Running the small-correlated-against-large estimator at scale: Applications of small-scale CMB lensing estimators on realistic simulations

TL;DR

This paper develops a novel small-scale CMB lensing estimator called SCALE, integrates it into cosmological parameter inference using neural network emulators, and demonstrates its potential to improve constraints on neutrino mass and dark matter models.

Contribution

The paper introduces a new SCALE estimator for small-scale CMB lensing, incorporates it into parameter inference with neural network emulators, and shows its effectiveness in constraining neutrino mass and dark matter models.

Findings

SCALE can detect small-scale lensing with high significance.

Including SCALE improves neutrino mass constraints to 4σ.

SCALE constrains models of warm or fuzzy dark matter.

Abstract

The Small-Correlated-Against-Large Estimator (SCALE) for small-scale lensing of the cosmic microwave background (CMB) provides a novel method for measuring the amplitude of CMB lensing power without the need for reconstruction of the lensing field. In our previous study, we showed that the SCALE method can outperform existing reconstruction methods to detect the presence of lensing at small scales ($\ell \gg 3000$). Here we develop a procedure to include information from SCALE in cosmological parameter inference. We construct a precise neural network emulator to quickly map cosmological parameters to desired CMB observables such as temperature and lensing power spectra and SCALE cross spectra. We also outline a method to apply SCALE to full-sky maps of the CMB temperature field, and construct a likelihood for the application of SCALE in parameter estimation. SCALE supplements conventional observables such as the CMB power spectra and baryon acoustic oscillations in constraining parameters that are sensitive to the small-scale lensing amplitude such as the neutrino mass $m_\nu$. We show that including estimates of the small-scale lensing amplitude from SCALE in such an analysis provides enough constraining information to measure the minimum neutrino mass at $4\sigma$ significance in the scenario of minimal mass, and higher significance for higher mass. Finally, we show that SCALE will play a powerful role in constraining models of clustering that generate scale-dependent modulation to the distribution of matter and the lensing power spectrum, as predicted by models of warm or fuzzy dark matter.