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Optimal Quantum de Finetti Theorems via Argmax Rounding

Quantum Physics 2026-08-03 v1 Computational Complexity

Abstract

We prove optimal finite quantum de Finetti upper bounds. Given a bosonic state ρND(SymN(Cd))\rho_N\in D(\mathrm{Sym}^N(\mathbb C^d)), there is a probability measure ν\nu on the unit sphere such that ρN(2)uu2dν(u)1d1N1. \left\| \rho_N^{(2)}-\int |u\rangle\langle u|^{\otimes 2}\,d\nu(u) \right\|_1 \le \frac{\sqrt{d-1}}{N-1}. By purification, the bosonic theorem also gives the optimal O(d/N)O(d/N) upper bound for arbitrary exchangeable states. These results settle the dimension dependence left open by Christandl, K\"onig, Mitchison, and Renner (CMP 2007). The proof casts de Finetti approximation as sum-of-squares rounding and applies the argmax method of Jeronimo, Wu, and Xu (manuscript 2026). More generally, tt-site marginals satisfy O(td/N)O(t\sqrt d/N) bosonic and O(td/N)O(td/N) permutation-invariant bounds. Our proof formulates de Finetti approximation as the integrality gap of a symmetric-extension semidefinite program and rounds an optimum by the argmax principle. The sharp bounds have several consequences. For every fixed ε(0,1)\varepsilon\in(0,1), we construct a channel with input dimension D=exp(Oε(dlogd))=exp(o(d))D=\exp(O_\varepsilon(\sqrt d\log d))=\exp(o(d)) whose outputs are ε\varepsilon-close to separable states of local dimension dd and whose image contains every such separable state, thereby refuting Watrous's disentangler conjecture. We also obtain deterministic exp(O~(d/ε))\exp(\widetilde O(\sqrt d/\varepsilon))-time algorithms for explicit Best Separable State without perfect completeness and for trace-distance separability testing. Finally, spectral truncation gives the first dimension-free bosonic de Finetti theorem in Hilbert--Schmidt distance, with the optimal rate Θ(N1/2)\Theta(N^{-1/2}) when the dimension may grow.

Cite

@article{arxiv.2608.02590,
  title  = {Optimal Quantum de Finetti Theorems via Argmax Rounding},
  author = {Fernando Granha Jeronimo and Pei Wu and Haochen Xu},
  journal= {arXiv preprint arXiv:2608.02590},
  year   = {2026}
}