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We build a deep learning framework that connects the local formation process of dark matter halos to the halo bias. We train a convolutional neural network (CNN) to predict the final mass and concentration of dark matter halos from the initial conditions. The CNN is then used as a surrogate model to derive the response of the halos' 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 halos 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 $b_\phi$. 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 $b_\phi$. 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., Comment: 11 pages, 5 figures, to be submitted to MNRAS, comments welcome

We discuss the potential of the multi-tracer technique to improve observational constraints of the local primordial non-Gaussianity (PNG) parameter $f_{\rm NL}$ from the galaxy power spectrum. For two galaxy samples $A$ and $B$, we show the constraining power is $\propto |b_1^B b_\phi^A - b_1^A b_\phi^B|$, where $b_1$ and $b_\phi$ are the linear and PNG galaxy bias parameters. This allows for significantly improved constraints compared to the traditional expectation $\propto |b_1^A - b_1^B|$ based on naive universality-like relations where $b_\phi \propto b_1$. Using IllustrisTNG galaxy simulation data, we find that different equal galaxy number splits of the full sample lead to different $|b_1^B b_\phi^A - b_1^A b_\phi^B|$, and thus have different constraining power. Of all of the strategies explored, splitting by $g-r$ color is the most promising, more than doubling the significance of detecting $f_{\rm NL}b_\phi \neq 0$. Importantly, since these are constraints on $f_{\rm NL}b_\phi$ and not $f_{\rm NL}$, they do not require priors on the $b_\phi(b_1)$ relation. For direct constraints on $f_{\rm NL}$, we show that multi-tracer constraints can be significantly more robust than single-tracer to $b_\phi$ misspecifications and uncertainties; this relaxes the precision and accuracy requirements for $b_\phi$ priors. Our results present new opportunities to improve our chances to detect and robustly constrain $f_{\rm NL}$, and strongly motivate galaxy formation simulation campaigns to calibrate the $b_\phi(b_1)$ relation., Comment: 9 pages, 4 figures, 1 table. Comments welcomed!

The integrated shear 3-point correlation function $\zeta_{\pm}$ measures the correlation between the local shear 2-point function $\xi_{\pm}$ and the 1-point shear aperture mass in patches of the sky. Unlike other higher-order statistics, $\zeta_{\pm}$ can be efficiently measured from cosmic shear data, and it admits accurate theory predictions on a wide range of scales as a function of cosmological and baryonic feedback parameters. Here, we develop and test a likelihood analysis pipeline for cosmological constraints using $\zeta_{\pm}$. We incorporate treatment of systematic effects from photometric redshift uncertainties, shear calibration bias and galaxy intrinsic alignments. We also develop an accurate neural-network emulator for fast theory predictions in MCMC parameter inference analyses. We test our pipeline using realistic cosmic shear maps based on $N$-body simulations with a DES Y3-like footprint, mask and source tomographic bins, finding unbiased parameter constraints. Relative to $\xi_{\pm}$-only, adding $\zeta_{\pm}$ can lead to $\approx 10-25\%$ improvements on the constraints of parameters like $A_s$ (or $\sigma_8$) and $w_0$. We find no evidence in $\xi_{\pm} + \zeta_{\pm}$ constraints of a significant mitigation of the impact of systematics. We also investigate the impact of the size of the apertures where $\zeta_{\pm}$ is measured, and of the strategy to estimate the covariance matrix ($N$-body vs. lognormal). Our analysis solidifies the strong potential of the $\zeta_{\pm}$ statistic and puts forward a pipeline that can be readily used to improve cosmological constraints using real cosmic shear data., Comment: 21 pages, 11 figures, 3 tables. Comments welcome

