Optimizing the green-field beta beam: Small versus large theta_13

TL;DR

This paper analyzes how to optimize green-field beta beam experiments for different scenarios of the unknown parameter theta_13, focusing on baseline, boost, luminosity, and isotope choices.

Contribution

It provides a framework for optimizing beta beam setups based on whether theta_13 is discovered or not at the decision time.

Findings

For small theta_13, sensitivity depends on effort invested.

For large theta_13, clear optimization criteria exist.

Information on theta_13 improves optimization strategies.

Abstract

We discuss the optimization of a green-field beta beam in terms of baseline, boost factor, luminosity, and isotope pair used. We identify two qualitatively different cases: theta_13 not discovered at the time a decision has to be made (theta_13 small), and theta_13 discovered at that time (theta_13 large). For small theta_13, it turns out that the obtainable sensitivity is essentially a matter of the effort one is willing to spend. For large theta_13, however, one can find clear optimization criteria, and one can use the information on theta_13 obtained until then.