Data repository for "Grain damping, not particle stiffness, controls velocity weakening in sheared granular layers"

Complete simulation output supporting the manuscript "Grain damping, not particle stiffness, controls velocity weakening in sheared granular layers" (P. Sarma). Two-dimensional discrete element simulations test whether the endogenous-noise friction law of DeGiuli and Wyart (2017) can generate stick-slip in the spring-block granular layer of Aharonov and Sparks (2004). The GranFrixrm code was extended with grain-scale diagnostics measuring the sliding-contact fraction, the acoustic energy and the distribution of distances to the Coulomb cone. Forty XLSX files, each containing an identical self-describing README sheet followed by one data sheet: three steady-state summaries, two analysis tables (flow-law fits, scaling exponents), ten Coulomb-cone distributions (pcone_), and twenty-five time series from imposed-velocity (R1_ts_), damping-sweep (R2_ts_) and spring-driven (R3_ts_) runs. Filenames encode parameters: P10Em3 denotes a confining stress of 1.0e-3, I32Em4 an inertial number of 3.2e-4, and g06 a damping coefficient of 0.6. All quantities are dimensionless. Uncertainties are block-averaged standard errors; sigma/sqrt(N) understates these autocorrelated records roughly threefold. Caveats: one realisation per parameter point, with runs chained so that consecutive rungs are not independent; the friction minimum at damping 0.6 is 2.5 standard errors deep and unreplicated.