We introduce the Quantum Consensus Principle (QCP), a first-principles framework that provides a dynamical derivation of quantum measurement within standard open-system quantum mechanics, without modifying the Schrödinger equation. By treating the system–apparatus–environment complex as an open quantum system, QCP derives measurement outcomes from a thermodynamic selection process governed by large-deviation dynamics. Central to the theory is a calibrated selection potential built from two canonical apparatus statistics, the redundancy rate and the noise susceptibility, defined in Bogoliubov–Kubo–Mori information geometry and linked to microscopic Hamiltonian parameters via Green–Kubo transport coefficients. Within the admissible class specified in the companion Supplement, the effective selector is unique up to affine gauge and takes a linear form in the canonical scores. In the Markovian pointer-preserving regime, the conditioned state process forms a Hellinger-type supermartingale and converges almost surely to unique pointer states. The Born rule is recovered as the exact trajectory-frequency law of the neutral instrument, while non-neutral calibrated instruments generate controlled POVM-level deviations. QCP further predicts a characteristic non-monotonic scaling of collapse timescales, providing a concrete route to experimental falsification. This work bridges quantum information theory and non-equilibrium thermodynamics by identifying measurement as a consensus phenomenon in macroscopic systems. Taken together, the main paper, Supplement, and companion notes establish the full physical and mathematical architecture of QCP.

Unlike approaches that treat measurement primarily at the level of interpretation, QCP advances a unified operational program in which single-outcome selection, neutral-instrument Born recovery, apparatus-dependent deviations, and calibration from microscopic detector physics arise within one framework. Its significance therefore lies not only in proposing a collapse architecture, but in turning foundational claims into quantitative questions about response matrices, transport coefficients, and experimentally testable timescales. In this sense, QCP is designed to move the measurement problem from the level of competing narratives to the level of calibrated dynamical law.

Recommended reading order: Main paper → Supplementary Information → Born note → Necessity note