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We build a deep learning framework that connects the local formation process of dark matter haloes to the halo bias. We train a convolutional neural network (CNN) to predict the final mass and concentration of dark matter haloes from the initial conditions. The CNN is then used as a surrogate model to derive the response of the haloes' mass and concentration to long-wavelength perturbations in the initial conditions, and consequently the halo bias parameters following the 'response bias' definition. The CNN correctly predicts how the local properties of dark matter haloes respond to changes in the large-scale environment, despite no explicit knowledge of halo bias being provided during training. We show that the CNN recovers the known trends for the linear and second-order density bias parameters b 1 and b 2, as well as for the local primordial non-Gaussianity linear bias parameter b ϕ. The expected secondary assembly bias dependence on halo concentration is also recovered by the CNN: at fixed mass, halo concentration has only a mild impact on b 1, but a strong impact on b ϕ. Our framework opens a new window for discovering which physical aspects of the halo's Lagrangian patch determine assembly bias, which in turn can inform physical models of halo formation and bias. [ABSTRACT FROM AUTHOR]

We build a deep learning framework that connects the local formation process of dark matter haloes to the halo bias. We train a convolutional neural network (CNN) to predict the final mass and concentration of dark matter haloes from the initial conditions. The CNN is then used as a surrogate model to derive the response of the haloes' mass and concentration to long-wavelength perturbations in the initial conditions, and consequently the halo bias parameters following the 'response bias' definition. The CNN correctly predicts how the local properties of dark matter haloes respond to changes in the large-scale environment, despite no explicit knowledge of halo bias being provided during training. We show that the CNN recovers the known trends for the linear and second-order density bias parameters b 1 and b 2, as well as for the local primordial non-Gaussianity linear bias parameter b ϕ. The expected secondary assembly bias dependence on halo concentration is also recovered by the CNN: at fixed mass, halo concentration has only a mild impact on b 1, but a strong impact on b ϕ. Our framework opens a new window for discovering which physical aspects of the halo's Lagrangian patch determine assembly bias, which in turn can inform physical models of halo formation and bias. [ABSTRACT FROM AUTHOR]

The integrated shear 3-point correlation function ζ± is a higher-order statistic of the cosmic shear field that describes the modulation of the 2-point correlation function ξ± by long-wavelength features in the field. Here, we introduce a new theoretical model to calculate ζ± that is accurate on small angular scales, and that allows to take baryonic feedback effects into account. Our model builds on the realization that the small-scale ζ± is dominated by the non-linear matter bispectrum in the squeezed limit, which can be evaluated accurately using the non-linear matter power spectrum and its first-order response functions to density and tidal field perturbations. We demonstrate the accuracy of our model by showing that it reproduces the small-scale ζ± measured in simulated cosmic shear maps. The impact of baryonic feedback enters effectively only through the corresponding impact on the non-linear matter power spectrum, thereby permitting to account for these astrophysical effects on ζ± similarly to how they are currently accounted for on ξ±. Using a simple idealized Fisher matrix forecast for a DES-like survey we find that, compared to ξ±, a combined |$\xi _{\pm }\ \&\ \zeta _{\pm }$| analysis can lead to improvements of order |$20\!-\!40{{\ \rm per\ cent}}$| on the constraints of cosmological parameters such as σ8 or the dark energy equation of state parameter w 0. We find similar levels of improvement on the constraints of the baryonic feedback parameters, which strengthens the prospects for cosmic shear data to obtain tight constraints not only on cosmology but also on astrophysical feedback models. These encouraging results motivate future works on the integrated shear 3-point correlation function towards applications to real survey data. [ABSTRACT FROM AUTHOR]

We investigate the accuracy of weak lensing simulations by comparing the results of five independently developed lensing simulation codes run on the same input N -body simulation. Our comparison focuses on the lensing convergence maps produced by the codes, and in particular on the corresponding PDFs, power spectra, and peak counts. We find that the convergence power spectra of the lensing codes agree to |$\lesssim 2{{\ \rm per\ cent}}$| out to scales ℓ ≈ 4000. For lensing peak counts, the agreement is better than |$5{{\ \rm per\ cent}}$| for peaks with signal-to-noise ≲ 6. We also discuss the systematic errors due to the Born approximation, line-of-sight discretization, particle noise, and smoothing. The lensing codes tested deal in markedly different ways with these effects, but they none-the-less display a satisfactory level of agreement. Our results thus suggest that systematic errors due to the operation of existing lensing codes should be small. Moreover their impact on the convergence power spectra for a lensing simulation can be predicted given its numerical details, which may then serve as a validation test. [ABSTRACT FROM AUTHOR]

