Redshift Bins Research Articles

Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory

We present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.78 and σ 8 = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.77 and σ 8 = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ωm and H 0 are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low σ 8 value are driven by cross correlations with CMB lensing in the low redshift bin (z ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.

HSC Year 1 cosmology results with the minimal bias method: HSC×BOSS galaxy-galaxy weak lensing and BOSS galaxy clustering

We present cosmological parameter constraints from a blinded joint analysis of galaxy-galaxy weak lensing, $\Delta\!\Sigma(R)$, and projected correlation function, $w_\mathrm{p}(R)$, measured from the first-year HSC (HSC-Y1) data and SDSS spectroscopic galaxies over $0.15<z<0.7$. We use luminosity-limited samples as lens samples for $\Delta\!\Sigma$ and as large-scale structure tracers for $w_\mathrm{p}$ in three redshift bins, and use the HSC-Y1 galaxy catalog to define a secure sample of source galaxies at $z_\mathrm{ph}>0.75$ for the $\Delta\!\Sigma$ measurements, selected based on their photometric redshifts. For theoretical template, we use the "minimal bias" model for the cosmological clustering observables for the flat $\Lambda$CDM cosmological model. We compare the model predictions with the measurements in each redshift bin on large scales, $R>12$ and $8~h^{-1}\mathrm{Mpc}$ for $\Delta\!\Sigma(R)$ and $w_\mathrm{p}(R)$, respectively, where the perturbation theory-inspired model is valid. When we employ weak priors on cosmological parameters, without CMB information, we find $S_8=0.936^{+0.092}_{-0.086}$, $\sigma_8=0.85^{+0.16}_{-0.11}$, and $\Omega_\mathrm{m}=0.283^{+0.12}_{-0.035}$ for the flat $\Lambda$CDM model. Although the central value of $S_8$ appears to be larger than those inferred from other cosmological experiments, we find that the difference is consistent with expected differences due to sample variance, and our results are consistent with the other results to within the statistical uncertainties. (abriged)

Groups and Protocluster Candidates in the CLAUDS and HSC-SSP Joint Deep Surveys

Using the extended halo-based group finder developed by Yang et al., which is able to deal with galaxies via spectroscopic and photometric redshifts simultaneously, we construct galaxy group and candidate protocluster catalogs in a wide redshift range (0 < z < 6) from the joint CFHT Large Area U-band Deep Survey and Hyper Suprime-Cam Subaru Strategic Program deep data set. Based on a selection of 5,607,052 galaxies with i-band magnitude m i < 26 and a sky coverage of 34.41 deg2, we identify a total of 2,232,134 groups, of which 402,947 groups have at least three member galaxies. We have visually checked and discussed the general properties of these richest groups at redshift z > 2.0. By checking the galaxy number distributions within a 5–7 h −1Mpc projected separation and a redshift difference Δz ≤ 0.1 around those richest groups at redshift z > 2, we identify lists of 761, 343, and 43 protocluster candidates in the redshift bins 2 ≤ z < 3, 3 ≤ z < 4, and z ≥ 4, respectively. In general, these catalogs of galaxy groups and protocluster candidates will provide useful environmental information in probing galaxy evolution along cosmic time.

Accretion history of AGN: Estimating the host galaxy properties in X-ray luminous AGN from z = 0–3

