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arXiv:2405.06544 · PRX Quantum

Efficient Distributed Inner-Product Estimation via Pauli Sampling

Marcel Hinsche, Marios Ioannou, Sofiène Jerbi, Lorenzo Leone, Jens Eisert, J. Carrasco

Published Jul 7, 2025• 8 citations
arXivHTMLPDF

Abstract

Cross-platform verification is the task of comparing the output states produced by different physical platforms using solely local quantum operations and classical communication. While protocols have previously been suggested for this task, their exponential sample complexity renders them impractical even for intermediate-scale quantum systems. In this work, we propose a novel protocol for this task based on , a subroutine that generates Paulis distributed according to their weight in the expansion of a quantum state in the Pauli basis. We show that our protocols for both Pauli sampling and cross-platform verification are efficient for pure states with low magic and entanglement [i.e., of the order O ( log  n ) ]. Conversely, we show superpolynomial lower bounds on the complexity of both tasks for states with ω ( log  ( n ) ) magic and entanglement. Interestingly, when considering states with real amplitudes, the requirements of our protocol for cross-platform verification can be significantly weakened.

DOI
10.1103/g53f-z8cr

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Cross-platform verification is the task of comparing the output states produced by different physical platforms using solely local quantum operations and classical communication. While protocols have previously been suggested for this task, their exponential sample complexity renders them impractical even for intermediate-scale quantum systems. In this work, we propose a novel protocol for this task based on , a subroutine that generates Paulis distributed according to their weight in the expansion of a quantum state in the Pauli basis. We show that our protocols for both Pauli sampling and cross-platform verification are efficient for pure states with low magic and entanglement [i.e., of the order O ( log  n ) ]. Conversely, we show superpolynomial lower bounds on the complexity of both tasks for states with ω ( log  ( n ) ) magic and entanglement. Interestingly, when considering states with real amplitudes, the requirements of our protocol for cross-platform verification can be significantly weakened.
As small quantum computers are becoming available on different physical platforms, a benchmarking task known as cross-platform verification has been proposed that aims to estimate the fidelity of states prepared on two quantum computers. This task is fundamentally distributed, as no quantum communication can be performed between the two physical platforms due to hardware constraints, which prohibits a joint SWAP test. In this paper we settle the sample complexity of this task across all measurement and communication settings. The essence of the task, which we call distributed quantum inner product estimation, involves two players Alice and Bob who have k copies of unknown states ρ,σ (acting on ℂd) respectively. Their goal is to estimate Tr(ρσ) up to additive error ε∈(0,1), using local quantum operations and classical communication. In the weakest setting where only non-adaptive single-copy measurements and simultaneous message passing are allowed, we show that k=O(max{1/ε2,√d/ε}) copies suffice. This achieves a savings compared to full tomography which takes Ω(d3) copies with single-copy measurements. Surprisingly, we also show that the sample complexity must be at least Ω(max{1/ε2,√d/ε}), even in the strongest setting where adaptive multi-copy measurements and arbitrary rounds of communication are allowed. This shows that the success achieved by shadow tomography, for sample-efficiently learning the properties of a single system, cannot be generalized to the distributed setting. Furthermore, the fact that the sample complexity remains the same with single and multi-copy measurements contrasts with single system quantum property testing, which often demonstrate exponential separations in sample complexity with single and multi-copy measurements.
We study the sample complexity of the prototypical tasks and . The former has been a key subroutine for experimental benchmarking and entropy estimation, while the latter is a core task for cross-platform validation that compares the unknown quantum states produced by different physical platforms. In purity estimation, we are to estimate tr ( ρ 2 ) of an unknown quantum state ρ to additive error ɛ . Meanwhile, for quantum inner product estimation, Alice and Bob are to estimate tr ( ρ σ ) to additive error ɛ , given copies of the unknown quantum states ρ and σ using classical communication and restricted quantum communication. We propose a protocol that solves quantum inner product estimation with k -qubit quantum communication and unentangled local measurements using O ( median { 1 / ɛ 2 , 2 n / 2 / ɛ , 2 n − k / ɛ 2 } ) copies of ρ and σ . Our protocol can be modified to estimate the purity of an unknown quantum state ρ using k -qubit quantum memory with the same sample complexity. We also prove that arbitrary protocols with k -qubit quantum memory that estimate purity to error ɛ require Ω ( median { 1 / ɛ 2 , 2 n / 2 / ɛ , 2 n − k / ɛ 2 } ) copies of ρ . This indicates the same sample complexity lower bound for quantum inner product estimation with k -qubit quantum communication and classical communication, and unentangled local measurements. We further improve the sample complexity lower bound for any purity estimation protocols using an identical single-copy projection-valued measurement. Last, we investigate a decisional variant of quantum distributed inner product estimation without quantum communication for mixed states and provide a sample complexity lower bound.
