arXiv subjects

István Szapudi

Publications and source records attributed to István Szapudi.

At least 37 records · Page 2Linked to original sources

arXiv2019

An Ising model for galaxy bias

A reliable model of galaxy bias is necessary for interpreting data from future dense galaxy surveys. Conventional bias models are inaccurate, in that they can yield unphysical results ($δ_g < -1$) for voids that might contain half of the available cosmological information. For this reason, we present a physically-motivated bias model based on an analogy with the Ising model. With only two free parameters, the model produces sensible results for both high- and low-density regions. We also test the model using a catalog of Millennium Simulation galaxies in cubical survey pixels with side lengths from $2h^{-1}$--$31h^{-1}$Mpc, at redshifts from 0 to 2. We find the Ising model markedly superior to linear and quadratic bias models on scales smaller than $10h^{-1}$Mpc, while those conventional models fare better on scales larger than $30h^{-1}$Mpc. While the largest scale where the Ising model is applicable might vary for a specific galaxy catalog, it should be superior on any scale with a non-negligible fraction of cells devoid of galaxies.

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arXiv2019

Predicting the Sufficient-Statistics Power Spectrum for Galaxy Surveys: A Recipe for $P_{A*}(k)$

Future galaxy surveys hope to realize significantly tighter constraints on various cosmological parameters. The higher number densities achieved by these surveys will allow them to probe the smaller scales affected by non-linear clustering. However, in these regimes, the standard power spectrum can extract only a portion of such surveys' cosmological information. In contrast, the alternate statistic $A^*$ has the potential to double these surveys' information return, provided one can predict the $A^*$-power spectrum for a given cosmology. Thus, in this work we provide a prescription for this power spectrum $P_{A^*}(k)$, finding that the prescription is typically accurate to about 5 per cent for near-concordance cosmologies. This prescription will thus allow us to multiply the information gained from surveys such as Euclid and WFIRST.

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arXiv2019

A Gravitational Ising Model for the Statistical Bias of Galaxies

Evaluation of gravitational theories by means of cosmological data suffers from the fact that galaxies are biased tracers of dark matter. Current bias models focus primarily on high-density regions, whereas low-density regions carry significant amounts of information relevant to the constraint of dark energy and alternative gravity theories. Thus, proper treatment of both high and low densities is important for future surveys. Accordingly, we here present an interactionless Ising model for this bias, and we demonstrate that it exhibits a remarkably good fit to both Millennium Simulation and Sloan Digital Sky Survey data, at both density extremes. The quality of the fit indicates that galaxy formation is (to first order) an essentially local process determined by initial conditions.

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arXiv2019

StePS: A Multi-GPU Cosmological N-body Code for Compactified Simulations

We present the multi-GPU realization of the StePS (Stereographically Projected Cosmological Simulations) algorithm with MPI-OpenMP-CUDA hybrid parallelization and nearly ideal scale-out to multiple compute nodes. Our new zoom-in cosmological direct N-body simulation method simulates the infinite universe with unprecedented dynamic range for a given amount of memory and, in contrast to traditional periodic simulations, its fundamental geometry and topology match observations. By using a spherical geometry instead of periodic boundary conditions, and gradually decreasing the mass resolution with radius, our code is capable of running simulations with a few gigaparsecs in diameter and with a mass resolution of $\sim 10^{9}M_{\odot}$ in the center in four days on three compute nodes with four GTX 1080Ti GPUs in each. The code can also be used to run extremely fast simulations with reasonable resolution for fitting cosmological parameters. These simulations are useful for prediction needs of large surveys. The StePS code is publicly available for the research community.

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arXiv2018

Precision Prediction for the Cosmological Density Distribution

The distribution of matter in the universe is, to first order, lognormal. Improving this approximation requires characterization of the third moment (skewness) of the log density field. Thus, using Millennium Simulation phenomenology and building on previous work, we present analytic fits for the mean, variance, and skewness of the log density field $A$. We further show that a Generalized Extreme Value (GEV) distribution accurately models $A$; we submit that this GEV behavior is the result of strong intrapixel correlations, without which the smoothed distribution would tend (by the Central Limit Theorem) toward a Gaussian. Our GEV model yields cumulative distribution functions accurate to within 1.7 per cent for near-concordance cosmologies, over a range of redshifts and smoothing scales.

