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Combining different observational probes, such as galaxy clustering and weaklensing, is a promising technique for unveiling the physics of the Universewith upcoming dark energy experiments. Whilst this strategy significantlyimproves parameter constraints, decreasing the degeneracies of individualanalyses and controlling the systematics, processing data from tens of millionsof galaxies is not a trivial task. In this work we derive and test a newestimator for joint clustering and lensing data analysis, maximising thescientific return and decreasing the computational cost. Our estimatorcompresses the data by up-weighting the components most sensitive to theparameters of interest, with no loss of information, taking into accountinformation from the cross-correlation between the two probes. We deriveoptimal redshift weights which may be applied to individual galaxies whentesting a given statistic and cosmological model.

Compressing combined probes: redshift weights for joint lensing and clustering analyses