Triangle inequality for the distance d₂ on the complex projective space induced by a distance matrix
Prove that for any integer n ≥ 2 and any n × n distance matrix (E_{ij}), the function d₂: P × P → ℝ defined on the complex projective space P by d₂(x, y) = (∑_{i<j} E_{ij}^2 |x_i y_j − x_j y_i|^2)^{1/2} satisfies the triangle inequality; specifically, show that for all pure states x, y, z ∈ P, d₂(x, y) ≤ d₂(x, z) + d₂(z, y).
References
In , we formulated this central challenge as a conjecture. Let $n \geq 2$. For any $n \times n$ distance matrix $(E_{ij})$ the function $d_{2} : P P \to $ defined by eq:old_dist satisfies the triangle inequality. That is, for any pure states $, , \in P$, d_{2}(,) \leq d_{2}(,) + d_{2}(,).
eq:old_dist:
The above reasoning seems to be specific to the quadratic cost in an essential way: the proof of Lemma~\ref{lem:interpolation} uses a Hermitian block matrix, Schur complements, and resolvents of positive operators. It does not by itself settle the corresponding metricity question for other orders $p$ or for general metrics on projective space. Nevertheless, Lemma~\ref{lem:interpolation} suggests a broader strategy for such problems: replace primal gluing by an operator-valued interpolation of Hermitian operators. Whether an analogous result holds beyond the quadratic setting or beyond the underlying Hilbert--Schmidt pure-state distance remains open.