tracing resolution. These improvements enable the Cardinal mocks to accurately reproduce the abundance of galaxy clusters and the properties of lens galaxies in the Dark Energy Survey data. As such, these simulations will be a valuable tool for future cosmological analyses based on large sky surveys. The cardinal mock will be released upon publication at https://chunhaoto.com/cardinalsim.

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arXiv2022

Kinematic Lensing with the Roman Space Telescope

Kinematic lensing (KL) is a new cosmological measurement technique that combines traditional weak lensing (WL) shape measurements of disc galaxies with their kinematic information. Using the Tully-Fisher relation KL breaks the degeneracy between intrinsic and observed ellipticity and significantly reduces the impact of multiple systematics that are present in traditional WL. We explore the performance of KL given the instrument capabilities of the $\textit{Roman Space Telescope}$, assuming overlap of the High Latitude Imaging Survey (HLIS), the High Latitude Spectroscopy Survey (HLSS) over 2,000 deg$^2$. Our KL suitable galaxy sample has a number density of $n_{\mathrm{gal}}=4~\mathrm{arcmin}^{-1}$ with an estimated shape noise level of $σ_ε=0.035$. We quantify the cosmological constraining power on $Ω_{\mathrm{m}}$-$S_8$, $w_p$-$w_a$ by running simulated likelihood analyses that account for redshift and shear calibration uncertainties, intrinsic alignment and baryonic feedback. Compared to a traditional WL survey we find that KL significantly improves the constraining power on $Ω_{\mathrm{m}}$-$S_8$ (FoM$_{\mathrm{KL}}$=1.70FoM$_{\mathrm{WL}}$) and $w_p$-$w_a$ (FoM$_{\mathrm{KL}}$=3.65FoM$_{\mathrm{WL}}$). We also explore a "narrow tomography KL survey" using 30 instead of the default 10 tomographic bins, however we find no meaningful enhancement to the FoM even when assuming a significant time-dependence in our fiducial dark energy input scenarios.

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arXiv2022

Kinematic Lensing Inference I: Characterizing Shape Noise with Simulated Analyses

The unknown intrinsic shape of source galaxies is one of the largest uncertainties of weak gravitational lensing (WL). It results in the so-called shape noise at the level of $σ_ε^{\mathrm{WL}} \approx 0.26$, whereas the shear effect of interest is of order percent. Kinematic lensing (KL) is a new technique that combines photometric shape measurements with resolved spectroscopic observations to infer the intrinsic galaxy shape and directly estimate the gravitational shear. This paper presents a KL inference pipeline that jointly forward-models galaxy imaging and slit spectroscopy to extract the shear signal. We build a set of realistic mock observations and show that the KL inference pipeline can robustly recover the input shear. To quantify the shear measurement uncertainty for KL, we average the shape noise over a population of randomly oriented disc galaxies and estimate it to be $σ_ε^{\mathrm{KL}}\approx 0.022-0.041$ depending on emission line signal-to-noise. This order of magnitude improvement over traditional WL makes a KL observational program feasible with existing spectroscopic instruments. To this end, we characterize the dependence of KL shape noise on observational factors and discuss implications for the survey strategy of future KL observations. In particular, we find that prioritizing quality spectra of low inclination galaxies is more advantageous than maximizing the overall number density.

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arXiv2022

Modal compression of the redshift-space galaxy bispectrum

We extend the modal decomposition method, previously applied to compress the information in the real-space bispectrum, to the anisotropic redshift-space galaxy bispectrum. In the modal method approach, the bispectrum is expanded on a basis of smooth functions of triangles and their orientations, such that a set of modal expansion coefficients can capture the information in the bispectrum. We assume a reference survey and compute Fisher forecasts for the compressed modal bispectrum and two other basis decompositions of the redshift-space bispectrum in the literature, one based on (single) spherical harmonics and another based on tripolar spherical harmonics. In each case, we compare the forecasted constraints from the compressed statistic with forecasted constraints from the full, uncompressed bispectrum which includes all triangles and orientations. Our main result is that all three compression methods achieve good recovery of the full information content of the bispectrum, but the modal decomposition approach achieves this the most efficiently: only 14 (42) modal expansion coefficients are necessary to obtain constraints that are within 10% (2%) of the full bispectrum result. The next most efficient decomposition is the one based on tripolar spherical harmonics, while the spherical harmonic multipoles are the least efficient.

