103 research outputs found
A Comparison between Shapefit compression and Full-Shape method with PyBird using Abacus DESI mocks
No full text<p>Supplementary material to DESI's publication TITLE to comply with the data management plan. This compressed file contains all the data that was used to create the plots in the PyBird paper. Read the readme file for more information. </p>
Strengthening the bound on the mass of the lightest neutrino with terrestrial and cosmological experiments
No full textWe determine the upper limit on the mass of the lightest neutrino from the most robust recent cosmological and terrestrial data. Marginalizing over possible effective relativistic degrees of freedom at early times ((N)(eff)) and assuming normal mass ordering, the mass of the lightest neutrino is less than 0.037 eV at 95% confidence; with inverted ordering, the bound is 0.042 eV. These results improve upon the strength and robustness of other recent limits and constrain the mass of the lightest neutrino to be barely larger than the largest mass splitting. We show the impacts of realistic mass models and different sources of (N)(eff).Patrick Stöcker, Csaba Balázs, Sanjay Bloor, Torsten Bringmann, Tomás E. Gonzalo, Will Handley, Selim Hotinli, Cullan Howlett, Felix Kahlhoefer, Janina J. Renk, Pat Scott, Aaron C. Vincent, and Martin White (The GAMBIT Cosmology Workgroup)
The redshift-space momentum power spectrum – I. Optimal estimation from peculiar velocity surveys
No full textLow redshift surveys of galaxy peculiar velocities provide a wealth of cosmological information. We revisit the idea of extracting this information by directly measuring the redshift-space momentum power spectrum from such surveys. We provide a comprehensive theoretical and practical framework for estimating and fitting this from data, analogous to well-understood techniques used to measure the galaxy density power spectrum from redshift surveys. We formally derive a new estimator, which includes the effects of shot noise and survey geometry; we evaluate the variance of the estimator in the Gaussian regime; we compute the optimal weights for the estimator; we demonstrate that the measurements are Gaussian distributed, allowing for easy extraction of cosmological parameters; and we explore the effects of peculiar velocity (PV) measurement errors. We finish with a proof-of-concept using realistic mock galaxy catalogues, which demonstrates that we can measure and fit both the redshift-space galaxy density and momentum power spectra from PV surveys and that including the latter substantially improves our constraints on the growth rate of structure. We also provide theoretical descriptions for modelling the non-linear redshift-space density and momentum power spectrum multipoles, and forecasting the constraints on cosmological parameters using the Fisher information contained in these measurements for arbitrary weights. These may be useful for measurements of the galaxy density power spectrum even in the absence of peculiar velocities
The SDSS Peculiar Velocity Catalogue
No full textData, randoms and mock galaxy catalogues for the Sloan Digital Sky Survey Peculiar Velocity Catalogue; Howlett et. al., 2022, MNRAS, in press. See arXiv:2201.03112 for more details.
This is version 1.0.0, and has been superseded by version 1.1.0. Please use the updated record.
