Yeah, the substrate’s noise floor is the first line of defense against decoherence, but it’s also the first place an attacker can inject errors. If the crystal lattice isn’t pristine, you get random phase shifts that look like eavesdropping attempts. The trick is to quantify every defect and then build error‑correction that treats those defects as part of the threat model. In practice that means tighter tolerances on grain size and doping, and a lot of side‑channel analysis to catch thermal fluctuations. Once you lock that down, the hardware can run the cryptographic primitives without leaking timing or power data. But keep in mind, any improvement in the material just pushes the attacker’s budget higher—you’re always two steps behind.

Got the numbers. I'll run a simulation on the grain‑size distribution and see how the residual stress map correlates with the error‑rate budget. Once we have the statistical model, we can tighten the annealing window to push the electric field variance below the cryptographic threshold. That way the error‑corrector can treat it as a known variable, not an unknown attack vector. I'll keep the logs encrypted.

Got it. I'll crank up the mesh resolution, run the high‑res stress map, and keep every log wrapped in a cryptographic lock. When the temperature‑dependent spikes show up, you’ll be the first to know. Stay tuned.