ABSTRACT We aim to determine the intrinsic far-Infrared (far-IR) emission of X-ray-luminous quasars over cosmic time. Using a 16 deg2 region of the Stripe 82 field surveyed by XMM-Newton and Herschel Space Observatory, we identify 2905 X-ray luminous (LX &amp;gt; 1042 erg/s) active galactic nuclei (AGN) in the range z ≈ 0–3. The IR is necessary to constrain host galaxy properties such as star formation rate (SFR) and gas mass. However, only 10 per cent of our AGN are detected both in the X-ray and IR. Because 90 per cent of the sample is undetected in the far-IR by Herschel, we explore the mean IR emission of these undetected sources by stacking their Herschel/SPIRE images in bins of X-ray luminosity and redshift. We create stacked spectral energy distributions from the optical to the far-IR, and estimate the median SFR, dust mass, stellar mass, and infrared luminosity using a fitting routine. We find that the stacked sources on average have similar SFR/Lbol ratios as IR detected sources. The majority of our sources fall on or above the main sequence line suggesting that X-ray selection alone does not predict the location of a galaxy on the main sequence. We also find that the gas depletion time scales of our AGN are similar to those of dusty star forming galaxies. This suggests that X-ray selected AGN host high star formation and that there are no signs of declining star formation.

PT challenge: validation of ShapeFit on large-volume, high-resolution mocks

The ShapeFit compression method has been shown to be a powerful tool to gain cosmological information from galaxy power spectra in an effective, model-independent way. Here we present its performance on the blind PT challenge mock products presented in [1]. Choosing a set-up similar to that of other participants to the blind challenge we obtained Δln(1010 As ) = -0.018 ± 0.014, ΔΩm = 0.0039 ± 0.0021 and Δh = -0.0009 ± 0.0034, remaining below 2σ deviations for a volume of 566 [h -1Gpc]3. This corresponds to a volume 10 times larger than the volume probed by future galaxy surveys. We also present an analysis of these mocks oriented towards an actual data analysis using the full redshift evolution, using all three redshift bins z 1 = 0.38, z 2 = 0.51, and z 3 = 0.61, and exploring different set-ups to quantify the impact of choices or assumptions on noise, bias, scale range, etc. We find consistency across reasonable changes in set-up and across redshifts and that, as expected, mapping the redshift evolution of clustering helps constraining cosmological parameters within a given model.

A cosmological distance measure using radio-loud quasars

ABSTRACT We use the X-ray luminosity relation of radio-loud quasars (RLQs) to measure these luminosity distances as well as estimate cosmological parameters. We adopt four parametric models of X-ray luminosity to test luminosity correlation for RLQs and radio-intermediate quasars (RIQs) and give these cosmological distances. By Bayesian information criterion (BIC), the data suggest that the luminosity relation ${L_X} \propto L_{\rm UV}^{{\gamma _{\rm uv}}}L_{\rm Radio}^{\gamma _{\rm radio}^{\prime }}$ for RLQs has a better goodness of fit, relative to other models, which can be interpreted as this relation being preferred for RLQs. Meanwhile, we compare the results from flat-spectrum radio-loud quasars (FSRLQs) and steep-spectrum radio-loud quasars (SSRLQs), which indicate that their luminosity correlations are not exactly the same. We also consider dividing the RLQ sample into various redshift bins, which can be used to check if the X-ray luminosity relation depends on the redshift. Finally, we apply a combination of RLQs and SN Ia Pantheon to verify the nature of dark energy concerning whether or not its density deviates from the constant, and give the statistical results.

The star formation rates of QSOs

ABSTRACT We examine the far-infrared (FIR) properties of a sample of 5391 optically selected QSOs in the 0.5 &amp;lt; z &amp;lt; 2.65 redshift range down to log [νLν, 2500(erg s−1)] &amp;gt; 44.7, using SPIRE data from Herschel-ATLAS. We split the sample in a grid of 74 luminosity–redshift bins and compute the average optical–IR spectral energy distribution (SED) in each bin. By normalizing an intrinsic active galactic nucleus (AGN) template to the AGN optical power (at 5100 Å), we decompose the total IR emission (LIR; 8–1000 µm) into an AGN (LIR, AGN) and star-forming component (LIR, SF). We find that the AGN contribution to LIR increases as a function of AGN power, manifesting as a reduction of the ‘FIR bump’ in the average QSO SEDs. We note that LIR, SF does not correlate with AGN power; the mean star formation rates (SFRs) of AGN host galaxies are a function of redshift only and they range from ∼6 M⊙ yr−1 at z ∼ 0 to a plateau of ≲ 200 M⊙ yr−1 at z ∼ 2.6. Our results indicate that the accuracy of FIR emission as a proxy for SFR decreases with increasing AGN luminosity. We show that, at any given redshift, observed trends between IR luminosity (whether monochromatic or total) and AGN power (in the optical or X-rays) can be explained by a simple model which is the sum of two components: (i) the IR emission from star formation, uncorrelated with AGN power and (ii) the IR emission from AGN, directly proportional to AGN power in the optical or X-rays.

