English

Approximate Unitary $k$-Designs from Shallow, Low-Communication Circuits

Quantum Physics 2026-02-09 v3 Mathematical Physics math.MP

Abstract

Random unitaries are useful in quantum information and related fields, but hard to generate with limited resources. An approximate unitary kk-design is an ensemble of unitaries with an underlying measure over which the average is close to a Haar random ensemble up to the first kk moments. A particularly strong notion of approximation bounds the distance from Haar randomness in relative error. Such relative-error approximate designs are secure against queries by an adaptive adversary trying to distinguish it from a Haar ensemble. We construct relative-error approximate unitary kk-design ensembles for which communication between subsystems is O(1)O(1) in the system size. These constructions use the alternating projection method to analyze overlapping Haar averages, giving a bound on the convergence speed to the full averaging with respect to the 22-norm. Using von Neumann subalgebra indices to replace system dimension, the 2-norm distance converts to relative error without introducing any additional dimension dependence. We use these constructions as the building blocks of a two-step protocol that achieves a relative-error design in O((logm+log(1/ϵ)+klogk)kpolylog(k))O \big ( (\log m + \log(1/\epsilon) + k \log k ) k\, \text{polylog}(k) \big ) depth, where mm is the number of qudits in the complete system and ϵ\epsilon the approximation error. This sublinear depth construction answers a variant of [Harrow and Mehraban 2023, Section 1.5, Open Questions 1 and 7]. Moreover, entanglement generated by the sublinear depth scheme follows area laws on spatial lattices up to corrections logarithmic in the full system size.

Keywords

Cite

@article{arxiv.2407.07876,
  title  = {Approximate Unitary $k$-Designs from Shallow, Low-Communication Circuits},
  author = {Nicholas LaRacuente and Felix Leditzky},
  journal= {arXiv preprint arXiv:2407.07876},
  year   = {2026}
}

Comments

47 pages, 2 figures. v3: Numerous improvements to presentation and streamlined proof of main result. Identical to published version

R2 v1 2026-06-28T17:36:06.499Z