scholarly journals Assessing non-linear models for galaxy clustering – II. Model validation and forecasts for Stage IV surveys

2020 ◽  
Vol 493 (4) ◽  
pp. 5301-5322 ◽  
Author(s):  
Benjamin Bose ◽  
Alkistis Pourtsidou ◽  
Katarina Markovič ◽  
Florian Beutler
Keyword(s):  
Power Spectrum ◽  
Large Scale ◽  
Linear Models ◽  
Stage Iv ◽  
Multipole Expansion ◽  
Effective Field ◽  
Nuisance Parameters ◽  
Galaxy Clustering ◽  
Galaxy Surveys ◽  
Non Linear

ABSTRACT Accurate modelling of non-linear scales in galaxy clustering will be crucial for data analysis of Stage IV galaxy surveys. A selection of competing non-linear models must be made based on validation studies. We provide a comprehensive set of forecasts of two different models for the halo redshift space power spectrum, namely the commonly applied TNS model and an effective field theory of large-scale structure (EFTofLSS) inspired model. Using simulation data and a least-χ2 analysis, we determine ranges of validity for the models. We then conduct an exploratory Fisher analysis using the full anisotropic power spectrum to investigate parameter degeneracies. We proceed to perform an MCMC analysis utilizing the monopole, quadrupole, and hexadecapole spectra, with a restricted range of scales for the latter in order to avoid biasing our growth rate, f, constraint. We find that the TNS model with a Lorentzian damping and standard Eulerian perturbative modelling outperforms other variants of the TNS model. Our MCMC analysis finds that the EFTofLSS-based model may provide tighter marginalized constraints on f at z = 0.5 and z = 1 than the TNS model, despite having additional nuisance parameters. However this depends on the range of scales used as well as the fiducial values and priors on the EFT nuisance parameters. Finally, we extend previous work to provide a consistent comparison between the Fisher matrix and MCMC forecasts using the multipole expansion formalism, and find good agreement between them.

scholarly journals Hybrid MARMA-NARX model for flow forecasting based on the large-scale climate signals, sea-surface temperatures, and rainfall

2018 ◽  
Vol 49 (6) ◽  
pp. 1788-1803 ◽  
Author(s):  
Mohammad Ebrahim Banihabib ◽  
Arezoo Ahmadian ◽  
Mohammad Valipour
Keyword(s):  
Linear Model ◽  
Hybrid Model ◽  
Large Scale ◽  
Linear Models ◽  
Moving Average ◽  
Effective Parameters ◽  
Forecasting Accuracy ◽  
Local Factor ◽  
Non Linear ◽  
Climate Signals

Abstract In this study, to reflect the effect of large-scale climate signals on runoff, these indices are accompanied with rainfall (the most effective local factor in runoff) as the inputs of the hybrid model. Where one-year in advance forecasting of reservoir inflows can provide data to have an optimal reservoir operation, reports show we still need more accurate models which include all effective parameters to have more forecasting accuracy than traditional linear models (ARMA and ARIMA). Thus, hybridization of models was employed for improving the accuracy of flow forecasting. Moreover, various forecasters including large-scale climate signals were tested to promote forecasting. This paper focuses on testing MARMA-NARX hybrid model to enhance the accuracy of monthly inflow forecasts. Since the inflow in different periods of the year has in linear and non-linear trends, the hybrid model is proposed as a means of combining linear model, monthly autoregressive moving average (MARMA), and non-linear model, nonlinear autoregressive model with exogenous (NARX) inputs to upgrade the accuracy of flow forecasting. The results of the study showed enhanced forecasting accuracy through using the hybrid model.

scholarly journals Estimates for the impact of ultraviolet background fluctuations on galaxy clustering measurements

2019 ◽  
Vol 485 (4) ◽  
pp. 5059-5072 ◽  
Author(s):  
Phoebe Upton Sanderbeck ◽  
Vid Iršič ◽  
Matthew McQuinn ◽  
Avery Meiksin
Keyword(s):  
Power Spectrum ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Galaxy Surveys ◽  
Intensity Mapping ◽  
Redshift Galaxy ◽  
Halo Gas ◽  
The Cost ◽  
The Impact