Galaxy blending effects in deep imaging cosmic shear probes of cosmology

ABSTRACT Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalogue consisting of galaxies at a depth equivalent to 1.3 yr of the full 10-yr Rubin Observatory that includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogues from imaging data. The emulated catalogue indicates that approximately 12 per cent of the observed galaxies are ‘unrecognized’ blends that contain two or more objects but are detected as one. Using the positions and shears of half a billion distant galaxies, we compute shear–shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. An ∼0.025 decrease in the derived structure growth parameter S8 = σ8(Ωm/0.3)0.5 is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-z-based tomography. This bias is greater than the 2σ statistical error in measuring S8.

Constraining low redshift [C II] emission by cross-correlating FIRAS and BOSS data

ABSTRACT We perform a tomographic cross-correlation analysis of archival FIRAS data and the BOSS galaxy redshift survey to constrain the amplitude of [C II] 2P3/2 → 2P1/2 fine structure emission. Our analysis employs spherical harmonic tomography (SHT), which is based on the angular cross-power spectrum between FIRAS maps and BOSS galaxy over-densities at each pair of redshift bins, over a redshift range of 0.24 &amp;lt; z &amp;lt; 0.69. We develop the SHT approach for intensity mapping, where it has several advantages over existing power spectral estimators. Our analysis constrains the product of the [C II] bias and [C II] specific intensity, $b_{\rm [C \small{\rm II}]}I_{\rm [C \small{\rm II}]}$, to be &amp;lt;0.31 MJy/sr at z ≈ 0.35 and &amp;lt;0.28 MJy/sr at z ≈ 0.57 at $95{{\ \rm per\ cent}}$ confidence. These limits are consistent with most current models of the [C II] signal, as well as with higher-redshift [C II] cross-power spectrum measurements from the Planck satellite and BOSS quasars. We also show that our analysis, if applied to data from a more sensitive instrument such as the proposed PIXIE satellite, can detect pessimistic [C II] models at high significance.

Detecting Baryon Acoustic Oscillations with Third-generation Gravitational Wave Observatories

We explore the possibility of detecting baryon acoustic oscillations (BAO) solely from gravitational wave (GW) observations of binary neutron star mergers with third-generation (3G) GW detectors such as the Cosmic Explorer and the Einstein Telescope. These measurements would provide a new independent probe of cosmology. The detection of the BAO peak with current-generation GW detectors (solely from GW observations) is not possible because i) unlike galaxies, the GW mergers are poorly localized, and ii) there are not enough merger events to probe the BAO length scale. With the 3G GW detector network, it is possible to observe binary neutron star mergers per year that are localized well within one square degree in the sky for redshift z ≤ 0.3. We show that 3G observatories will enable precision measurements of the BAO feature in the large-scale two-point correlation function; the effect of BAO can be independently detected at different redshifts, with a log-evidence ratio of ∼23, 17, or 3, favoring a model with a BAO peak at redshift of 0.2, 0.25, or 0.3, respectively, using a redshift bin corresponding to a shell of thickness 150h −1 Mpc.

