Preprint
Aug 2026
Bosonic Encodings for Hermite-Galerkin Discretizations of High-Dimensional PDEs and Bayesian Inverse Problems
The Koopman-von Neumann framework is applied to Bayesian inverse problems with Gaussian priors and observation noise, reducing posterior-state preparation to the preparation of a structured Hamiltonian's ground state and introducing a qubit encoding that supports efficient block encodings of the truncated operators.
Alice Barthe
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