Changelog:
1.1.0:
Fixed error in v1.0.0 in specObjID column caused (at some point in the pipeline) due to rounding errors when reading/writing large numbers. v1.1.0 has the correct specObjIDs. Note that 'objid' is correct in both versions of the SDSS PV catalogue, and our recommended method to crossmatch to the spectroscopic SDSS data (wherein the corresponding column to match with is 'bestobjid')
Standard siren speeds: improving velocities in gravitational-wave measurements of H0
No full textWe re-analyse data from the gravitational-wave event GW170817 and its host galaxy NGC 4993 to demonstrate the importance of accurate total and peculiar velocities when measuring the Hubble constant using this nearby standard siren. We show that a number of reasonable choices can be made to estimate the velocities for this event, but that systematic differences remain between these measurements depending on the data used. This leads to significant changes in the Hubble constant inferred from GW170817. We present Bayesian model averaging as one way to account for these differences, and obtain H-0 = 66.8(-9.2)(+13.4) km s(-1)Mpc(-1). Adding additional information on the viewing angle from high-resolution imaging of the radio counterpart refines this to H-0 = 64.8(-7.2)(+7.3) km s(-1) Mpc(-1). During this analysis, we also present an alternative Bayesian model for the posterior on H-0 from standard sirens that works more closely with observed quantities from redshift and peculiar velocity surveys. Our results more accurately capture the true uncertainty on the total and peculiar velocities of NGC 4993 and show that exploring how well different data sets characterize galaxy groups and the velocity field in the local Universe could improve this measurement further. These considerations impact any low-redshift distance measurement, and the improvements we suggest here can also be applied to standard candles like Type Ia supernovae. GW170817 is particularly sensitive to peculiar velocity uncertainties because it is so close. For future standard siren measurements, the importance of this error will decrease as (i) we will measure more distant standard sirens and (ii) the random direction of peculiar velocities will average out with more detections
Galaxy 2-point covariance matrix estimation for next generation surveys
No full textWe perform a detailed analysis of the covariance matrix of the spherically averaged galaxy power spectrum and present a new, practical method for estimating this within an arbitrary survey without the need for running mock galaxy simulations that cover the full survey volume. The method uses theoretical arguments to modify the covariance matrix measured from a set of small-volume cubic galaxy simulations, which are computationally cheap to produce compared to larger simulations and match the measured small-scale galaxy clustering more accurately than is possible using theoretical modelling. We include prescriptions to analytically account for the window function of the survey, which convolves the measured covariance matrix in a non-trivialway. We also present a newmethod to include the effects of super-sample covariance and modes outside the small simulation volume which requires no additional simulations and still allows us to scale the covariance matrix. As validation, we compare the covariance matrix estimated using our new method to that from a brute-force calculation using 500 simulations originally created for analysis of the Sloan Digital Sky Survey Main Galaxy Sample. We find excellent agreement on all scales of interest for large-scale structure analysis, including those dominated by the effects of the survey window, and on scales where theoretical models of the clustering normally break down, but the new method produces a covariance matrix with significantly better signal-to-noise ratio. Although only formally correct in real space, we also discuss how our method can be extended to incorporate the effects of redshift space distortions
Ho’oleilana: An Individual Baryon Acoustic Oscillation?
No full textTheory of the physics of the early hot universe leads to a prediction of baryon acoustic oscillations (BAOs) that has received confirmation from the pairwise separations of galaxies in samples of hundreds of thousands of objects. Evidence is presented here for the discovery of a remarkably strong individual contribution to the BAO signal at z = 0.068, an entity that is given the name Ho’oleilana. The radius of the 3D structure is Mpc. At its core is the Boötes supercluster. The Sloan Great Wall, Center for Astrophysics Great Wall, and Hercules complex all lie within the BAO shell. The interpretation of Ho’oleilana as a BAO structure with our preferred analysis implies a value of the Hubble constant of ${76.9}_{-4.8}^{+8.2}\,\mathrm{km}\,{{\rm{s}}}^{-1}\,{\mathrm{Mpc}}^{-1}.
Faster cosmological analysis with power spectrum without simulations
No full textFuture surveys could obtain tighter constraints on the cosmological parameters with the galaxy power spectrum than with the Cosmic Microwave Background. However, the inclusion of multiple overlapping tracers, redshift bins, and more non-linear scales means that generating the necessary ensemble of simulations for model-fitting presents a computational burden. In this work, we combine full-shape fitting of galaxy power spectra, analytical covariance matrix estimates, the MOPED (Massively Optimised Parameter Estimation and Data compression) method, and the Taylor expansion interpolation of the power spectrum for the first time to constrain the cosmological parameters directly from a state-of-the-art set of galaxy clustering measurements. We find it takes less than a day to compute the analytical covariance while it takes several months to calculate the simulated ones. Combining MOPED with the Taylor expansion interpolation of the power spectrum, we can constrain the cosmological parameters in just a few hours instead of a few days. We also find that even without a priori knowledge of the best-fit cosmological or galaxy bias parameters, the analytical covariance matrix with the MOPED compression still gives consistent cosmological constraints to within 0.1 after two iterations. Therefore, the pipeline we have developed here can significantly speed up the analysis for future surveys such as DESI and Euclid.Revised version for MNRAS submission. 5 figures, 6 tables, and 13 pages. Comments are welcom
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