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Dual-unitary shadow tomography

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arxiv 2404.01068 v4 pith:RRTFUHOX submitted 2024-04-01 quant-ph cond-mat.dis-nncond-mat.stat-mechmath-phmath.MP

classification quant-phcond-mat.dis-nncond-mat.stat-mechmath-phmath.MP
keywords dual-unitaryweightbrick-walldustpaulishadowtomographycircuits
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We introduce ``dual-unitary shadow tomography'' (DUST), a classical shadow tomography protocol based on dual-unitary brick-wall circuits. To quantify the performance of DUST, we study operator spreading and Pauli weight dynamics in one-dimensional qubit systems, evolved by random two-local dual-unitary gates arranged in a brick-wall structure, ending with a measurement layer. We do this by deriving general constraints on the Pauli weight transfer matrix and specializing to the case of dual-unitarity. Remarkably, we find that operator spreading in these circuits have a rich structure resembling that of relativistic quantum field theories, with massless chiral excitations that can decay or fuse into each other, which we call left- or right-movers. We develop a mean-field description of the Pauli weight in terms of $\rho(x,t)$, which represents the probability of having nontrivial support at site $x$ and depth $t$ starting from a fixed weight distribution. We develop an equation of state for $\rho(x,t)$ and simulate it numerically using Monte Carlo simulations. For the task of predicting operators with (nearly) full support, we show that DUST outperforms brick-wall Clifford shadows of equal depth. This advantage is further pronounced for small system sizes and our results are generally robust to finite-size effects.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Contractive Unitary and Classical Shadow Tomography

    quant-ph 2024-11 conditional novelty 8.0 of 10

    Using an all-to-all product of ZZ gates as a deterministic global unitary, classical shadow tomography achieves ~1.8^k sample complexity for dense k-local Pauli strings.

  2. Classical Shadows with Improved Median-of-Means Estimation

    quant-ph 2024-12 conditional novelty 5.0 of 10

    Applying Minsker's tighter median-of-means estimator with incomplete U-statistics to classical shadows improves sample efficiency for Clifford measurements but not for Pauli measurements.

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