Stable Self-Modulating Quantum Fast-Weight Programmers with Bounded Memory Gates

What the math gives to ML

The paper's transferable contribution is a multiplicative fast-memory update whose recurrent branch is explicitly bounded by a sign-preserving hyperbolic-tangent gate. The important property is not the quantum circuit, but the separation between the accumulated state and the newly generated update: only the old-state multiplier is constrained, preventing repeated input-dependent gains from causing exponential growth over long sequences. This can be transplanted into hypernetworks, fast-weight attention, recurrent adapters, or state-space modules by replacing an unconstrained recurrent memory multiplier with a bounded signed gate while leaving the innovation/update path expressive.