Cosmology in the non-linear regime: the small scale miracle

Interest is rising in exploiting the full shape information of the galaxy power spectrum, and in pushing analyses to smaller non-linear scales. Here I use the halo model to quantify the information content in the tomographic angular power spectrum of galaxies Cℓgal(iz) for the future high-resolution surveys Euclid and SKA2. I study how this information varies as a function of the scale cut applied, either with angular cut ℓmax or physical cut kmax. For this, I use analytical covariances with the most complete census of non-Gaussian terms, which proves to be critical. I find that the Fisher information on most cosmological and astrophysical parameters shows a striking behaviour. Beyond the perturbative regime, we first get decreasing returns: the information continues to rise but the slope slows down until reaching saturation. The location of this plateau, at k ∼ 2 Mpc−1, is slightly beyond the reach of current modelling methods and depends to some extent on the parameter and redshift bin considered. I explain the origin of this plateau, which is due to non-linear effects both on the power spectrum, and more importantly on non-Gaussian covariance terms. Then, pushing further, we see the information rising again in the highly non-linear regime, with a steep slope. This is the small-scale miracle, for which I give my interpretation and discuss the properties. There are suggestions that it may be possible to disentangle this information from the astrophysical content, and improve dark energy constraints. Finally, more hints are shown that high-order statistics may yield significant improvements over the power spectrum in this regime, with the improvements increasing with kmax.

The miniJPAS survey: Identification and characterization of the emission line galaxies down to z &lt; 0.35 in the AEGIS field

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is expected to map thousands of square degrees of the northern sky with 56 narrowband filters (spectral resolution of R ∼ 60) in the upcoming years. This resolution allows us to study emission line galaxies (ELGs) with a minimum equivalent width of 10 Å in the Hα emission line for a median signal-to-noise ratio (S/N) of 5. This will make J-PAS a very competitive and unbiased emission line survey compared to spectroscopic or narrowband surveys with fewer filters. The miniJPAS survey covered 1 deg2, and it used the same photometric system as J-PAS, but the observations were carried out with the pathfinder J-PAS camera. In this work, we identify and characterize the sample of ELGs from miniJPAS with a redshift lower than 0.35, which is the limit to which the Hα line can be observed with the J-PAS filter system. Using a method based on artificial neural networks, we detect the ELG population and measure the equivalent width and flux of the Hα, Hβ, [O III], and [N II] emission lines. We explore the ionization mechanism using the diagrams [OIII]/Hβ versus [NII]/Hα (BPT) and EW(Hα) versus [NII]/Hα (WHAN). We identify 1787 ELGs (83%) from the parent sample (2154 galaxies) in the AEGIS field. For the galaxies with reliable EW values that can be placed in the WHAN diagram (2000 galaxies in total), we obtained that 72.8 ± 0.4%, 17.7 ± 0.4%, and 9.4 ± 0.2% are star-forming (SF), active galactic nucleus (Seyfert), and quiescent galaxies, respectively. The distribution of EW(Hα) is well correlated with the bimodal color distribution of galaxies. Based on the rest-frame (u − r)–stellar mass diagram, 94% of the blue galaxies are SF galaxies, and 97% of the red galaxies are LINERs or passive galaxies. The nebular extinction and star formation rate (SFR) were computed from the Hα and Hβ fluxes. We find that the star formation main sequence is described as log SFR [M⊙ yr−1] = 0.90−0.02+0.02 log M⋆[M⊙]−8.85−0.20+0.19 and has an intrinsic scatter of 0.20−0.01+0.01. The cosmic evolution of the SFR density (ρSFR) is derived at three redshift bins: 0 &lt; z ≤ 0.15, 0.15 &lt; z ≤ 0.25, and 0.25 &lt; z ≤ 0.35, which agrees with previous results that were based on measurements of the Hα emission line. However, we find an offset with respect to other estimates that were based on the star formation history obtained from fitting the spectral energy distribution of the stellar continuum. We discuss the origin of this discrepancy, which is probably a combination of several factors: the escape of ionizing photons, the SFR tracers, and dust attenuation, among others.

