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The most promising method for measuring primordial non-Gaussianity in thepost-Planck era is to detect large-scale, scale-dependent galaxy bias.Considering the information in the galaxy power spectrum, we here derive theproperties of a galaxy clustering survey that would optimize constraints onprimordial non-Gaussianity using this technique. Specifically, we ask thequestion what survey design is needed to reach a precision $\sigma(f_{\rmNL}^{\rm loc}) \approx 1$. To answer this question, we calculate thesensitivity to $f_{\rm NL}^{\rm loc}$ as a function of galaxy number density,redshift accuracy and sky coverage. We include the multitracer technique, whichhelps minimize cosmic variance noise, by considering the possibility ofdividing the galaxy sample into stellar mass bins. We show that the idealsurvey for $f_{\rm NL}^{\rm loc}$ looks very different than most galaxyredshift surveys scheduled for the near future. Since those are more or lessoptimized for measuring the BAO scale, they typically require spectroscopicredshifts. On the contrary, to optimize the $f_{\rm NL}^{\rm loc}$ measurement,a deep, wide, multi-band imaging survey is preferred. An uncertainty$\sigma(f_{\rm NL}^{\rm loc}) = 1$ can be reached with a full-sky survey thatis complete to an $i$-band AB magnitude $i \approx 23$ and has a number density$\sim 8$ arcmin$^{-2}$. Requirements on the multi-band photometry are set by amodest photo-$z$ accuracy $\sigma(z)/(1+z) < 0.1$ and the ability to measurestellar mass with a precision $\sim 0.2$ dex or better (or another proxy forhalo mass with equivalent scatter). While here we focus on the information inthe power spectrum, even stronger constraints can potentially be obtained withthe galaxy bispectrum.

Designing an Inflation Galaxy Survey: how to measure $\sigma(f_{\rm NL}) \sim 1$ using scale-dependent galaxy bias