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[abridged] We describe LyMAS (Ly-alpha Mass Association Scheme), a method ofpredicting clustering statistics in the Ly-alpha forest on large scales frommoderate resolution simulations of the dark matter distribution, withcalibration from high-resolution hydrodynamic simulations of smaller volumes.We use the "Horizon MareNostrum" simulation, a 50 Mpc/h comoving volume evolvedwith the adaptive mesh hydrodynamic code RAMSES, to compute the conditionalprobability distribution P(F_s|delta_s) of the transmitted flux F_s, smoothed(1-dimensionally) over the spectral resolution scale, on the dark matterdensity contrast delta_s, smoothed (3-dimensionally) over a similar scale. Inthis study we adopt the spectral resolution of the SDSS-III BOSS at z=2.5, andwe find optimal results for a dark matter smoothing length sigma=0.3 Mpc/h(comoving). In extended form, LyMAS exactly reproduces both the 1-dimensionalpower spectrum and 1-point flux distribution of the hydro simulation spectra.Applied to the MareNostrum dark matter field, LyMAS accurately predicts the2-point conditional flux distribution and flux correlation function of the fullhydro simulation for transverse sightline separations as small as 1 Mpc/h,including redshift-space distortion effects. It is substantially more accuratethan a deterministic density-flux mapping ("Fluctuating Gunn-PetersonApproximation"), often used for large volume simulations of the forest. Withthe MareNostrum calibration, we apply LyMAS to 1024^3 N-body simulations of a300 Mpc/h and 1.0 Gpc/h cube to produce large, publicly available catalogs ofmock BOSS spectra that probe a large comoving volume. LyMAS will be a powerfultool for interpreting 3-d Ly-alpha forest data, thereby transformingmeasurements from BOSS and other massive quasar absorption surveys intoconstraints on dark energy, dark matter, space geometry, and IGM physics.

LyMAS: Predicting Large-Scale Lyman-alpha Forest Statistics from the Dark Matter Density Field