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arXiv2018

The Bias of the Log Power Spectrum for Discrete Surveys

A primary goal of galaxy surveys is to tighten constraints on cosmological parameters, and the power spectrum $P(k)$ is the standard means of doing so. However, at translinear scales $P(k)$ is blind to much of these surveys' information---information which the log density power spectrum recovers. For discrete fields (such as the galaxy density), $A^*$ denotes the statistic analogous to the log density: $A^*$ is a "sufficient statistic" in that its power spectrum (and mean) capture virtually all of a discrete survey's information. However, the power spectrum of $A^*$ is biased with respect to the corresponding log spectrum for continuous fields, and to use $P_{A^*}(k)$ to constrain the values of cosmological parameters, we require some means of predicting this bias. Here we present a prescription for doing so; for Euclid-like surveys (with cubical cells 16$h^{-1}$ Mpc across) our bias prescription's error is less than 3 per cent. This prediction will facilitate optimal utilization of the information in future galaxy surveys.

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arXiv2018

Density-dependent clustering: I. Pulling back the curtains on motions of the BAO peak

The most common statistic used to analyze large-scale structure surveys is the correlation function, or power spectrum. Here, we show how `slicing' the correlation function on local density brings sensitivity to interesting non-Gaussian features in the large-scale structure, such as the expansion or contraction of baryon acoustic oscillations (BAO) according to the local density. The sliced correlation function measures the large-scale flows that smear out the BAO, instead of just correcting them as reconstruction algorithms do. Thus, we expect the sliced correlation function to be useful in constraining the growth factor, and modified gravity theories that involve the local density. Out of the studied cases, we find that the run of the BAO peak location with density is best revealed when slicing on a $\sim 40$ Mpc/$h$ filtered density. But slicing on a $\sim100$ Mpc/$h$ filtered density may be most useful in distinguishing between underdense and overdense regions, whose BAO peaks are separated by a substantial $\sim 5$ Mpc/$h$ at $z=0$. We also introduce `curtain plots' showing how local densities drive particle motions toward or away from each other over the course of an $N$-body simulation.

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arXiv2018

Compactified Cosmological Simulations of the Infinite Universe

We present a novel $N$-body simulation method that compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to follow the evolution of the large-scale structure. Our approach eliminates the need for periodic boundary conditions, a mere numerical convenience which is not supported by observation and which modifies the law of force on large scales in an unrealistic fashion. We demonstrate that our method outclasses standard simulations executed on workstation-scale hardware in dynamic range, it is balanced in following a comparable number of high and low $k$ modes and, its fundamental geometry and topology match observations. Our approach is also capable of simulating an expanding, infinite universe in static coordinates with Newtonian dynamics. The price of these achievements is that most of the simulated volume has smoothly varying mass and spatial resolution, an approximation that carries different systematics than periodic simulations. Our initial implementation of the method is called StePS which stands for Stereographically Projected Cosmological Simulations. It uses stereographic projection for space compactification and naive $\mathcal{O}(N^2)$ force calculation which is nevertheless faster to arrive at a correlation function of the same quality than any standard (tree or P$^3$M) algorithm with similar spatial and mass resolution. The $N^2$ force calculation is easy to adapt to modern graphics cards, hence our code can function as a high-speed prediction tool for modern large-scale surveys. To learn about the limits of the respective methods, we compare StePS with GADGET-2 \citep{Gadget2_2005MNRAS.364.1105S} running matching initial conditions.

