Coherence Compute - exact on every machine
Run the same math on two different machines and you usually get almost the same answer - floating-point rounds a hair differently on every chip, which is the “it worked on my machine” bug. So we don’t use floating point for the decision. This is a real physical field (a fixed-point reaction-diffusion PDE) computed in exact integer math on your CPU and your GPU at the same time - and the two results come out bit-for-bit identical: same pixels, same SHA-256, zero difference. Then flip one bit and watch the proof catch it.
i32 compute shader on your GPU - hashed with SHA-256 and compared. Integer +, *, and arithmetic-shift >> are defined identically on both, so the result is exact by construction (the same kernel also compiles to WebAssembly, identical). What it is not: a floating-point demo - float is exactly what drifts, and that is the point.A decision you can re-run anywhere and get the same answer is a decision you can sign, audit, and trust. Floating point can’t give you that across machines - the order of operations, fused multiply-adds, and rounding differ per chip. Integer and fixed-point math have no rounding: a*b and a>>n mean the exact same thing on a CPU, in WebAssembly, and on a GPU. That is why every provable decision in the Coherence stack runs on the integer path - this page is the smallest honest proof of it.
Honest scope. This proves the integer path is bit-identical across your CPU and GPU (0 ULP, same hash). Floating-point work agrees only to the single-precision floor - which is exactly why the decisions ride on integers, not floats.
The real thing. This is the same fixed-point kernel and the same WebGPU i32 compute path used in the Coherence Compute engine, where the browser result is verified bit-identical to the native C++ and Python reference implementations, not just to itself. Nothing here is pre-recorded: the field is computed live on your two processors when you press the button.