Curl lensing, also known as lensing field-rotation or shear B-modes, is a distinct post-Born observable caused by two lensing deflections at different redshifts (lens-lens coupling). For the Cosmic ...Microwave Background (CMB), the field-rotation is approximately four orders of magnitude smaller than the CMB lensing convergence. Direct detection is therefore challenging for near-future CMB experiments such as the Simons Observatory (SO) or CMB `Stage-4' (CMB-S4). Instead, the curl can be probed in cross-correlation between a direct reconstruction and a template formed using pairs of large-scale structure (LSS) tracers to emulate the lens-lens coupling. In this paper, we derive a new estimator for the optimal curl template specifically adapted for curved-sky applications, and test it against non-Gaussian complications using N-body cosmology simulations. We find non-foreground biases to the curl cross-spectrum are purely Gaussian at the sensitivity of SO. However, higher-order curl contractions induce non-Gaussian bias at the order of \(1\sigma\) for CMB-S4 using quadratic estimators (QE). Maximum a-Posteriori (MAP) lensing estimators significantly reduce biases for both SO and CMB-S4, in agreement with our analytic predictions. We also show that extragalactic foregrounds in the CMB can bias curl measurements at order of the signal, and evaluate a variety of mitigation strategies to control these biases for SO-like experiments. Near-future observations will be able to measure post-Born lensing curl B-modes.
The gravitational lensing signal from the Cosmic Microwave Background is highly valuable to constrain the growth of the structures in the Universe in a clean and robust manner over a wide range of ...redshifts. One of the theoretical systematics for lensing reconstruction is the impact of the lensing field non-Gaussianities on its estimators. Non-linear matter clustering and post-Born lensing corrections are known to bias standard quadratic estimators to some extent, most significantly so in temperature. In this work, we explore the impact of non-Gaussian deflections on Maximum a Posteriori lensing estimators, which, in contrast to quadratic estimators, are able to provide optimal measurements of the lensing field. We show that these naturally reduce the induced non- Gaussian bias and lead to unbiased cosmological constraints in \(\Lambda\)CDM at CMB-S4 noise levels without the need for explicit modelling. We also test the impact of assuming a non-Gaussian prior for the reconstruction; this mitigates the effect further slightly, but generally has little impact on the quality of the reconstruction. This shows that higher-order statistics of the lensing deflections are not expected to present a major challenge for optimal CMB lensing reconstruction in the foreseeable future.
We present a new Planck CMB lensing-CMB temperature cross-correlation likelihood that can be used to constrain cosmology via the Integrated Sachs-Wolfe (ISW) effect. CMB lensing is an excellent ...tracer of ISW, and we use the latest PR4 Planck data maps and lensing reconstruction to produce the first public Planck likelihood to constrain this signal. We demonstrate the likelihood by constraining the CMB background temperature from Planck data alone, where the ISW-lensing cross-correlation is a powerful way to break the geometric degeneracy, substantially improving constraints from the CMB and lensing power spectra alone.
Deviations from the blackbody spectral energy distribution of the CMB are a precise probe of physical processes active both in the early universe (such as those connected to particle decays and ...inflation) and at later times (e.g. reionization and astrophysical emissions). Limited progress has been made in the characterization of these spectral distortions after the pioneering measurements of the FIRAS instrument on the COBE satellite in the early 1990s, which mainly targeted the measurement of their average amplitude across the sky. Since at present no follow-up mission is scheduled to update the FIRAS measurement, in this work we re-analyze the FIRAS data and produce a map of \(\mu\)-type spectral distortion across the sky. We provide an updated constraint on the \(\mu\) distortion monopole \(|\langle\mu\rangle|<47\times 10^{-6}\) at 95\% confidence level that sharpens the previous FIRAS estimate by a factor of \(\sim 2\). We also constrain primordial non-Gaussianities of curvature perturbations on scales \(10\lesssim k\lesssim 5\times 10^4\) through the cross-correlation of \(\mu\) distortion anisotropies with CMB temperature and, for the first time, the full set of polarization anisotropies from the Planck satellite. We obtain upper limits on \(f_{\rm NL}\lesssim 3.6 \times 10^6\) and on its running \(n_{\rm NL}\lesssim 1.4\) that are limited by the FIRAS sensitivity but robust against galactic and extragalactic foreground contaminations. We revisit previous similar analyses based on data of the Planck satellite and show that, despite their significantly lower noise, they yield similar or worse results to ours once all the instrumental and astrophysical uncertainties are properly accounted for. Our work is the first to self-consistently analyze data from a spectrometer and demonstrate the power of such instrument to carry out this kind of science case with reduced systematic uncertainties.
Cosmic voids are a powerful probe of cosmology and are one of the core observables of upcoming galaxy surveys. The cross-correlations between voids and other large-scale structure tracers such as ...galaxy clustering and galaxy lensing have been shown to be very sensitive probes of cosmology and among the most promising to probe the nature of gravity and the neutrino mass. However, recent measurements of the void imprint on the lensed Cosmic Microwave Background (CMB) have been shown to be in tension with expectations based on LCDM simulations, hinting to a possibility of non-standard cosmological signatures due to massive neutrinos. In this work we use the DEMNUni cosmological simulations with massive neutrino cosmologies to study the neutrino impact on voids selected in photometric surveys, e.g. via Luminous Red Galaxies, as well as on the void- CMB lensing cross-correlation. We show how the void properties observed in this way (size function, profiles) are affected by the presence of massive neutrinos compared to the neutrino massless case, and show how these can vary as a function of the selection method of the void sample. We comment on the possibility for massive neutrinos to be the source of the aforementioned tension. Finally, we identify the most promising setup to detect signatures of massive neutrinos in the voids-CMB lensing cross-correlation and define a new quantity useful to distinguish among different neutrino masses by comparing future observations against predictions from simulations including massive neutrinos.
