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Accurate predictions from small boxes: variance suppression via the Zel'dovich approximation

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arxiv 2205.15327 v2 pith:JR75O7YJ submitted 2022-05-30 astro-ph.CO astro-ph.IM

classification astro-ph.COastro-ph.IM
keywords simulationsdovichaccuratecomputedcontroldisplacementsfieldgalaxy
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Simulations have become an indispensable tool for accurate modelling of observables measured in galaxy surveys, but can be expensive if very large dynamic range in scale is required. We describe how to combine Lagrangian perturbation theory models with N-body simulations to reduce the effects of finite computational volume in the prediction of ensemble average properties in the simulations within the context of control variates. In particular we use the fact that Zel'dovich displacements, computed during initial condition generation for any simulation, correlate strongly with the final density field. Since all the correlators of biased tracers can be computed with arbitrary precision for these displacements, pairing the Zel'dovich `simulation' with the N-body realization allows hundredfold reductions in sample variance for power spectrum or correlation function estimation. Zel'dovich control variates can accurately extend matter or tracer field emulators to larger scales than previously possible, as well as improving measurements of statistics in simulations which are inherently limited to small volumes, such as hydrodynamical simulations of galaxy formation and reionization.

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Cited by 2 Pith papers

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  1. The One-Loop Power Spectrum of Fast Radio Burst Dispersion Measures

    astro-ph.CO 2026-08 accept novelty 7.0 of 10

    A one-loop EFT power spectrum model for FRB free-electron clustering matches FLAMINGO simulations to k ~ 0.2 h/Mpc, with electron bias b_e ~ 0.92 and near-perfect electron-matter correlation.

  2. Sample Variance Cancellation for Future Spectroscopic Surveys

    astro-ph.CO 2026-08 conditional novelty 6.0 of 10

    A multi-tracer statistical toolbox can detect, characterize, and constrain angular clustering distortions in LAE surveys using a clean second tracer, within a linear Gaussian framework.

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