# Model Breaking Measure for Cosmological Surveys

## TL;DR

This paper introduces a new figure of merit for cosmological surveys that measures their ability to rule out the LCDM model by comparing constrained observable volumes with and without the model, aiding in survey optimization.

## Contribution

It proposes a novel, easily computable figure of merit based on the volume difference in observable space to evaluate and optimize future cosmological surveys.

## Key findings

- The new figure of merit can lead to different survey optimization strategies.
- Application to supernovae and BAO mock data demonstrates its effectiveness.
- It provides a complementary approach to existing metrics for model testing.

## Abstract

Recent observations have led to the establishment of the concordance LCDM model for cosmology. A number of experiments are being planned to shed light on dark energy, dark matter, inflation and gravity, which are the key components of the model. To optimize and compare the reach of these surveys, several figures of merit have been proposed. They are based on either the forecasted precision on the LCDM model and its expansion, or on the expected ability to distinguish two models. We propose here another figure of merit that quantifies the capacity of future surveys to rule out the LCDM model. It is based on a measure of the difference in volume of observable space that the future surveys will constrain with and without imposing the model. This model breaking figure of merit is easy to compute and can lead to different survey optimizations than other metrics. We illustrate its impact using a simple combination of supernovae and BAO mock observations and compare the respective merit of these probes to challenge LCDM. We discuss how this approach would impact the design of future cosmological experiments.