Multivariate DQI uses N-variable polynomials for weighted Max-LINSAT, derives closed-form asymptotics for expectation and concentration, provides a single-decoder preparation circuit, and shows outperformance over weighted Prange for some OPI cases while extending to Hamiltonian DQI.
Kernelized decoded quantum interferometry
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Decoded quantum interferometry is generalized to translation association schemes, reducing analysis to tridiagonal eigenvalue problems, with a finite-field matrix rank-difference protocol that produces constant-probability residual-rank bounds but no additive optimality guarantee.
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Multivariate Decoded Quantum Interferometry for Weighted Optimization
Multivariate DQI uses N-variable polynomials for weighted Max-LINSAT, derives closed-form asymptotics for expectation and concentration, provides a single-decoder preparation circuit, and shows outperformance over weighted Prange for some OPI cases while extending to Hamiltonian DQI.