Faster cosmological analysis with power spectrum without simulations

$ $FuturesurveyscouldobtaintighterconstraintsonthecosmologicalparameterswiththegalaxypowerspectrumthanwiththeCosmicMicrowaveBackground\mathrm{.}However,theinclusionofmultipleoverlappingtracers,redshiftbins,andmorenon-linearscalesmeansthatgeneratingthenecessaryensembleofsimulationsformodel-fittingpresentsacomputationalburden\mathrm{.}Inthiswork,wecombinefull-shapefittingofgalaxypowerspectra,analyticalcovariancematrixestimates,theMOPED(MassivelyOptimisedParameterEstimationandDatacompression)method,andtheTaylorexpansioninterpolationofthepowerspectrumforthefirsttimetoconstrainthecosmologicalparametersdirectlyfromastate-of-the-artsetofgalaxyclusteringmeasurements\mathrm{.}Wefindittakeslessthanadaytocomputetheanalyticalcovariancewhileittakesseveralmonthstocalculatethesimulatedones\mathrm{.}CombiningMOPEDwiththeTaylorexpansioninterpolationofthepowerspectrum,wecanconstrainthecosmologicalparametersinjustafewhoursinsteadofafewdays\mathrm{.}Wealsofindthatevenwithoutaprioriknowledgeofthebest-fitcosmologicalorgalaxybiasparameters,theanalyticalcovariancematrixwiththeMOPEDcompressionstillgivesconsistentcosmologicalconstraintstowithin0.1$σ$ after two iterations. Therefore, the pipeline we have developed here can significantly speed up the analysis for future surveys such as DESI and Euclid.