Fault-tolerant compiling of classically hard IQP circuits on hypercubes
Abstract
Realizing computationally complex quantum circuits in the presence of noise and imperfections is a challenging task. While fault-tolerant quantum computing provides a route to reducing noise, it requires a large overhead for generic algorithms. Here, we develop and analyze a hardware-efficient, fault-tolerant approach to realizing complex sampling circuits. We co-design the circuits with the appropriate quantum error correcting codes for efficient implementation in a reconfigurable neutral atom array architecture, constituting what we call a fault-tolerant compilation of the sampling algorithm. Specifically, we consider a family of quantum error detecting codes whose transversal and permutation gate set can realize arbitrary degree- instantaneous quantum polynomial (IQP) circuits. Using native operations of the code and the atom array hardware, we compile a fault-tolerant and fast-scrambling family of such IQP circuits in a hypercube geometry, realized recently in the experiments by Bluvstein et al. [Nature 626, 7997 (2024)]. We develop a theory of second-moment properties of degree- IQP circuits for analyzing hardness and verification of random sampling by mapping to a statistical mechanics model. We provide evidence that sampling from hypercube IQP circuits is classically hard to simulate and analyze the linear cross-entropy benchmark (XEB) in comparison to the average fidelity. To realize a fully scalable approach, we first show that Bell sampling from degree- IQP circuits is classically intractable and can be efficiently validated. We further devise new families of color codes of increasing distance , permitting exponential error suppression for transversal IQP sampling. Our results highlight fault-tolerant compiling as a powerful tool in co-designing algorithms with specific error-correcting codes and realistic hardware.
Cite
@article{arxiv.2404.19005,
title = {Fault-tolerant compiling of classically hard IQP circuits on hypercubes},
author = {Dominik Hangleiter and Marcin Kalinowski and Dolev Bluvstein and Madelyn Cain and Nishad Maskara and Xun Gao and Aleksander Kubica and Mikhail D. Lukin and Michael J. Gullans},
journal= {arXiv preprint arXiv:2404.19005},
year = {2025}
}
Comments
28 + 20 pages, 13 Figures, v2: generalized analytical results to degree D, extended discussion