# PACT I: Combining ACT and Planck data for optimal detection of tSZ signal

## TL;DR

This paper develops methods to optimally combine ACT and Planck data for enhanced detection and mapping of the tSZ signal, reducing degeneracies and improving resolution.

## Contribution

It introduces two approaches, MMF and ILC, for combining heterogeneous datasets to improve tSZ detection and resolution beyond individual datasets.

## Key findings

- Signal-to-noise of clusters improves by up to a factor of three.
- tSZ map resolution improves to ~1.5 arcmin, more than twice better than Planck.
- Enhanced capability to study cluster pressure profiles and substructure.

## Abstract

We present the optimal reconstruction of the thermal Sunyaev-Zel'dovich (tSZ) effect signal based on the combination of a heterogeneous dataset consisting of ACT and Planck data, with different numbers of channels, angular resolutions and noise levels. We combine both datasets using two different approaches, a Matched Multi-Filter (MMF) technique and an optimised Internal Linear Combination (ILC). We show that when applying the MMF to the combination of ACT and Planck data, the size-flux degeneracy is reduced and the signal-to-noise of clusters detected with their SZ signal improves by up to a factor of three. In the case of the optimised ILC method, we show that the tSZ map is reconstructed with a resolution of $\sim 1.5$ arcmin. This is more than a factor two improvement compared with the Planck resolution, and with a very good control of noise, i.e. limited only by the intrinsic noise of the individual experiments. The combination of ACT and Planck data offers a unique opportunity to improve on the study of the pressure profiles and to study substructure in clusters through their tSZ.