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arXiv2022

LINNA: Likelihood Inference Neural Network Accelerator

Bayesian posterior inference of modern multi-probe cosmological analyses incurs massive computational costs. For instance, depending on the combinations of probes, a single posterior inference for the Dark Energy Survey (DES) data had a wall-clock time that ranged from 1 to 21 days using a state-of-the-art computing cluster with 100 cores. These computational costs have severe environmental impacts and the long wall-clock time slows scientific productivity. To address these difficulties, we introduce LINNA: the Likelihood Inference Neural Network Accelerator. Relative to the baseline DES analyses, LINNA reduces the computational cost associated with posterior inference by a factor of 8--50. If applied to the first-year cosmological analysis of Rubin Observatory's Legacy Survey of Space and Time (LSST Y1), we conservatively estimate that LINNA will save more than US $\$300,000$ on energy costs, while simultaneously reducing $\rm{CO}_2$ emission by $2,400$ tons. To accomplish these reductions, LINNA automatically builds training data sets, creates neural network surrogate models, and produces a Markov chain that samples the posterior. We explicitly verify that LINNA accurately reproduces the first-year DES (DES Y1) cosmological constraints derived from a variety of different data vectors with our default code settings, without needing to retune the algorithm every time. Further, we find that LINNA is sufficient for enabling accurate and efficient sampling for LSST Y10 multi-probe analyses. We make LINNA publicly available at https://github.com/chto/linna, to enable others to perform fast and accurate posterior inference in contemporary cosmological analyses.

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arXiv2021

Cosmology from Clustering, Cosmic Shear, CMB Lensing, and Cross Correlations: Combining Rubin Observatory and Simons Observatory

In the near future, the overlap of the Rubin Observatory Legacy Survey of Space and Time (LSST) and the Simons Observatory (SO) will present an ideal opportunity for joint cosmological dataset analyses. In this paper we simulate the joint likelihood analysis of these two experiments using six two-point functions derived from galaxy position, galaxy shear, and CMB lensing convergence fields. Our analysis focuses on realistic noise and systematics models and we find that the dark energy Figure-of-Merit (FoM) increases by 53% (92%) from LSST-only to LSST+SO in Year 1 (Year 6). We also investigate the benefits of using the same galaxy sample for both clustering and lensing analyses, and find the choice improves the overall signal-to-noise by ~30-40%, which significantly improves the photo-z calibration and mildly improves the cosmological constraints. Finally, we explore the effects of catastrophic photo-z outliers finding that they cause significant parameter biases when ignored. We develop a new mitigation approach termed "island model", which corrects a large fraction of the biases with only a few parameters while preserving the constraining power.