A Flexible Method for Estimating Luminosity Functions via Kernel Density Estimation. II. Generalization and Python Implementation

We propose a generalization of our previous kernel density estimation (KDE) method for estimating luminosity functions (LFs). This new upgrade further extends the application scope of our KDE method, making it a very flexible approach that is suitable to deal with most bivariate LF calculation problems. From the mathematical point of view, usually the LF calculation can be abstracted as a density estimation problem in the bounded domain of . We use the transformation-reflection KDE method () to solve the problem, and introduce an approximate method () based on one-dimensional KDE to deal with the small sample size case. In practical applications, the different versions of LF estimators can be flexibly chosen according to the Kolmogorov–Smirnov test criterion. Based on 200 simulated samples, we find that for both cases of dividing or not dividing redshift bins, especially for the latter, our method performs significantly better than the traditional binning method . Moreover, with the increase of sample size n, our LF estimator converges to the true LF remarkably faster than . To implement our method, we have developed a public, open-source Python toolkit, called kdeLF. With the support of kdeLF, our KDE method is expected to be a competitive alternative to existing nonparametric estimators, due to its high accuracy and excellent stability. kdeLF is available online at GitHub with further extensive documentation available.

Dark Energy Survey Year 3 results: Exploiting small-scale information with lensing shear ratios

Using the first three years of data from the Dark Energy Survey (DES), we use ratios of small-scale galaxy-galaxy lensing measurements around the same lens sample to constrain source redshift uncertainties, intrinsic alignments and other systematics or nuisance parameters of our model. Instead of using a simple geometric approach for the ratios as has been done in the past, we use the full modeling of the galaxy-galaxy lensing measurements, including the corresponding integration over the power spectrum and the contributions from intrinsic alignments and lens magnification. We perform extensive testing of the small-scale shear-ratio (SR) modeling by studying the impact of different effects such as the inclusion of baryonic physics, nonlinear biasing, halo occupation distribution descriptions and lens magnification, among others, and using realistic N-body simulations of the DES data. We validate the robustness of our constraints in the data by using two independent lens samples with different galaxy properties, and by deriving constraints using the corresponding large-scale ratios for which the modeling is simpler. The results applied to the DES Y3 data demonstrate how the ratios provide significant improvements in constraining power for several nuisance parameters in our model, especially on source redshift calibration and intrinsic alignments. For source redshifts, SR improves the constraints from the prior by up to 38% in some redshift bins. Such improvements, and especially the constraints it provides on intrinsic alignments, translate to tighter cosmological constraints when shear ratios are combined with cosmic shear and other 2pt functions. In particular, for the DES Y3 data, SR improves S8 constraints from cosmic shear by up to 31%, and for the full combination of probes (3×2pt) by up to 10%. The shear ratios presented in this work are used as an additional likelihood for cosmic shear, 2×2pt and the full 3×2pt in the fiducial DES Y3 cosmological analysis.10 MoreReceived 3 June 2021Accepted 7 March 2022DOI:https://doi.org/10.1103/PhysRevD.105.083529© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasCosmological parametersCosmologyDark energyDark matterGravitational lensesLarge scale structure of the UniverseOptical, UV, & IR astronomyGravitation, Cosmology & Astrophysics

The physical origin of dark energy constraints from rubin observatory and CMB-S4 lensing tomography

ABSTRACT We seek to clarify the origin of constraints on the dark energy equation of state parameter from CMB lensing tomography, that is the combination of galaxy clustering and the cross-correlation of galaxies with CMB lensing in a number of redshift bins. We focus on the analytic understanding of the origin of the constraints. Dark energy information in these data arises from the influence of three primary relationships: distance as a function of redshift (geometry), the amplitude of the power spectrum as a function of redshift (growth), and the power spectrum as a function of wavenumber (shape). We find that the effects from geometry and growth play a significant role and partially cancel each other out, while the shape effect is unimportant. We also show that Dark Energy Task Force figure of merit forecasts from the combination of LSST galaxies and CMB-S4 lensing are comparable to the forecasts from cosmic shear in the absence of the CMB lensing map, thus providing an important independent check. Compared to the forecasts with the LSST galaxies alone, combining CMB lensing and LSST clustering information increases the FoM by roughly a factor of 3–4 in the optimistic scenario where systematics are fully under control. We caution that achieving these forecasts will likely require a full analysis of higher-order biasing, photometric redshift uncertainties, and stringent control of other systematic limitations, which are outside the scope of this work, whose primary purpose is to elucidate the physical origin of the constraints.

