We examine the possibility of applying the baryonic acoustic oscillation reconstruction method to improve the neutrino massΣm_νconstraint.Thanks to the Gaussianization of the process,we demonstrate that the reconstr...We examine the possibility of applying the baryonic acoustic oscillation reconstruction method to improve the neutrino massΣm_νconstraint.Thanks to the Gaussianization of the process,we demonstrate that the reconstruction algorithm could improve the measurement accuracy by roughly a factor of two.On the other hand,the reconstruction process itself becomes a source of systematic error.While the algorithm is supposed to produce the displacement field from a density distribution,various approximations cause the reconstructed output to deviate on intermediate scales.Nevertheless,it is still possible to benefit from this Gaussianized field,given that we can carefully calibrate the“transfer function”between the reconstruction output and theoretical displacement divergence from simulations.The limitation of this approach is then set by the numerical stability of this transfer function.With an ensemble of simulations,we show that such systematic error could become comparable to statistical uncertainties for a DESI-like survey and be safely neglected for other less ambitious surveys.展开更多
基金the support from the science research grants from the China Manned Space Project with NO.CMS-CSST-2021-B01supported by the World Premier International Research Center Initiative(WPI),MEXT,Japan+12 种基金the Ontario Research Fund:Research Excellence Program(ORF-RE)Natural Sciences and Engineering Research Council of Canada(NSERC)[funding reference number RGPIN-2019-067,CRD 523638-201,555585-20]Canadian Institute for Advanced Research(CIFAR)Canadian Foundation for Innovation(CFI)the National Natural Science Foundation of China(NSFC,Grant No.11929301)Simons FoundationThoth Technology IncAlexander von Humboldt Foundationthe Niagara supercomputers at the SciNet HPC Consortiumthe Canada Foundation for Innovationthe Government of OntarioOntario Research Fund—Research Excellencethe University of Toronto。
文摘We examine the possibility of applying the baryonic acoustic oscillation reconstruction method to improve the neutrino massΣm_νconstraint.Thanks to the Gaussianization of the process,we demonstrate that the reconstruction algorithm could improve the measurement accuracy by roughly a factor of two.On the other hand,the reconstruction process itself becomes a source of systematic error.While the algorithm is supposed to produce the displacement field from a density distribution,various approximations cause the reconstructed output to deviate on intermediate scales.Nevertheless,it is still possible to benefit from this Gaussianized field,given that we can carefully calibrate the“transfer function”between the reconstruction output and theoretical displacement divergence from simulations.The limitation of this approach is then set by the numerical stability of this transfer function.With an ensemble of simulations,we show that such systematic error could become comparable to statistical uncertainties for a DESI-like survey and be safely neglected for other less ambitious surveys.
