1 INTRODUCTION
AMICO: optimised detection of galaxy clusters

2 OPTIMAL FILTERING OF THE DATA
2.1 General principles
2.2 Applying the filter
2.3 Variance of the amplitude estimate
2.4 Likelihood
2.5 Masked areas
2.6 Local background
2.7 Model

3 SELECTING THE CLUSTER CANDIDATES
3.1 Membership assignment
3.2 Cleaning the detections

4 TESTS ON IDEAL MOCKS
4.1 Simulation
4.2 Model and background

5 TESTS ON COSMOLOGICAL MOCKS
5.1 Completeness
5.2 Redshift estimation

6 SUMMARY AND CONCLUSIONS