We measure power spectrum response functions in the presence of baryonic physical processes using separate universe simulations with the IllustrisTNG galaxy formation model. The response functions describe how the small-scale power spectrum reacts to long-wavelength perturbations and they can be efficiently measured with the separate universe technique by absorbing the effects of the long modes into a modified cosmology. Specifically, we focus on the total first-order matter power spectrum response to an isotropic density fluctuation R 1(k, z), which is fully determined by the logarithmic derivative of the non-linear matter power spectrum dln P m(k, z)/dln k and the growth-only response function G 1(k, z). We find that G 1(k, z) is not affected by the baryonic physical processes in the simulations at redshifts z < 3 and on all scales probed (k ≲ 15  h  Mpc−1; i.e. length scales |$\gtrsim 0.4\, {\rm Mpc}\,h^{-1}$|⁠). In practice, this implies that the power spectrum fully specifies the baryonic dependence of its response function. Assuming an idealized lensing survey set-up, we evaluate numerically the baryonic impact on the squeezed-lensing bispectrum and the lensing supersample power spectrum covariance, which are given in terms of responses. Our results show that these higher-order lensing statistics can display varying levels of sensitivity to baryonic effects compared to the power spectrum, with the squeezed bispectrum being the least sensitive. We also show that ignoring baryonic effects on lensing covariances slightly overestimates the error budget (and is therefore conservative from the point of view of parameter error bars) and likely has negligible impact on parameter biases in inference analyses. [ABSTRACT FROM AUTHOR]

Self-consistent N-body simulations of modified gravity models are a key ingredient to obtain rigorous constraints on deviations from general relativity using large-scale structure observations. This paper provides the first detailed comparison of the results of different N-body codes for the f (R), Dvali-Gabadadze-Porrati and Symmetron models, starting from the same initial conditions. We find that the fractional deviation of the matter power spectrum from ? cold dark matter agrees to better than 1 per cent up to k ~ 5-10 h Mpc-1 between the different codes. These codes are thus able to meet the stringent accuracy requirements of upcoming observational surveys. All codes are also in good agreement in their results for the velocity divergence power spectrum, halo abundances and halo profiles. We also test the quasi-static limit, which is employed in most modified gravity N-body codes, for the Symmetron model for which the most significant non-static effects among the models considered are expected. We conclude that this limit is a very good approximation for all of the observables considered here. [ABSTRACT FROM AUTHOR]

The large-scale clustering of matter is impacted by baryonic physics, particularly active galactic nuclei (AGN) feedback. Modelling or mitigating this impact will be essential for making full use of upcoming measurements of cosmic shear and other large-scale structure probes. We study baryonic effects on the matter bispectrum, using measurements from a selection of state-of-the-art hydrodynamical simulations: IllustrisTNG, Illustris, EAGLE, and BAHAMAS. We identify a low-redshift enhancement of the bispectrum, peaking at |$k\sim 3\,h\, {\rm Mpc}^{-1}$|⁠ , which is present in several simulations, and discuss how it can be associated to the evolving nature of AGN feedback at late times. This enhancement does not appear in the matter power spectrum, and therefore represents a new source of degeneracy breaking between two- and three-point statistics. In addition, we provide physical interpretations for other aspects of these measurements, and make initial comparisons to predictions from perturbation theory, empirical fitting formulas, and the response function formalism. We publicly release our measurements (including estimates of their uncertainty due to sample variance) and bispectrum measurement code as resources for the community. [ABSTRACT FROM AUTHOR]

We present high signal-to-noise galaxy-galaxy lensing measurements of the Baryon Oscillation Spectroscopic Survey constant mass (CMASS) sample using 250 deg² of weak-lensing data from Canada-France-Hawaii Telescope Lensing Survey and Canada-France-Hawaii Telescope Stripe 82 Survey. We compare this signal with predictions from mock catalogues trained to match observables including the stellar mass function and the projected and two-dimensional clustering of CMASS. We show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40 per cent larger than observed. Detailed tests show that our results are robust to a variety of systematic effects. Lowering the value of S8 = σ8 √Ωm/0.3 compared to Planck Collaboration XIII reconciles the lensing with clustering. However, given the scale of our measurement (r < 10 h-1 Mpc), other effects may also be at play and need to be taken into consideration. We explore the impact of baryon physics, assembly bias, massive neutrinos and modifications to general relativity on ΔΣ and show that several of these effects may be non-negligible given the precision of our measurement. Disentangling cosmological effects from the details of the galaxy-halo connection, the effect of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy samples from Baryon Acoustic Oscillation surveys with precise measurements but complex selection functions. [ABSTRACT FROM AUTHOR]