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arXiv2021

The High Latitude Spectroscopic Survey on the Nancy Grace Roman Space Telescope

The Nancy Grace Roman Space Telescope will conduct a High Latitude Spectroscopic Survey (HLSS) over a large volume at high redshift, using the near-IR grism (1.0-1.93 $μ$m, $R=435-865$) and the 0.28 deg$^2$ wide field camera. We present a reference HLSS which maps 2000 deg$^2$ and achieves an emission line flux limit of 10$^{-16}$ erg/s/cm$^2$ at 6.5$σ$, requiring $\sim$0.6 yrs of observing time. We summarize the flowdown of the Roman science objectives to the science and technical requirements of the HLSS. We construct a mock redshift survey over the full HLSS volume by applying a semi-analytic galaxy formation model to a cosmological N-body simulation, and use this mock survey to create pixel-level simulations of 4 deg$^2$ of HLSS grism spectroscopy. We find that the reference HLSS would measure $\sim$ 10 million H$α$ galaxy redshifts that densely map large scale structure at $z=1-2$ and 2 million [OIII] galaxy redshifts that sparsely map structures at $z=2-3$. We forecast the performance of this survey for measurements of the cosmic expansion history with baryon acoustic oscillations and the growth of large scale structure with redshift space distortions. We also study possible deviations from the reference design, and find that a deep HLSS at $f_{\rm line}>7\times10^{-17}$erg/s/cm$^2$ over 4000 deg$^2$ (requiring $\sim$1.5 yrs of observing time) provides the most compelling stand-alone constraints on dark energy from Roman alone. This provides a useful reference for future optimizations. The reference survey, simulated data sets, and forecasts presented here will inform community decisions on the final scope and design of the Roman HLSS.

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arXiv2021

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.

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arXiv2021

Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe

Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3$\times$2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modeling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude ($Q_1$) generally reflects the strength of baryon feedback. With the upper limit of $Q_1$ prior being bound by the Illustris feedback scenarios, we reach $\sim 20\%$ improvement in the constraint of $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3$\times$2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative $Q_1$ prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than $2 σ$.

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arXiv2021

Mitigating baryonic effects with a theoretical error covariance

One of the primary sources of uncertainties in modeling the cosmic-shear power spectrum on small scales is the effect of baryonic physics. Accurate cosmology for Stage-IV surveys requires knowledge of the matter power spectrum deep in the nonlinear regime at the percent level. Therefore, it is important to develop reliable mitigation techniques to take into account baryonic uncertainties if information from small scales is to be considered in the cosmological analysis. In this work, we develop a new mitigation method for dealing with baryonic physics for the case of the shear angular power spectrum. The method is based on an extended covariance matrix that incorporates baryonic uncertainties informed by hydrodynamical simulations. We use the results from 13 hydrodynamical simulations and the residual errors arising from a fit to a $Λ$CDM model using the extended halo model code {\tt HMCode} to account for baryonic physics. These residual errors are used to model a so-called theoretical error covariance matrix that is added to the original covariance matrix. In order to assess the performance of the method, we use the 2D tomographic shear from four hydrodynamical simulations that have different extremes of baryonic parameters as mock data and run a likelihood analysis comparing the residual bias on $Ω_m$ and $σ_8$ of our method and the HMCode for an LSST-like survey. We use different modelling of the theoretical error covariance matrix to test the robustness of the method. We show that it is possible to reduce the bias in the determination of the tested cosmological parameters at the price of a modest decrease in the precision.

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arXiv2021

Combining information from multiple cosmological surveys: inference and modeling challenges

The tightest and most robust cosmological results of the next decade will be achieved by bringing together multiple surveys of the Universe. This endeavor has to happen across multiple layers of the data processing and analysis, e.g., enhancements are expected from combining Euclid, Rubin, and Roman (as well as other surveys) not only at the level of joint processing and catalog combination, but also during the post-catalog parts of the analysis such as the cosmological inference process. While every experiment builds their own analysis and inference framework and creates their own set of simulations, cross-survey work that homogenizes these efforts, exchanges information from numerical simulations, and coordinates details in the modeling of astrophysical and observational systematics of the corresponding datasets is crucial.

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arXiv2021

2D-FFTLog: Efficient computation of real space covariance matrices for galaxy clustering and weak lensing

Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate and numerically stable computation of non-Gaussian real space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory's Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real space covariances with or without the flat sky approximation is released along with this paper.