ABSTRACT Spatial fluctuations in ultraviolet backgrounds can subtly modulate the distribution of extragalactic sources, a potential signal and systematic for large-scale structure surveys. While this modulation has been shown to be significant for 3D Ly α forest surveys, its relevance for other large-scale structure probes has been hardly explored, despite being the only astrophysical process that likely can affect clustering measurements on the scales of ≳Mpc. We estimate that the background fluctuations, modulating the amount of H i, have a fractional effect of (0.03–0.3) × (k/[10−2 Mpc−1])−1 on the power spectrum of 21 cm intensity maps at z = 1–3. We find a smaller effect for H α and Ly α intensity mapping surveys of (0.001–0.1) × (k/[10−2 Mpc−1])−1 and even smaller effect for more traditional surveys that correlate the positions of individual H α or Ly α emitters. We also estimate the effect of backgrounds on low-redshift galaxy surveys in general based on a simple model in which background fluctuations modulate the rate halo gas cools, modulating star formation: We estimate a maximum fractional effect on the power of ∼0.01 (k/[10−2 Mpc−1])−1 at z = 1. We compare sizes of these imprints to cosmological parameter benchmarks for the next generation of redshift surveys: We find that ionizing backgrounds could result in a bias on the squeezed triangle non-Gaussianity parameter fNL that can be larger than unity for power spectrum measurements with a SPHEREx-like galaxy survey, and typical values of intensity bias. Marginalizing over a shape of the form k−1PL, where PL is the linear matter power spectrum, removes much of this bias at the cost of ${\approx } 40{{\ \rm per\ cent}}$ larger statistical errors.

scholarly journals Power spectrum response of large-scale structure in 1D and in 3D: tests of prescriptions for post-collapse dynamics

2020 ◽  
Vol 499 (2) ◽  
pp. 1769-1787
Author(s):  
Anaëlle Halle ◽  
Takahiro Nishimichi ◽  
Atsushi Taruya ◽  
Stéphane Colombi ◽  
Francis Bernardeau
Keyword(s):  
Power Spectrum ◽  
Response Function ◽  
Large Scale ◽  
Initial Conditions ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Adaptive Smoothing ◽  
Single Stream ◽  
Non Linear ◽  
Spectrum Response

ABSTRACT The power spectrum response function of the large-scale structure of the Universe describes how the evolved power spectrum is modified by a small change in initial power through non-linear mode coupling of gravitational evolution. It was previously found that the response function for the coupling from small to large scales is strongly suppressed in amplitude, especially at late times, compared to predictions from perturbation theory (PT) based on the single-stream approximation. One obvious explanation for this is that PT fails to describe the dynamics beyond shell crossing. We test this idea by comparing measurements in N-body simulations to prescriptions based on PT but augmented with adaptive smoothing to account for the formation of non-linear structures of various sizes in the multistream regime. We first start with one-dimensional (1D) cosmology, where the Zel’dovich approximation provides the exact solution in the single-stream regime. Similarly to the three-dimensional (3D) case, the response function of the large-scale modes exhibits a strong suppression in amplitude at small scales that cannot be explained by the Zel’dovich solution alone. However, by performing adaptive smoothing of initial conditions to identify haloes of different sizes and solving approximately post-collapse dynamics in the three-stream regime, agreement between theory and simulations drastically improves. We extend our analyses to the 3D case using the pinocchio algorithm, in which similar adaptive smoothing is implemented on the Lagrangian PT fields to identify haloes and is combined with a spherical halo prescription to account for post-collapse dynamics. Again, a suppression is found in the coupling between small- and large-scale modes and the agreement with simulations is improved.

scholarly journals Constraining the growth rate of structure with phase correlations

2020 ◽  
Vol 497 (2) ◽  
pp. 1765-1790
Author(s):  
Joyce Byun ◽  
Felipe Oliveira Franco ◽  
Cullan Howlett ◽  
Camille Bonvin ◽  
Danail Obreschkow
Keyword(s):  
Growth Rate ◽  
Correlation Function ◽  
Power Spectrum ◽  
Large Scale ◽  
Large Scale Structure ◽  
Density Field ◽  
Galaxy Surveys ◽  
Additional Information ◽  
Forecasting Method ◽  
The Galaxy

ABSTRACT We show that correlations between the phases of the galaxy density field in redshift space provide additional information about the growth rate of large-scale structure that is complementary to the power-spectrum multipoles. In particular, we consider the multipoles of the line correlation function (LCF), which correlates phases between three collinear points, and use the Fisher forecasting method to show that the LCF multipoles can break the degeneracy between the measurement of the growth rate of structure f and the amplitude of perturbations σ8 that is present in the power-spectrum multipoles at large scales. This leads to an improvement in the measurement of f and σ8 by up to 220 per cent for $k_{\rm max} = 0.15 \, h\, \mathrm{Mpc}^{-1}$ and up to 50 per cent for $k_{\rm max} = 0.30 \, h\, \mathrm{Mpc}^{-1}$ at redshift z = 0.25, with respect to power-spectrum measurements alone for the upcoming generation of galaxy surveys like DESI and Euclid. The average improvements in the constraints on f and σ8 for $k_{\rm max} = 0.15 \, h\, \mathrm{Mpc}^{-1}$ are ∼90 per cent for the DESI BGS sample with mean redshift $\overline{z}=0.25$, ∼40 per cent for the DESI ELG sample with $\overline{z}=1.25$, and ∼40 per cent for the Euclid Hα galaxies with $\overline{z}=1.3$. For $k_{\rm max} = 0.30 \, h\, \mathrm{Mpc}^{-1}$, the average improvements are ∼40 per cent for the DESI BGS sample and ∼20 per cent for both the DESI ELG and Euclid Hα galaxies.

