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Protecting Expressive Circuits with a Quantum Error Detection Code
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Protecting Expressive Circuits with a Quantum Error Detection Code
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A successful quantum error correction protocol would allow quantum computers to run algorithms without suffering from the effects of noise. However, fully fault-tolerant quantum error correction is too resource intensive for existing quantum computers. In this context we develop a quantum error detection code for implementations on existing trapped-ion computers. By encoding $k$ logical qubits into $k+2$ physical qubits, this code presents fault-tolerant state initialisation and syndrome measurement circuits that can detect any single-qubit error. It provides a universal set of local and global logical rotations that have physical support on only two qubits. A high-fidelity -- though non fault-tolerant -- compilation of this universal gate set is possible thanks to the two-qubit physical rotations present in trapped-ion computers with all-to-all connectivity. Given the particular structure of the logical operators, we nickname it the Iceberg code. We demonstrate the protection of circuits of 8 logical qubits with up to 256 layers, saturate the logical quantum volume of $2^8$, and show the positive effect of increasing the frequency of syndrome measurements within the circuit. These results illustrate the practical usefulness of the Iceberg code to protect expressive circuits on existing trapped-ion quantum computers.
Forward citations
Cited by 2 Pith papers
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Realizing Error Suppression in Partially Fault-Tolerant Quantum Simulations with IBM Quantum Computers
Partially fault-tolerant [[4,2,2]] Iceberg-code simulations on ibm_boston improve local Ising observables over unencoded baselines by a few percent in 1D and over 200% in 2D at late times via Observable-Ranked Postselection.
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Opportunities and challenges in scaling quantum error detection on hardware
Hardware benchmarks of repetition and triangular color codes for quantum error detection show promise for scaling despite exponential sample costs and embedding overheads.
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