Optimality conjecture for the natural orthogonal complement in hidden Markov model reduction

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Let cmathcalEcperpcmathcal{E}_cperp be the natural orthogonal-complement effective subspace defined above, and let coverlinepcoverline{\bm p} be the vector defined in Corollary corresponding to cmathcalEcperpcmathcal{E}_cperp. For any other completion cmathcalEcmathcal{E} and any non-negative vector cbmwcbm w, consider the reduced algebras obtained by the operation alg⁡(p‾−1∧E⊥)\operatorname{alg}(\overline{\bm p}^{-1}\wedge\mathcal{E}_\perp) and alg⁡(w−1∧E)\operatorname{alg}(\bm w^{-1}\wedge\mathcal{E}). Optimality conjecture. The natural orthogonal complement gives a reduced model of minimal dimension, namely

dim⁡(E⊥)≤dim⁡(alg⁡(p‾−1∧E⊥))≤dim⁡(alg⁡(w−1∧E)).\dim(\mathcal{E}_\perp)\leq\dim(\operatorname{alg}(\overline{\bm p}^{-1}\wedge\mathcal{E}_\perp))\leq\dim(\operatorname{alg}(\bm w^{-1}\wedge\mathcal{E})).

This conjecture asserts that the natural orthogonal-complement choice is optimal among the possible effective subspaces and non-negative completion vectors, based on the analytical and numerical examples examined in the paper. Its resolution is not supplied in the given text.

References

Primary source

Tommaso Grigoletto and Francesco Ticozzi, “Algebraic Reduction of Hidden Markov Models”, arXiv:2208.05968 (2023).

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