LiteBIRD science goals and forecasts: improved full-sky reconstruction of the gravitational lensing potential through the combination of Planck and LiteBIRD data

TL;DR

This work forecasts a significantly enhanced full-sky CMB lensing reconstruction by combining Planck's high-resolution temperature data with LiteBIRD's precise large-angle polarization. By extending multipole coverage and employing a minimum-variance (MV) lensing estimator across $TT$, $EE$, $TE$, $TB$, and $EB$ channels, the authors predict a LiteBIRD-alone detection of $49$–$58\sigma$ and a Planck+LiteBIRD detection of $72$–$78\sigma$ over $80\%$ of the sky, with robust performance against complex foregrounds. They demonstrate the lensing map’s utility for cosmological parameter inference using a lensing-only likelihood and for internal delensing to improve $r$ constraints, forecasting a roughly factor of 2 improvement in $S_8^{\mathrm{CMBL}}$ and a few percent gain in $r$ with Planck+LiteBIRD MV. The study emphasizes the complementary strengths of the two missions, showing that Planck supplies small-scale temperature information while LiteBIRD provides large-scale polarization, yielding a superior full-sky lensing map in the 2030s and meaningful gains for late-time cosmology and primordial B-mode studies, even under foreground complexity.

Abstract

Cosmic microwave background (CMB) photons are deflected by large-scale structure through gravitational lensing. This secondary effect introduces higher-order correlations in CMB anisotropies, which are used to reconstruct lensing deflections. This allows mapping of the integrated matter distribution along the line of sight, probing the growth of structure, and recovering an undistorted view of the last-scattering surface. Gravitational lensing has been measured by previous CMB experiments, with $\textit{Planck}$'s $42\,σ$ detection being the current best full-sky lensing map. We present an enhanced $\textit{LiteBIRD}$ lensing map by extending the CMB multipole range and including the minimum-variance estimation, leading to a $49$ to $58\,σ$ detection over $80\,\%$ of the sky, depending on the final complexity of polarized Galactic emission. The combination of $\textit{Planck}$ and $\textit{LiteBIRD}$ will be the best full-sky lensing map in the 2030s, providing a $72$ to $78\,σ$ detection over $80\,\%$ of the sky, almost doubling $\textit{Planck}$'s sensitivity. Finally, we explore different applications of the lensing map, including cosmological parameter estimation using a lensing-only likelihood and internal delensing, showing that the combination of both experiments leads to improved constraints. The combination of $\textit{Planck}$ + $\textit{LiteBIRD}$ will improve the $S_8$ constraint by a factor of 2 compared to $\textit{Planck}$, and $\textit{Planck}$ + $\textit{LiteBIRD}$ internal delensing will improve $\textit{LiteBIRD}$'s tensor-to-scalar ratio constraint by $6\,\%$. We have tested the robustness of our results against foreground models of different complexity, showing that improvements remains even for the most complex foregrounds.

Figures (22)

• Figure 1: Foreground and noise residuals computed from $400$ component-separated temperature and polarization simulations in the simple-foregrounds case. Solid black lines correspond to the input signal (from left to right, $T$, $E$, and $B$). Residuals are shown for LiteBIRD (blue), Planck (orange) and Planck + LiteBIRD (green). Temperature power spectra are calculated with the $97\,\%$Planck Galactic mask, while polarization results are for full sky.
• Figure 2: Foreground and noise residuals computed from $400$ component-separated temperature and polarization simulations of Planck + LiteBIRD. Solid black lines correspond to the input signal (from left to right, $T$, $E$, and $B$). Residuals are shown for the no-foregrounds (blue), simple-foregrounds (orange), and complex-foreground (green) cases. Temperature power spectra are calculated with the $97\,\%$Planck Galactic mask, while polarization results are for full sky.
• Figure 3: Ratio between the diagonal harmonic-space C-inverse filtered data of masked and full-sky angular power spectra for no-foreground LiteBIRD simulations. Results are averaged over 400 simulations. Dashed black lines correspond to the unmasked sky fraction, $f_{\mathrm{sky},2}=\sum_i w_i^2/N_{\rm pix}$.
• Figure 4: Power spectrum of the mean field (MF) calculated for Planck, and for LiteBIRD and Planck + LiteBIRD with our simple-foreground simulations. The black line shows the input lensing power spectrum used to generate the simulations.
• Figure 5: Lensing reconstruction MCN0 noise for Planck, LiteBIRD and Planck + LiteBIRD for the simple-foregrounds case. The MCN0 of the minimum variance (MV) estimator is also plotted. Black lines show the input lensing power spectrum used to generate the simulations.