In this paper, we introduce a class of highly entangled real quantum states that cannot be approximated by circuits with log -many non-Clifford gates and prove that Bell sampling enables efficient cross-device verification (or distributed inner product estimation) for these states. That is, two remote parties can estimate the inner product tr ( ρ σ ) , each having black-box access to copies of a state ρ (or respectively σ ) in this class. This is significant because it is clear that this task can be achieved in those cases (such as low entanglement or low non-Clifford gate count) where one can independently learn efficient classical descriptions of each state using established techniques and share the description to compute the overlap. Instead, our results demonstrate that this is possible even in more complex scenarios where these “learn and share” methods are insufficient. Our proposal is scalable, as it just requires a number of two-copy Bell measurements and single-copy Pauli measurements that grows polynomially with both the number of qubits and the desired inverse error, and can be implemented in the near term. Moreover, the required number of samples can be efficiently experimentally determined by the parties in advance, and our findings are robust against preparation errors. We anticipate that these results could have applications in quantum cryptography and verification.
Large-scale quantum computers are expected to benefit from modular architectures. Validating the capabilities of modular devices requires benchmarking strategies that assess performance within and between modules. In this work, we evaluate cross-platform verification protocols, which are critical for quantifying how accurately different modules prepare the same quantum state—a key requirement for modular scalability and system-wide consistency. We demonstrate these algorithms using a six-qubit flip-chip superconducting quantum device consisting of two 3-qubit modules on a single carrier chip, with connectivity for intra- and intermodule entanglement. We examine how the resource requirements of protocols relying solely on classical communication between modules scale exponentially with qubit number, and demonstrate that introducing an intermodule two-qubit gate enables subexponential scaling in cross-platform verification. This approach reduces the number of repetitions required by a factor of 4 for three-qubit states, with greater reductions projected for larger and higher-fidelity devices.
Statistical verification of a quantum state aims to certify whether a given unknown state is close to the target state with confidence. So far, sample-optimal verification protocols based on local measurements have been found only for disparate groups of states: bipartite pure states, GHZ states, and antisymmetric basis states. In this work, we investigate systematically optimal verification of entangled stabilizer states using Pauli measurements. First, we provide a lower bound on the sample complexity of any verification protocol based on separable measurements, which is independent of the number of qubits and the specific stabilizer state. Then we propose a simple algorithm for constructing optimal protocols based on Pauli measurements. Our calculations suggest that optimal protocols based on Pauli measurements can saturate the above bound for all entangled stabilizer states, and this claim is verified explicitly for states up to seven qubits. Similar results are derived when each party can choose only two measurement settings, say X and Z. Furthermore, by virtue of the chromatic number, we provide an upper bound for the minimum number of settings required to verify any graph state, which is expected to be tight. For experimentalists, optimal protocols and protocols with the minimum number of settings are explicitly provided for all equivalent classes of stabilizer states up to seven qubits. For theorists, general results on stabilizer states (including graph states in particular) and related structures derived here may be of independent interest beyond quantum state verification.
We study distributed inner product estimation for nnn-qubit states using local randomized measurements, for which rigorous worst-case guarantees are less understood. We first reduce the minimax kernel optimization to Hamming-distance kernels. Within this class, unbiasedness fixes a unique kernel. For this kernel under local Clifford sampling, we prove a sharp fourth-moment bound using the single-qubit Clifford commutant. This yields worst-case sample complexity O(4.5n)\mathcal{O}(\sqrt{4.5^n})O(4.5n​), attained by identical pure product stabilizer states. For the same kernel under local Haar sampling, we prove a local twirling identity that compares its fourth moment with the Clifford fourth moment. This gives the same rigorous upper bound as in the Clifford case, but the comparison is lossy. This motivates the conjectured sharper Haar scaling O(3.6n)\mathcal{O}(\sqrt{3.6^n})O(3.6n​) attained by product states, and verify it for several important classes of states. We also show that independent single-qubit Pauli shadows have worst-case scaling O(7.5n)\mathcal{O}(\sqrt{7.5^n})O(7.5n​) for large nnn.