Optimally Mapping Large-Scale Structures with Luminous Sources

TL;DR

This paper develops a formalism to compare galaxy redshift surveys and intensity mapping for large-scale structure measurement, providing optimal strategies based on survey parameters and source luminosity functions.

Contribution

It introduces a Fisher information-based framework to evaluate and optimize large-scale structure measurements using different observational approaches.

Findings

Identifies regimes where galaxy surveys or intensity mapping are more effective.

Provides a metric to select optimal survey strategies based on source luminosity and sensitivity.

Demonstrates the framework with planned intensity mapping surveys.

Abstract

Intensity mapping has emerged as a promising tool to probe the three-dimensional structure of the universe. The traditional approach of galaxy redshift surveys is based on individual galaxy detection, typically performed by thresholding and digitizing large-scale intensity maps. By contrast, intensity mapping uses the integrated emission from all sources in a 3D pixel (or voxel) as an analog tracer of large-scale structure. In this work, we develop a formalism to quantify the performance of both approaches when measuring large-scale structures. We compute the Fisher information of an arbitrary observable, derive the optimal estimator, and study its performance as a function of source luminosity function, survey resolution, instrument sensitivity, and other survey parameters. We identify regimes where each approach is advantageous and discuss optimal strategies for different scenarios. To determine the best strategy for any given survey, we develop a metric that is easy to compute from the source luminosity function and the survey sensitivity, and we demonstrate the application with several planned intensity mapping surveys.