Stronger Welch Bounds and Optimal Approximate $k$-Designs
- URL: http://arxiv.org/abs/2602.13099v1
- Date: Fri, 13 Feb 2026 17:05:26 GMT
- Title: Stronger Welch Bounds and Optimal Approximate $k$-Designs
- Authors: Riccardo Castellano, Dmitry Grinko, Sadra Boreiri, Nicolas Brunner, Jef Pauwels,
- Abstract summary: A fundamental question asks how uniformly finite sets of pure quantum states can be distributed in a Hilbert space.<n>Welch bounds address this question, and are saturated by $k$-designs, i.e. sets of states reproducing the $k$-th Haar moments.<n>We derive strengthened Welch-type inequalities that remain sharp in this regime by exploiting rank constraints from partial transposition and spectral properties of the partially transposed Haar moment operator.
- Score: 0.13048920509133805
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A fundamental question asks how uniformly finite sets of pure quantum states can be distributed in a Hilbert space. The Welch bounds address this question, and are saturated by $k$-designs, i.e. sets of states reproducing the $k$-th Haar moments. However, these bounds quickly become uninformative when the number of states is below that required for an exact $k$-design. We derive strengthened Welch-type inequalities that remain sharp in this regime by exploiting rank constraints from partial transposition and spectral properties of the partially transposed Haar moment operator. We prove that the deviation from the Welch bound captures the average-case approximation error, hence characterizing a natural notion of minimum achievable error at fixed cardinality. For $k=3$, we prove that SICs and complete MUB sets saturate our bounds, making them optimal approximate 3-designs of their cardinality. This leads a natural variational criterion to rule out the existence of a complete set MUBs, which we use to obtain numerical evidence against such set in dimension $6$. As a key technical ingredient, we compute the complete spectrum of the partially transposed symmetric-subspace projector, including multiplicities and eigenvectors, which may find applications beyond the present work.
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