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Plenty of crucial information about our Universe is encoded in the cosmiclarge-scale structure (LSS). However, the extractions of these information areusually hindered by the nonlinearities of the LSS, which can be largelyalleviated by various techniques known as the reconstruction. In realisticapplications, the efficiencies of these methods are always degraded by manylimiting factors, a quite important one being the shot noise induced by thefinite number density of biased matter tracers (i.e., luminous galaxies or darkmatter halos) in observations. In this work, we explore the gains of biasedtracer reconstruction achieved from halo mass information, which can suppressshot noise component and dramatically improves the cross-correlation betweentracer field and dark matter. To this end, we first closely study theclustering biases and the stochasticity properties of halo fields with variousnumber densities under different weighting schemes, i.e., the uniform, mass andoptimal weightings. Then, we apply the biased tracer reconstruction method tothese different weighted halo fields and investigate how linear bias andobservational mass scatter affect the reconstruction performance. Our resultsdemonstrate that halo masses are critical information for significantlyimproving the performance of biased tracer reconstruction, indicating a greatapplication potential for substantially promoting the precision of cosmologicalmeasurements [especially for baryon acoustic oscillations (BAO)] in theambitious on-going and future galaxy surveys.

Biased tracer reconstruction with halo mass information