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The sensitivity and wide area reached by ongoing and future wide-fieldoptical surveys allows for the detection of an increasing number of galaxyclusters uniquely through their weak lensing (WL) signal. This motivates thedevelopment of new methods to analyse the unprecedented volume of data fasterand more efficiently. Here we introduce a new multi-scale WL detection methodbased on application of wavelet filters to the convergence maps. We compare ourresults to those obtained from four commonly-used single scale approaches basedon the application of aperture mass filters to the shear in real and Fourierspace. The method is validated on Euclid-like mocks from theDUSTGRAIN-pathfinder simulations. We introduce a new matching procedure thattakes into account the theoretical signal-to-noise of detection by WL and thefilter size. We perform a complete analysis of the filters, and a comparison ofthe purity and the completeness of the resulting detected catalogues. We showthat equivalent results are obtained when the detection is undertaken in realand Fourier space, and when the algorithms are applied to the shear and theconvergence. We show that the multiscale method applied to the convergence isfaster and more efficient at detecting clusters than single scale methodsapplied to the shear. We obtained an increase of 25% in the number ofdetections while maintaining the same purity compared to the most up-to-dateaperture mass filter. We analyse the detected catalogues and quantify theefficiency of the matching procedure, showing in particular that less than 5%of the detections from the multiscale method can be ascribed to line-of-sightalignments. The method is well-adapted to the more sensitive, wider-area,optical surveys that will be available in the near future, and paves the way tocluster samples that are as near as possible to being selected by total mattercontent.

Fast multiscale galaxy cluster detection with weak lensing: towards a mass-selected sample