Implementing small quantum codes with superconducting qubits

Abhinav Kandala

Hany A. Ali

Current quantum processors are fragile, noisy and fairly limited in both quantity and quality with tens of qubits and physical error rates of around 10^-3. To realize practical quantum applications, however, error rates need to be below 10^-15 across millions of qubits. To bridge this gap and fully harness the potential of quantum computers, quantum error correction (QEC) is essential. QEC codes are designed to protect quantum information by redundantly encoding it onto multiple physical qubits. This encoding allows for the detection and correction of local errors affecting individual qubits, e.g., through stabilizer measurements. Importantly, if the physical error rates are below a specific threshold, QEC codes can exponentially suppress logical error rates by increasing the number of physical qubits involved. This is essential for achieving fault-tolerant computations, which are key to unlocking the full potential of quantum computers. The work presented in this thesis focuses on the implementation and optimization of small-scale QEC experiments using the surface code and flux-tunable superconducting qubits (Transmons). It addresses several key challenges: enhancing two-qubit gate fidelity in Surface-4 (Chapter 2), implementing an error-detection code with Surface-7 (Chapter 3), automating the calibration and benchmarking of the building blocks in Surface-17 (Chapter 4), reducing leakage into higher excited states with leakage reduction units (Chapter 5), assessing and enhancing the performance of logical qubits (Chapters 7 and 8).

Michel Devoret, John M. Martinis

Lopez, Santiago, Jonathan Andrade-Plascencia, Gabriel Perdue

Quantum computers are highly susceptible to errors due to unintended interactions with their environment. It is crucial to correct these errors without gaining information about the quantum state, which would result in its destruction through back-action. Quantum Error Correction (QEC) provides information about occurred errors without compromising the quantum state of the system. However, the implementation of QEC has proven to be challenging due to the current performance levels of qubits -- break-even requires fabrication and operation quality that is beyond the state-of-the-art. Understanding how qubit performance factors into the success of a QEC code is a valuable exercise for tracking progress towards fault-tolerant quantum computing. Here we present qec_code_sim, an open-source, lightweight Python framework for studying the performance of small quantum error correcting codes under the influence of a realistic error model appropriate for superconducting transmon qubits, with the goal of enabling useful hardware studies and experiments. qec_code_sim requires minimal software dependencies and prioritizes ease of use, ease of change, and pedagogy over execution speed. As such, it is a tool well-suited to small teams studying systems on the order of one dozen qubits.

Christian Kraglund Andersen, Eliška Greplová

It is widely accepted that quantum error correction is essential for realizing large-scale fault-tolerant quantum computing. Recent experiments have demonstrated error correction codes operating below threshold, primarily using local planar codes such as the surface code and color code. In parallel, theoretical advances in quantum low-density parity-check (LDPC) codes promise significantly lower overheads, albeit at the cost of requiring non-local parity checks. While these results are encouraging, implementing such codes remains challenging for near-term experiments, creating obstacles to holistic benchmarking of hardware architectures capable of supporting long-range couplers. In this work, we present a simple construction recipe for small quantum LDPC codes based on recent developments in the field. Our codes are approximately twice as efficient as comparable surface codes, yet require only weight-four parity checks, which simplifies experimental realization compared to other quantum LDPC codes. We provide concrete proposals for implementations with superconducting qubits in flip-chip architectures and with semiconductor spin qubits using shuttling-based approaches.

Michel Devoret, John M. Martinis