GaussianMove uses the AAA algorithm to generate near-optimal rational approximations offline, then evaluates them on-chain via Horner's method—achieving CDF error of 3.35×10⁻⁹ and PPF error of 3.11×10⁻¹³ with predictable gas costs. Sui's native sui::random then makes Gaussian sampling operationally simple inside a single transaction. This article describes the constraints, the approximation methods, and several applications once these functions are available as ordinary library calls.

GaussianMove uses the AAA algorithm to generate near-optimal rational approximations offline, then evaluates them on-chain via Horner's method—achieving CDF error of 3.35×10⁻⁹ and PPF error of 3.11×10⁻¹³ with predictable gas costs. Sui's native sui::random then makes Gaussian sampling operationally simple inside a single transaction. This article describes the constraints, the approximation methods, and several applications once these functions are available as ordinary library calls.