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arXiv2018

The integrated Sachs-Wolfe effect in the AvERA cosmology

The recent AvERA cosmological simulation of Rácz et al. (2017) has a $Λ\mathrm{CDM}$-like expansion history and removes the tension between local and Planck (cosmic microwave background) Hubble constants. We contrast the AvERA prediction of the integrated Sachs--Wolfe (ISW) effect with that of $Λ\mathrm{CDM}$. The linear ISW effect is proportional to the derivative of the growth function, thus it is sensitive to small differences in the expansion histories of the respective models. We create simulated ISW maps tracing the path of light-rays through the Millennium XXL cosmological simulation, and perform theoretical calculations of the ISW power spectrum. AvERA predicts a significantly higher ISW effect than $Λ\mathrm{CDM}$, $A=1.93-5.29$ times larger depending on the $l$ index of the spherical power spectrum, which could be utilized to definitively differentiate the models. We also show that AvERA predicts an opposite-sign ISW effect in the redshift range $z \approx 1.5 - 4.4$, in clear contrast with $Λ\mathrm{CDM}$. Finally, we compare our ISW predictions with previous observations. While at present these cannot distinguish between the two models due to large error bars, and lack of internal consistency suggesting systematics, ISW probes from future surveys will tightly constrain the models.

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arXiv2017

What does the N-point function hierarchy of the cosmological matter density field really measure ?

The cosmological dark matter field is not completely described by its hierarchy of $N$-point functions, a non-perturbative effect with the consequence that only part of the theory can be probed with the hierarchy. We give here an exact characterization of the joint information of the full set of $N$-point correlators of the lognormal field. The lognormal field is the archetypal example of a field where this effect occurs, and, at the same time, one of the few tractable and insightful available models to specify fully the statistical properties of the evolved matter density field beyond the perturbative regime. Nonlinear growth in the Universe in that model is set letting the log-density field probability density functional evolve keeping its Gaussian shape, according to the diffusion equation in Euclidean space. We show that the hierarchy probes a different evolution equation, the diffusion equation defined not in Euclidean space but on the compact torus, with uniformity as the long-term solution. The extraction of the hierarchy of correlators can be recast in the form of a nonlinear transformation applied to the field, 'wrapping', undergoing a sharp transition towards complete disorder in the deeply nonlinear regime, where all memory of the initial conditions is lost.

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arXiv2017

Concordance cosmology without dark energy

According to the separate universe conjecture, spherically symmetric sub-regions in an isotropic universe behave like mini-universes with their own cosmological parameters. This is an excellent approximation in both Newtonian and general relativistic theories. We estimate local expansion rates for a large number of such regions, and use a scale parameter calculated from the volume-averaged increments of local scale parameters at each time step in an otherwise standard cosmological $N$-body simulation. The particle mass, corresponding to a coarse graining scale, is an adjustable parameter. This mean field approximation neglects tidal forces and boundary effects, but it is the first step towards a non-perturbative statistical estimation of the effect of non-linear evolution of structure on the expansion rate. Using our algorithm, a simulation with an initial $Ω_m=1$ Einstein--de~Sitter setting closely tracks the expansion and structure growth history of the $Λ$CDM cosmology. Due to small but characteristic differences, our model can be distinguished from the $Λ$CDM model by future precision observations. Moreover, our model can resolve the emerging tension between local Hubble constant measurements and the Planck best-fitting cosmology. Further improvements to the simulation are necessary to investigate light propagation and confirm full consistency with cosmic microwave background observations.

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arXiv2016

Precision Prediction of the Log Power Spectrum

At translinear scales, the log power spectrum captures significantly more cosmological information than the standard power spectrum. At high wavenumbers $k$, the Fisher information in the standard power spectrum $P(k)$ fails to increase in proportion to $k$ in part due to correlations between large- and small-scale modes. As a result, $P(k)$ suffers from an information plateau on these translinear scales, so that analysis with the standard power spectrum cannot access the information contained in these small-scale modes. The log power spectrum $P_A(k)$, on the other hand, captures the majority of this otherwise lost information. Until now there has been no means of predicting the amplitude of the log power spectrum apart from cataloging the results of simulations. We here present a cosmology-independent prescription for the log power spectrum; this prescription displays accuracy comparable to that of Smith et al. (2003), over a range of redshifts and smoothing scales, and for wavenumbers up to $1.5h$ Mpc$^{-1}$.

