177 | Stasyq

Using Markov Chain Monte‑Carlo (MCMC) with Hamiltonian dynamics we update the posterior [ p(\mathbfθ\mid D) \propto p(D\mid\mathbfθ)p(\mathbfθ) ] where D denotes calibration data (RB, GST, and idle‑time tomography).

Energy error for VQE dropped from to 1.7 mHa , well within chemical accuracy (≈ 1 mHa). stasyq 177

| Approach | Noise Model | Mitigation | Typical Fidelity Gain | |----------|-------------|------------|-----------------------| | Zero‑Noise Extrapolation (ZNE) | Implicit (linear) | Post‑processing | 10‑20 % | | Probabilistic Error Cancellation (PEC) | Explicit (Pauli) | Inverse‑noise weighting | 25‑35 % (high sampling cost) | | | Multi‑channel Bayesian | RL‑driven DD + adaptive resampling | 30‑45 % (moderate overhead) | stasyq 177

Every stakeholder—city, citizen, and private sector—has a seat at the table. stasyq 177