We use the BOSS DR12 galaxy power spectrum to constrain compensated isocurvature perturbations (CIP), which are opposite-sign primordial baryon and dark matter perturbations that leave the total matter density unchanged. Long-wavelength CIP $\sigma(\vec{x})$ enter the galaxy density contrast as $\delta_g(\vec{x}) \supset b_\sigma\sigma(\vec{x})$, with $b_\sigma$ the linear CIP galaxy bias parameter. We parameterize the CIP spectra as $P_{\sigma\sigma} = A^2P_{\mathcal{R}\mathcal{R}}$ and $P_{\sigma\mathcal{R}} = \xi\sqrt{P_{\sigma\sigma}P_{\mathcal{R}\mathcal{R}}}$, where $A$ is the CIP amplitude and $\xi$ is the correlation with the curvature perturbations $\mathcal{R}$. We find a significance of detection of $Ab_\sigma \neq 0$ of $1.8\sigma$ for correlated ($\xi = 1$) and $3.7\sigma$ for uncorrelated ($\xi = 0$) CIP. Large-scale data systematics have a bigger impact for uncorrelated CIP, which may explain the large significance of detection. The constraints on $A$ depend on the assumed priors for the $b_\sigma$ parameter, which we estimate using separate universe simulations. Assuming $b_\sigma$ values representative of all halos we find $\sigma_A = 145$ for correlated CIP and $\sigma_{|A|} = 475$ for uncorrelated CIP. Our strongest uncorrelated CIP constraint is for $b_\sigma$ representative of the $33\%$ most concentrated halos, $\sigma_{|A|} = 197$, which is better than the current CMB bounds $|A| \lesssim 360$. We also discuss the impact of the local primordial non-Gaussianity parameter $f_{\rm NL}$ in CIP constraints. Our results demonstrate the power of galaxy data to place tight constraints on CIP, and motivate works to understand better the impact of data systematics, as well as to determine theory priors for $b_\sigma$., Comment: 11 pages, 4 figures, 3 tables. Comments welcomed!

We study the effect of super-sample covariance (SSC) on the power spectrum and higher-order statistics: bispectrum, halo mass function, and void size function. We also investigate the effect of SSC on the cross-covariance between the statistics. We consider both the matter and halo fields. Higher-order statistics of the large-scale structure contain additional cosmological information beyond the power spectrum and are a powerful tool to constrain cosmology. They are a promising probe for ongoing and upcoming high precision cosmological surveys such as DESI, PFS, Rubin Observatory LSST, Euclid, SPHEREx, SKA, and Roman Space Telescope. Cosmological simulations used in modeling and validating these statistics often have sizes that are much smaller than the observed Universe. Density fluctuations on scales larger than the simulation box, known as super-sample modes, are not captured by the simulations and in turn can lead to inaccuracies in the covariance matrix. We compare the covariance measured using simulation boxes containing super-sample modes to those without. We also compare with the Separate Universe approach. We find that while the power spectrum, bispectrum and halo mass function show significant scale- or mass-dependent SSC, the void size function shows relatively small SSC. We also find significant SSC contributions to the cross-covariances between the different statistics, implying that future joint-analyses will need to carefully take into consideration the effect of SSC., 8+2 pages, 4 figures

We show that, in the presence of massive neutrinos, the Galileon gravity model provides a very good fit to the current CMB temperature, CMB lensing and BAO data. This model, which we dub $�� \rm{Galileon}$, when assuming its stable attractor background solution, contains the same set of free parameters as $��\rm{CDM}$, although it leads to different expansion dynamics and nontrivial gravitational interactions. The data provide compelling evidence ($\gtrsim 6��$) for nonzero neutrino masses, with $��m_��\gtrsim 0.4\ {\rm eV}$ at the $2��$ level. Upcoming precision terrestrial measurements of the absolute neutrino mass scale therefore have the potential to test this model. We show that CMB lensing measurements at multipoles $l \lesssim 40$ will be able to discriminate between the $�� \rm{Galileon}$ and $��\rm{CDM}$ models. Unlike $��\rm{CDM}$, the $�� \rm{Galileon}$ model is consistent with local determinations of the Hubble parameter. The presence of massive neutrinos lowers the value of $��_8$ substantially, despite of the enhanced gravitational strength on large scales. Unlike $��\rm{CDM}$, the $�� \rm{Galileon}$ model predicts a negative ISW effect, which is difficult to reconcile with current observational limits., 4 pages, 2 figures, 1 table. Version 3: matches published version

Self-consistent ${\it N}$-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 ${\it N}$-body codes for the $f(R)$, DGP, and Symmetron models, starting from the same initial conditions. We find that the fractional deviation of the matter power spectrum from $\Lambda$CDM agrees to better than $1\%$ up to $k \sim 5-10~h/{\rm Mpc}$ 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 ${\it N}$-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., Comment: 31 pages, 16 figures. Version to appear in MNRAS