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arXiv2016

The Rapid Transient Surveyor

The Rapid Transient Surveyor (RTS) is a proposed rapid-response, high-cadence adaptive optics (AO) facility for the UH 2.2-m telescope on Maunakea. RTS will uniquely address the need for high-acuity and sensitive near-infrared spectral follow-up observations of tens of thousands of objects in mere months by combining an excellent observing site, unmatched robotic observational efficiency, and an AO system that significantly increases both sensitivity and spatial resolving power. We will initially use RTS to obtain the infrared spectra of ~4,000 Type Ia supernovae identified by the Asteroid Terrestrial-Impact Last Alert System over a two year period that will be crucial to precisely measuring distances and mapping the distribution of dark matter in the z < 0.1 universe. RTS will comprise an upgraded version of the Robo-AO laser AO system and will respond quickly to target-of-opportunity events, minimizing the time between discovery and characterization. RTS will acquire simultaneous-multicolor images with an acuity of 0.07-0.10" across the entire visible spectrum (20% i'-band Strehl in median conditions) and <0.16" in the near infrared, and will detect companions at 0.5" at contrast ratio of ~500. The system will include a high-efficiency prism integral field unit spectrograph: R = 70-140 over a total bandpass of 840-1830 nm with an 8.7" by 6.0" field of view (0.15" spaxels). The AO correction boosts the infrared point-source sensitivity of the spectrograph against the sky background by a factor of seven for faint targets, giving the UH 2.2-m the H-band sensitivity of a 5.7-m telescope without AO.

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arXiv2015

The Impact of Non-Gaussianity upon Cosmological Forecasts

The primary science driver for 3D galaxy surveys is their potential to constrain cosmological parameters. Forecasts of these surveys' effectiveness typically assume Gaussian statistics for the underlying matter density, despite the fact that the actual distribution is decidedly non-Gaussian. To quantify the effect of this assumption, we employ an analytic expression for the power spectrum covariance matrix to calculate the Fisher information for BAO-type model surveys. We find that for typical number densities, at $k_\mathrm{max} = 0.5 h$ Mpc$^{-1}$, Gaussian assumptions significantly overestimate the information on all parameters considered, in some cases by up to an order of magnitude. However, after marginalizing over a six-parameter set, the form of the covariance matrix (dictated by $N$-body simulations) causes the majority of the effect to shift to the "amplitude-like" parameters, leaving the others virtually unaffected. We find that Gaussian assumptions at such wavenumbers can underestimate the dark energy parameter errors by well over 50 per cent, producing dark energy figures of merit almost 3 times too large. Thus, for 3D galaxy surveys probing the non-linear regime, proper consideration of non-Gaussian effects is essential.

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arXiv2015

On the information content of the matter power spectrum

We discuss an analytical approximation for the matter power spectrum covariance matrix and its inverse on translinear scales, $k \sim 0.1h - 0.8h/\textrm{Mpc}$ at $z = 0$. We proceed to give an analytical expression for the Fisher information matrix of the nonlinear density field spectrum, and derive implications for its cosmological information content. We find that the spectrum information is characterized by a pair of upper bounds, 'plateaux', caused by the trispectrum, and a 'knee' in the presence of white noise. The effective number of Fourier modes, normally growing as a power law, is bounded from above by these plateaux, explaining naturally earlier findings from $N$-body simulations. These plateaux limit best possible measurements of the nonlinear power at the percent level in a $h^{-3}\textrm{Gpc}^3$ volume; the extraction of model parameters from the spectrum is limited explicitly by their degeneracy to the nonlinear amplitude. The value of the first, super-survey (SS) plateau depends on the characteristic survey volume and the large scale power; the second, intra-survey (IS) plateau is set by the small scale power. While both have simple interpretations within the hierarchical \textit{Ansatz}, the SS plateau can be predicted and generalized to still smaller scales within Takada and Hu's spectrum response formalism. Finally, the noise knee is naturally set by the density of tracers.

