CMBComp: A Simple and Accurate Compressed CMB Likelihood for Dark Energy, Curvature, and Massive Neutrinos

We present CMBComp, a compact and accurate compressed cosmic microwave background (CMB) likelihood that captures the dominant geometric information of the full CMB likelihood derived from the combined SPT-3G D1 + ACT DR6 + Planck PR3 primary CMB anisotropy + Planck PR4/NPIPE CMB-lensing dataset, which we collectively refer to as SPA. The compression is fast to evaluate and trivial to implement in standard inference pipelines. We construct and validate it in five model spaces: the spatially flat cosmological-constant model (CDM), and its dynamical-dark-energy (w 0w a CDM), massive-neutrino (nu CDM), non-flat (o CDM), and joint massive-neutrino--dynamical-dark-energy (nu w 0 w a CDM) extensions. Five compressed likelihoods are introduced, corresponding to two three-parameter compressions for the dark-energy sector (CMB-3 for CDM and CMB-3w for w 0w a CDM), two four-parameter compressions for the neutrino sector (CMB-4 nu for nu CDM and CMB-4 nu w for nu w 0 w a CDM), and a four-parameter curvature compression (CMB-4k for o CDM). Combining each compressed likelihood with the DESI DR2 baryon acoustic oscillation (BAO) data, we demonstrate that the resulting posteriors agree to high precision with those obtained from the corresponding full-CMB chains. CMBComp is therefore particularly well suited to cosmological inference for models that modify the late-time expansion history, enabling accurate CMB constraints to be incorporated into new analyses with minimal computational overhead and without reliance on a full Boltzmann-solver-based inference pipeline. The compressed likelihood files and example notebooks accompanying CMBComp are made publicly available at https://github.com/Amoghsriv/CMBComp.