Prospects for kSZ2–Galaxy Cross-correlations during Reionization

Abstract We explore a new approach for extracting reionization-era contributions to the kinetic Sunyaev–Zel’dovich (kSZ) effect. Our method utilizes the cross-power spectrum between filtered and squared maps of the cosmic microwave background (CMB) and photometric galaxy surveys during the Epoch of Reionization (EoR). This kSZ2–galaxy cross-power spectrum statistic has been successfully detected at lower redshifts (z ≲ 1.5). Here we extend this method to z ≳ 6 as a potential means to extract signatures of patchy reionization. We model the expected signal across multiple photometric redshift bins using seminumeric simulations of the reionization process. In principle, the cross-correlation statistic robustly extracts reionization-era contributions to the kSZ signal, while its redshift evolution yields valuable information regarding the timing of reionization. Specifically, the model cross-correlation signal near ℓ ∼ 1000 peaks during the early stages of the EoR, when about 20% of the volume of the universe is ionized. Detectable ℓ modes mainly reflect squeezed-triangle configurations of the related bispectrum, quantifying correlations between the galaxy overdensity field on large scales and the smaller-scale kSZ power. We forecast the prospects for detecting this signal using future wide-field samples of Lyman-break galaxies from the Roman Space Telescope and next-generation CMB surveys including the Simons Observatory, CMB-S4, and CMB-HD. We find that a roughly 13σ detection is possible for CMB-HD and Roman after summing over all ℓ modes. We discuss the possibilities for improving this approach and related statistics, with the aim of moving beyond simple detections to measure the scale and redshift dependence of the cross-correlation signals.

MIGHTEE-H i: the H i size–mass relation over the last billion years

ABSTRACT We present the observed H i size–mass relation of 204 galaxies from the MIGHTEE Survey Early Science data. The high sensitivity of MeerKAT allows us to detect galaxies spanning more than 4 orders of magnitude in H i mass, ranging from dwarf galaxies to massive spirals, and including all morphological types. This is the first time the relation has been explored on a blind homogeneous data set that extends over a previously unexplored redshift range of 0 &amp;lt; z &amp;lt; 0.084, i.e. a period of around one billion years in cosmic time. The sample follows the same tight logarithmic relation derived from previous work, between the diameter ($D_{\rm H\, \small {\rm I}}$) and the mass ($M_{\rm H\, \small {\rm I}}$) of H i discs. We measure a slope of 0.501 ± 0.008, an intercept of $-3.252^{+0.073}_{-0.074}$, and an observed scatter of 0.057 dex. For the first time, we quantify the intrinsic scatter of 0.054 ± 0.003 dex (${\sim } 10 {{\ \rm per\ cent}}$), which provides a constraint for cosmological simulations of galaxy formation and evolution. We derive the relation as a function of galaxy type and find that their intrinsic scatters and slopes are consistent within the errors. We also calculate the $D_{\rm H\, \small {\rm I}}{ \!-\! }M_{\rm H\, \small {\rm I}}$ relation for two redshift bins and do not find any evidence for evolution with redshift. These results suggest that over a period of one billion years in look-back time, galaxy discs have not undergone significant evolution in their gas distribution and mean surface mass density, indicating a lack of dependence on both morphological type and redshift.