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arXiv2020

Discovery of a Candidate Binary Supermassive Black Hole in a Periodic Quasar from Circumbinary Accretion Variability

Binary supermassive black holes (BSBHs) are expected to be a generic byproduct from hierarchical galaxy formation. The final coalescence of BSBHs is thought to be the loudest gravitational wave (GW) siren, yet no confirmed BSBH is known in the GW-dominated regime. While periodic quasars have been proposed as BSBH candidates, the physical origin of the periodicity has been largely uncertain. Here we report discovery of a periodicity (P=1607$\pm$7 days) at 99.95% significance (with a global p-value of ~$10^{-3}$ accounting for the look elsewhere effect) in the optical light curves of a redshift 1.53 quasar, SDSS J025214.67-002813.7. Combining archival Sloan Digital Sky Survey data with new, sensitive imaging from the Dark Energy Survey, the total ~20-yr time baseline spans ~4.6 cycles of the observed 4.4-yr (restframe 1.7-yr) periodicity. The light curves are best fit by a bursty model predicted by hydrodynamic simulations of circumbinary accretion disks. The periodicity is likely caused by accretion rate modulation by a milli-parsec BSBH emitting GWs, dynamically coupled to the circumbinary accretion disk. A bursty hydrodynamic variability model is statistically preferred over a smooth, sinusoidal model expected from relativistic Doppler boost, a kinematic effect proposed for PG1302-102. Furthermore, the frequency dependence of the variability amplitudes disfavors Doppler boost, lending independent support to the circumbinary accretion variability hypothesis. Given our detection rate of one BSBH candidate from circumbinary accretion variability out of 625 quasars, it suggests that future large, sensitive synoptic surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time may be able to detect hundreds to thousands of candidate BSBHs from circumbinary accretion with direct implications for Laser Interferometer Space Antenna.

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arXiv2020

Beyond Limber: Efficient computation of angular power spectra for galaxy clustering and weak lensing

Angular two-point statistics of large-scale structure observables are important cosmological probes. To reach the high accuracy required by the statistical precision of future surveys, some of these statistics may need to be computed without the commonly employed Limber approximation; the exact computation however requires integration over Bessel functions, and a brute-force evaluation is slow to converge. We present a new method based on our generalized FFTLog algorithm for the efficient computation of angular power spectra beyond the Limber approximation. The new method significantly simplifies the calculation and improves the numerical speed and stability. It is easily extended to handle integrals involving derivatives of Bessel functions, making it equally applicable to numerically more challenging cases such as contributions from redshift-space distortions and Doppler effects. We implement our method for galaxy clustering and galaxy-galaxy lensing power spectra. We find that using the Limber approximation for galaxy clustering in future analyses like LSST Year 1 and DES Year 6 may cause significant biases in cosmological parameters, indicating that going beyond the Limber approximation is necessary for these analyses.

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arXiv2020

The Curious Case of PHL 293B: A Long-Lived Transient in a Metal-Poor Blue Compact Dwarf Galaxy

We report on small-amplitude optical variability and recent dissipation of the unusually persistent broad emission lines in the blue compact dwarf galaxy PHL 293B. The galaxy's unusual spectral features (P Cygni-like profiles with $\sim$800 km s$^{-1}$ blueshifted absorption lines) have resulted in conflicting interpretations of the nature of this source in the literature. However, analysis of new Gemini spectroscopy reveals the broad emission has begun to fade after being persistent for over a decade prior. Precise difference imaging light curves constructed with the Sloan Digital Sky Survey and the Dark Energy Survey reveal small-amplitude optical variability of $\sim$0.1 mag in the g band offset by $100\pm21$ pc from the brightest pixel of the host. The light curve is well-described by an active galactic nuclei (AGN)-like damped random walk process. However, we conclude that the origin of the optical variability and spectral features of PHL 293B is due to a long-lived stellar transient, likely a Type IIn supernova or non-terminal outburst, mimicking long-term AGN-like variability. This work highlights the challenges of discriminating between scenarios in such extreme environments, relevant to searches for AGNs in dwarf galaxies. This is the second long-lived transient discovered in a blue compact dwarf, after SDSS1133. Our result implies such long-lived stellar transients may be more common in metal-deficient galaxies. Systematic searches for low-level variability in dwarf galaxies will be possible with the upcoming Legacy Survey of Space and Time at Vera C. Rubin Observatory.

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