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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!