Precision analysis of the redshift-space galaxy bispectrum

We study the information content of the angle-averaged (monopole) redshift space galaxy bispectrum. The main novelty of our approach is the use of a systematic tree-level perturbation theory model that includes galaxy bias, IR resummation, and also accounts for nonlinear redshift space distortions, binning, and projection effects. We analyze data from the PT challenge simulations, whose cumulative volume of 566 $h^{-3}$Gpc$^3$ allows for a precise comparison to theoretical predictions. Fitting the power spectrum and bispectrum of our simulated data, and varying all necessary cosmological and nuisance parameters in a consistent Markov chain Monte Carlo analysis, we find that our tree-level bispectrum model is valid up to $k_{\max}=0.08~h{\rm Mpc}^{-1}$ (at $z=0.61$). We also find that inclusion of the bispectrum monopole improves constraints on cosmological parameters by $(5-15)\%$ relative to the power spectrum. The improvement is more significant for the quadratic bias parameters of our simulated galaxies, which we also show to deviate from biases of the host dark matter halos at the $\sim 3\sigma$ level. Finally, we adjust the covariance and scale cuts to match the volume of the BOSS survey, and estimate that within the minimal $\Lambda$CDM model the bispectrum data can tighten the constraint on the mass fluctuation amplitude $\sigma_8$ by roughly $10\%$.

Fast radio bursts as probes of feedback from active galactic nuclei

ABSTRACT Fast radio bursts (FRBs) are a promising tool for studying the low-density universe as their dispersion measures (DM) are extremely sensitive probes of electron column density. Active galactic nuclei (AGN) inject energy into the intergalactic medium, affecting the DM and their scatter. To determine the effectiveness of FRBs as a probe of AGN feedback, we analysed three different AGN models from the EAGLE simulation series. We measured the mean DM–redshift relation, and the scatter around it, using 2.56 × 108 sightlines at 131 redshift (z) bins between 0 ≤ z ≤ 3. While the DM–redshift relation itself is highly robust against different AGN feedback models, significant differences are detected in the scatter around the mean: weaker feedback leads to more scatter. We find that ∼104 localized FRBs are needed to discriminate between the scatter in standard feedback and stronger, more intermittent feedback models. The number of FRBs required is dependent on the redshift distribution of the detected population. A lognormal redshift distribution at z = 0.5 requires approximately 50 per cent fewer localized FRBs than a distribution centred at z = 1. With the Square Kilometre Array expected to detect &amp;gt;103 FRBs per day, in the future, FRBs will be able to provide constraints on AGN feedback.

The 6 × 2pt method: supernova velocities meet multiple tracers

ABSTRACT We present a new methodology to analyse in a comprehensive way large-scale and supernova (or any other distance indicator) surveys. Our approach combines galaxy and supernova position and redshift data with supernova peculiar velocities, obtained through their magnitude scatter, to construct a 6 × 2pt analysis that includes six power spectra. The 3 × 3 correlation matrix of these spectra expresses exhaustively the information content of the surveys at the linear level. We then proceed to forecast the performance of future surveys like Legacy Survey of Space and Time and 4MOST with a Fisher matrix analysis, adopting both a model-dependent and a model-independent approach. We compare the performance of the 6 × 2pt approach to that of the traditional one using only galaxy clustering and some recently proposed combinations of galaxy and supernova data and quantify the possible gains by optimally extracting the linear information. We show that the 6 × 2pt method shrinks the uncertainty area in the $\sigma _8, \, \gamma$ plane by more than half when compared to the traditional method. The combined clustering and velocity data on the growth of structures have uncertainties at similar levels to those of the cosmic microwave background but exhibit orthogonal degeneracies, and the combined constraints yield improvements of factors of 5 or more in each of the five cosmological parameters considered here. Concerning the model-independent results, we find that our method can improve the constraints on H(z)/H0 in all redshift bins by more than 70 per cent with respect to the galaxy clustering alone and by 30 per cent when supernova velocities (but not clustering) are considered, reaching a precision of 3–4 per cent at high redshifts.