The analyses of the next generation cosmological surveys demand an accurate, efficient, and differentiable method for simulating the universe and its observables across cosmological volumes. We ...present Hamiltonian ray tracing (HRT) -- the first post-Born (accounting for lens-lens coupling and without relying on the Born approximation), three-dimensional (without assuming the thin-lens approximation), and on-the-fly (applicable to any structure formation simulations) ray tracing algorithm based on the Hamiltonian formalism. HRT performs symplectic integration of the photon geodesics in a weak gravitational field, and can integrate tightly with any gravity solver, enabling co-evolution of matter particles and light rays with minimal additional computations. We implement HRT in the particle-mesh library \(\texttt{pmwd}\), leveraging hardware accelerators such as GPUs and automatic differentiation capabilities based on \(\texttt{JAX}\). When tested on a point-mass lens, HRT achieves sub-percent accuracy in deflection angles above the resolution limit across both weak and moderately strong lensing regimes. We also test HRT in cosmological simulations on the convergence maps and their power spectra.
Extracting non-Gaussian information from the next generation weak lensing surveys will require fast and accurate full-sky simulations. This is difficult to achieve in practice with existing ...simulation methods: ray-traced \(N\)-body simulations are computationally expensive, and approximate simulation methods (such as lognormal mocks) are not accurate enough. Here, we present GANSky, an interpretable machine learning method that uses Generative Adversarial Networks (GANs) to produce fast and accurate full-sky tomographic weak lensing maps. The input to our GAN are lognormal maps that approximately describe the late-time convergence field of the Universe. Starting from these lognormal maps, we use GANs to learn how to locally redistribute mass to achieve simulation-quality maps. This can be achieved using remarkably small networks (\(\approx 10^3\) parameters). We validate the GAN maps by computing a number of summary statistics in both simulated and GANSky maps. We show that GANSky maps correctly reproduce both the mean and \(\chi^2\) distribution for several statistics, specifically: the 2-pt function, 1-pt PDF, peak and void counts, and the equilateral, folded and squeezed bispectra. These successes makes GANSky an attractive tool to compute the covariances of these statistics. In addition to being useful for rapidly generating large ensembles of artificial data sets, our method can be used to extract non-Gaussian information from weak lensing data with field-level or simulation-based inference.
Observed Cosmic Microwave Background (CMB) maps are contaminated by foregrounds, some of which are usually masked to perform cosmological analyses. If masks are correlated to the lensing signal, such ...as those removing extragalactic emissions located in matter overdensities, measurements over the unmasked sky may give biased estimates. We quantify the impact of these mask-induced biases for the reconstructed CMB lensing auto- and cross-correlation power spectra with external matter tracers. We show that they arise both from changes in the lensing power, and via modifications to the reconstruction power spectrum corrections, \(N_L^{(0)}\), \(N_L^{(1)}\) and \(N_L^{(3/2)}\)). For direct masking of the CMB lensing field, we derive simple analytic models of the masking effect and show that it is potentially large. We show that mask-induced biases are significantly reduced by optimal filtering of the CMB maps in the lensing reconstruction. We test the resulting lensing power spectrum biases on numerical simulations, masking radio sources, and peaks of thermal Sunyaev-Zeldovich (tSZ) and cosmic infrared background (CIB) emission. For the lensing auto spectrum, masking biases can only be measured with a statistical significance \(\lesssim 3\sigma\) for future data sets. The same applies to the cross-correlation power spectra between CMB lensing and tSZ and CIB even though biases are larger (up to ~30%). We find that masking tSZ-selected galaxy clusters leads to the largest mask biases, potentially detectable with high significance. We find that the calibration of cluster masses using CMB lensing, in particular for objects at \(z\lesssim 0.6\), might be significantly affected by mask biases for near-future observations if the lensing signal recovered inside the mask holes is used without further corrections. Conversely, mass calibration of high redshift objects will still deliver unbiased results.
Weak gravitational lensing of the cosmic microwave background (CMB) is an important cosmological tool that allows us to learn about the structure, composition and evolution of the Universe. Upcoming ...CMB experiments, such as the Simons Observatory (SO), will provide high-resolution and low-noise CMB measurements. We consider the impact of instrumental systematics on the corresponding high-precision lensing reconstruction power spectrum measurements. We simulate CMB temperature and polarization maps for an SO-like instrument and potential scanning strategy, and explore systematics relating to beam asymmetries and offsets, boresight pointing, polarization angle, gain drifts, gain calibration and electric crosstalk. Our analysis shows that the majority of the biases induced by the systematics we modeled are below a detection level of \(\sim 0.6\sigma\). We discuss potential mitigation techniques to further reduce the impact of the more significant systematics, and pave the way for future lensing-related systematics analyses.
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