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arXiv2015

Detection of a Supervoid Aligned with the Cold Spot of the Cosmic Microwave Background

We use the WISE-2MASS infrared galaxy catalog matched with Pan-STARRS1 (PS1) galaxies to search for a supervoid in the direction of the Cosmic Microwave Background Cold Spot. Our imaging catalog has median redshift $z\simeq 0.14$, and we obtain photometric redshifts from PS1 optical colours to create a tomographic map of the galaxy distribution. The radial profile centred on the Cold Spot shows a large low density region, extending over 10's of degrees. Motivated by previous Cosmic Microwave Background results, we test for underdensities within two angular radii, $5^\circ$, and $15^\circ$. The counts in photometric redshift bins show significantly low densities at high detection significance, $\gtrsim 5 σ$ and $\gtrsim 6 σ$, respectively, for the two fiducial radii. The line-of-sight position of the deepest region of the void is $z\simeq 0.15-0.25$. Our data, combined with an earlier measurement by Granett et al. 2010, are consistent with a large $R_{\rm void}=(220 \pm 50) h^{-1}Mpc $ supervoid with $δ_{m} \simeq -0.14 \pm 0.04$ centered at $z=0.22\pm0.03$. Such a supervoid, constituting at least a $\simeq 3.3σ$ fluctuation in a Gaussian distribution of the $ΛCDM$ model, is a plausible cause for the Cold Spot.

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arXiv2015

Star-galaxy separation strategies for WISE-2MASS all-sky infrared galaxy catalogs

We combine photometric information of the WISE and 2MASS all-sky infrared databases, and demonstrate how to produce clean and complete galaxy catalogs for future analyses. Adding 2MASS colors to WISE photometry improves star-galaxy separation efficiency substantially at the expense of loosing a small fraction of the galaxies. We find that 93% of the WISE objects within W1<15.2 mag have a 2MASS match, and that a class of supervised machine learning algorithms, Support Vector Machines (SVM), are efficient classifiers of objects in our multicolor data set. We constructed a training set from the SDSS PhotoObj table with known star-galaxy separation, and determined redshift distribution of our sample from the GAMA spectroscopic survey. Varying the combination of photometric parameters input into our algorithm we show that W1 - J is a simple and effective star-galaxy separator, capable of producing results comparable to the multi-dimensional SVM classification. We present a detailed description of our star-galaxy separation methods, and characterize the robustness of our tools in terms of contamination, completeness, and accuracy. We explore systematics of the full sky WISE-2MASS galaxy map, such as contamination from Moon glow. We show that the homogeneity of the full sky galaxy map is improved by an additional J<16.5 mag flux limit. The all-sky galaxy catalog we present in this paper covers 21,200 sq. degrees with dusty regions masked out, and has an estimated stellar contamination of 1.2% and completeness of 70.1% among 2.4 million galaxies with $z_{med}= 0.14$. WISE-2MASS galaxy maps with well controlled stellar contamination will be useful for spatial statistical analyses, including cross correlations with other cosmological random fields, such as the Cosmic Microwave Background. The same techniques also yield a statistically controlled sample of stars as well.

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arXiv2014

The impact of super-survey modes on cosmological constraints from cosmic shear fields

Owing to the mass-sheet degeneracy, cosmic shear maps do not probe directly the Fourier modes of the underlying mass distribution on scales comparable to the survey size and larger. To assess the corresponding effect on attainable cosmological parameter constraints, we quantify the information on super-survey modes in a lognormal model and, when interpreted as nuisance parameters, their degeneracies to cosmological parameters. Our analytical and numerical calculations clarify the central role of super-sample covariance (SSC) in shaping the statistical power of cosmological observables. Reconstructing the background modes from their non-Gaussian statistical dependence to small scales modes yields the renormalized convergence. This diagonalizes the spectrum covariance matrix, and the information content of the corresponding power spectrum is increased by a factor of two over standard methods. Unfortunately, careful calculation of the Cramer-Rao bound shows that the information recovery can never be made complete, any observable built from shear fields, including optimal sufficient statistics, are subject to severe information loss, typically $80\%$ to $90\%$ below $\ell \sim 3000$ for generic cosmological parameters. The lost information can only be recovered from additional, non-shear based data. Our predictions hold just as well for a tomographic analysis, and/or full sky surveys.

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