Integrated Sachs–Wolfe maps from the Gower Street w CDM simulations

Context. The late-time linear integrated Sachs-Wolfe (ISW) effect directly probes the dynamics of cosmic acceleration and the nature of dark energy. Detecting these weak, secondary temperature anisotropy signals of the cosmic microwave background requires accurate theoretical predictions of their amplitude across cosmological models. Aims. By extending the pyGenISW package, previously limited to the Lambda cold dark matter (ΛCDM) model, we aim to generate full-sky ISW maps for a suite of 791 w CDM cosmologies using the Gower Street N-body simulations, enabling ISW analyses across a broader dark-energy parameter space. We make our code and ISW data publicly available. Methods. We computed the ISW signals by tracing the time evolution of the gravitational potential across large-volume simulations that span dark energy equation of state parameters from phantom to quintessence, −1.79 ≲ w ≲ −0.34. These data are projected onto the sphere using HEALP IX to obtain full-sky temperature maps. Results. We validate our pipeline by comparing the measured ISW angular power spectra and ISW-density cross-correlations against linear theory expectations (2 ≤ ℓ ≤ 200) computed with benchmarks from the pyCCL library. The agreement is excellent across the multipole range where the ISW contribution is expected to dominate, confirming the reliability of our modelling of gravitational-potential evolution. With additional tests of the ISW signal’s strength in density extrema, as well as comparisons of all models to a reference ΛCDM cosmology using power ratios, we find that quintessence-like models ( w > −1) show higher ISW amplitudes than phantom models ( w < −1), consistent with the enhanced late-time decay of gravitational potentials. Conclusions. The consistency of our w CDM ISW maps and their agreement with theory predictions confirm the robustness of our methodology, establishing it as a reliable tool for theoretical and observational ISW-LSS analyses. This includes applications to next-generation surveys in the context of covariance calculations and various map-based statistics.