scholarly journals Power spectrum of halo intrinsic alignments in simulations

2020 ◽  
Vol 501 (1) ◽  
pp. 833-852
Author(s):  
Toshiki Kurita ◽  
Masahiro Takada ◽  
Takahiro Nishimichi ◽  
Ryuichi Takahashi ◽  
Ken Osato ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Large Scale ◽  
Signal To Noise Ratio ◽  
Cosmological Parameters ◽  
Three Dimensional ◽  
Power Spectra ◽  
Acoustic Oscillations ◽  
Matter Power Spectrum ◽  
Sample Covariance ◽  
Non Linear

ABSTRACT We use a suite of N-body simulations to study intrinsic alignments (IA) of halo shapes with the surrounding large-scale structure in the ΛCDM model. For this purpose, we develop a novel method to measure multipole moments of the three-dimensional power spectrum of the E-mode field of halo shapes with the matter/halo distribution, $P_{\delta E}^{(\ell)}(k)$ (or $P^{(\ell)}_{{\rm h}E}$), and those of the auto-power spectrum of the E-mode, $P^{(\ell)}_{EE}(k)$, based on the E/B-mode decomposition. The IA power spectra have non-vanishing amplitudes over the linear to non-linear scales, and the large-scale amplitudes at k ≲ 0.1 h−1 Mpc are related to the matter power spectrum via a constant coefficient (AIA), similar to the linear bias parameter of galaxy or halo density field. We find that the cross- and auto-power spectra PδE and PEE at non-linear scales, k ≳ 0.1 h−1 Mpc, show different k-dependences relative to the matter power spectrum, suggesting a violation of the non-linear alignment model commonly used to model contaminations of cosmic shear signals. The IA power spectra exhibit baryon acoustic oscillations, and vary with halo samples of different masses, redshifts, and cosmological parameters (Ωm, S8). The cumulative signal-to-noise ratio for the IA power spectra is about 60 per cent of that for the halo density power spectrum, where the super-sample covariance is found to give a significant contribution to the total covariance. Thus our results demonstrate that the IA power spectra of galaxy shapes, measured from imaging and spectroscopic surveys for an overlapping area of the sky, can be used to probe the underlying matter power spectrum, the primordial curvature perturbations, and cosmological parameters, in addition to the standard galaxy density power spectrum.

scholarly journals Minimising the impact of scale-dependent galaxy bias on the joint cosmological analysis of large scale structures

2020 ◽  
Author(s):  
Marika Asgari ◽  
Indiarose Friswell ◽  
Mijin Yoon ◽  
Catherine Heymans ◽  
Andrej Dvornik ◽  
...  
Keyword(s):  
Large Scale ◽  
Cosmological Parameter ◽  
Galaxy Surveys ◽  
Large Scale Structures ◽  
Non Linear ◽  
Point Correlation ◽  
Galaxy Bias ◽  
New Statistics ◽  
The Impact ◽  
Parameter Constraints

Abstract We present a mitigation strategy to reduce the impact of non-linear galaxy bias on the joint ‘3 × 2pt’ cosmological analysis of weak lensing and galaxy surveys. The Ψ-statistics that we adopt are based on Complete Orthogonal Sets of E/B Integrals (COSEBIs). As such they are designed to minimize the contributions to the observable from the smallest physical scales where models are highly uncertain. We demonstrate that Ψ-statistics carry the same constraining power as the standard two-point galaxy clustering and galaxy-galaxy lensing statistics, but are significantly less sensitive to scale-dependent galaxy bias. Using two galaxy bias models, motivated by halo-model fits to data and simulations, we quantify the error in a standard 3 × 2pt analysis where constant galaxy bias is assumed. Even when adopting conservative angular scale cuts, that degrade the overall cosmological parameter constraints, we find of order 1σ biases for Stage III surveys on the cosmological parameter S8 = σ8(Ωm/0.3)α. This arises from a leakage of the smallest physical scales to all angular scales in the standard two-point correlation functions. In contrast, when analysing Ψ-statistics under the same approximation of constant galaxy bias, we show that the bias on the recovered value for S8 can be decreased by a factor of ∼2, with less conservative scale cuts. Given the challenges in determining accurate galaxy bias models in the highly non-linear regime, we argue that 3 × 2pt analyses should move towards new statistics that are less sensitive to the smallest physical scales.

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