arXiv subjects

Evan T. Hockings

Publications and source records attributed to Evan T. Hockings.

4 recordsLinked to original sources

arXiv2026

Scalable quantum error correction tailored for a heavy-hex qubit array

To produce an operable quantum computer that is made with imperfect hardware, we must design and test scalable quantum error correcting codes that are suited for the devices we can build and, in unison, develop decoding strategies that accommodate device-specific noise characteristics. Here, we introduce the \emph{dynamic compass code}, a subsystem code with a novel syndrome extraction cycle, that has a competitive threshold while making efficient use of qubits arranged on a heavy-hex lattice. We use a superconducting qubit array to implement a distance-5 instance of this code, and demonstrate how detailed noise characterisation can boost decoder performance to yield significant improvements in logical error rates. We perform averaged circuit eigenvalue sampling (ACES) to acquire detailed context-dependent error information on all elements of the syndrome extraction process. Furthermore, we leverage soft information produced from measurement devices to augment the decoder with measurement error information and detect leakage errors for exclusion through post-selection. Our noise-informed approach yields up to 38.3\% improvement in the logical error rate of a distance-5 implementation of the dynamic compass code in experiment.

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arXiv2026

The Pinnacle Architecture: Reducing the cost of breaking RSA-2048 to 100 000 physical qubits using quantum LDPC codes

The realisation of utility-scale quantum computing inextricably depends on the design of practical, low-overhead fault-tolerant architectures. We introduce the Pinnacle Architecture, which uses quantum low-density parity check (QLDPC) codes to allow for universal, fault-tolerant quantum computation with a spacetime overhead significantly smaller than that of any competing architecture. With this architecture, we show that 2048-bit RSA integers can be factored with fewer than one hundred thousand physical qubits, given a physical error rate of $10^{-3}$, code cycle time of $1$ microsecond and a reaction time of $10$ microseconds. We thereby demonstrate the feasibility of utility-scale quantum computing with an order of magnitude fewer physical qubits than has previously been believed necessary.

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arXiv2025

Improving error suppression with noise-aware decoding

We demonstrate that the performance of quantum error correction can be improved with noise-aware decoders that are calibrated to the likelihood of physical error configurations in a device. We show that noise-aware decoding increases the error suppression factor of the surface code, yielding reductions in the logical error rate that increase exponentially with the code distance. Our calibration protocol involves circuit-level Pauli noise characterisation experiments with averaged circuit eigenvalue sampling. This enables decoder calibration at the scales required for fault-tolerant quantum computation and near-optimal decoding when compared to the true noise model. Our results indicate that these noise characterisation experiments could be performed and processed in seconds for superconducting quantum computers. This establishes the practicality and utility of noise-aware decoding for quantum error correction at scale.

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arXiv2025

Scalable noise characterization of syndrome-extraction circuits with averaged circuit eigenvalue sampling

Characterising the performance of noisy quantum circuits is central to the production of prototype quantum computers and can enable improved quantum error correction that exploits noise biases identified in a quantum device. We develop a scalable noise characterisation protocol suited to characterising the syndrome extraction circuits of quantum error correcting codes, a key component of fault-tolerant architectures. Our protocol builds upon averaged circuit eigenvalue sampling (ACES), a framework for noise characterisation experiments that simultaneously estimates the Pauli error probabilities of all gates in a Clifford circuit and captures averaged spatial correlations between gates implemented simultaneously in the layers of the circuit. By rigorously analysing the performance of noise characterisation experiments in the ACES framework, we derive a figure of merit for their expected performance, allowing us to optimise their experimental design and improve the precision to which we estimate noise given fixed experimental resources. We demonstrate the scalability and performance of our protocol through circuit-level numerical simulations of the entire noise characterisation procedure for the syndrome extraction circuit of a distance-25 surface code with over 1000 qubits. Our results indicate that detailed noise characterisation methods are scalable to near-term quantum devices. We release our code in the form of the Julia package QuantumACES.

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