QUANT-PHLGMay 16, 2024

Architectures and random properties of symplectic quantum circuits

arXiv:2405.10264v212 citationsh-index: 8Quantum Science and Technology
Originality Incremental advance
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This work addresses a gap in quantum information theory by studying symplectic transformations, which could impact quantum computing and simulation, though it appears incremental as it builds on known tools for unitary and orthogonal circuits.

The paper tackles the overlooked problem of symplectic quantum circuits by presenting a universal generator set for the symplectic algebra and analyzing random properties, proving that Pauli measurements converge to Gaussian processes and showing computational-basis measurements anti-concentrate at logarithmic depth in shallow circuits.

Parametrized and random unitary (or orthogonal) $n$-qubit circuits play a central role in quantum information. As such, one could naturally assume that circuits implementing symplectic transformations would attract similar attention. However, this is not the case, as $\mathbb{SP} d/2)$ -- the group of $d\times d$ unitary symplectic matrices -- has thus far been overlooked. In this work, we aim at starting to fill this gap. We begin by presenting a universal set of generators $\mathcal{G}$ for the symplectic algebra $\mathfrak{sp}(d/2)$, consisting of one- and two-qubit Pauli operators acting on neighboring sites in a one-dimensional lattice. Here, we uncover two critical differences between such set, and equivalent ones for unitary and orthogonal circuits. Namely, we find that the operators in $\mathcal{G}$ cannot generate arbitrary local symplectic unitaries and that they are not translationally invariant. We then review the Schur-Weyl duality between the symplectic group and the Brauer algebra, and use tools from Weingarten calculus to prove that Pauli measurements at the output of Haar random symplectic circuits can converge to Gaussian processes. As a by-product, such analysis provides us with concentration bounds for Pauli measurements in circuits that form $t$-designs over $\mathbb{SP}(d/2)$. To finish, we present tensor-network tools to analyze shallow random symplectic circuits, and we use these to numerically show that computational-basis measurements anti-concentrate at logarithmic depth.

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