Gap Engineering: A Promising Solution for Quantum Error Correction in Superconducting Qubits

Quantum error correction (QEC) is a vital aspect of quantum computing, but high-energy impact events can cause correlated errors that violate QEC’s key assumptions. Researchers at Google Quantum AI and Yale University have found that gap engineering, which involves creating different superconducting gaps across a qubit’s Josephson junctions, can resist these errors. The team demonstrated that strongly gap engineered qubits maintained their performance during high-energy impact events, while weakly gap engineered qubits showed correlated degradation. This research suggests that scalable quantum computing is achievable with QEC, provided the hardware meets certain conditions.

What is Quantum Error Correction and Why is it Important?

Quantum error correction (QEC) is a crucial aspect of quantum computing that allows for fault-tolerant quantum computing through scaling to large qubit numbers. This is under the assumption that physical errors are sufficiently uncorrelated in time and space. In superconducting qubit arrays, high-energy impact events produce correlated errors, violating this key assumption. Following such an event, phonons with energy above the superconducting gap propagate throughout the device substrate, which in turn generate a temporary surge in quasiparticle (QP) density throughout the array. When these QPs tunnel across the qubits’ Josephson junctions, they induce correlated errors.

One of the key assumptions for the successful implementation of QEC is the absence of any substantial source of correlated error. In superconducting qubit arrays, this assumption is heavily violated by error bursts due to high-energy impacts. During an impact event, high-energy radiation deposits up to 1 MeV in the device substrate, which radiates throughout the device as high-energy phonons. These phonons then break Cooper pairs, producing significantly elevated quasiparticle (QP) densities. These QPs tunnel through the Josephson junction, absorbing the qubit excitation and inducing excess T1 decay. Impacts therefore produce a massive correlated error burst that extends through time and space, which is not correctable using standard QEC.

The presence of these bursts induces an error floor on the logical performance of QEC experiments, preventing the promised exponential suppression of logical error with increasing code size. Without mitigation in hardware, this effect single-handedly prevents scaling QEC to algorithmically relevant logical error rates. Therefore, it is crucial to find ways to resist these high-energy impact events in superconducting qubit arrays.

How Can Gap Engineering Help in Resisting High-Energy Impact Events?

Engineering different superconducting gaps across the qubits’ Josephson junctions provides a method to resist this form of QP tunneling. By fabricating all-aluminum transmon qubits with both strong and weak gap engineering on the same substrate, researchers observed starkly different responses during high-energy impact events. Strongly gap engineered qubits do not show any degradation in T1 during impact events, while weakly gap engineered qubits show events of correlated degradation in T1.

Gap engineering involves producing different superconducting gaps on each side of the junction, which presents an energy barrier to QPs. The superconducting gap in thin films of aluminum is sensitive to thickness, with thinner films displaying higher superconducting gaps. When the gap difference between the thin and thick leads of the Josephson junction is significantly larger than the qubit energy, QPs with energy near the gap can no longer absorb the qubit energy required to climb up the barrier to the higher gap material. This suppresses the primary mechanism by which QPs induce T1 decay.

Based on these results, gap engineering removes the threat of high-energy impacts to QEC in superconducting qubit arrays. This means that scalable and useful quantum computing is achievable through the use of quantum error correction, provided the hardware satisfies key underlying assumptions.

What are the Challenges and Possible Solutions?

While there have been several suggested and implemented strategies for suppressing these effects, none have yet demonstrated total suppression of the error bursts. Moving to a low-radiation underground facility greatly reduces the event rate of impacts, but remaining events such as those due to radioactive materials in the device and packaging remain unmitigated. Using phonon or QP traps reduces both the temporal and spatial extent of the error burst, but QP poisoning is still observed.

Meanwhile, gap engineering has been shown to modify the dynamics of QP tunneling and improve the charge parity lifetimes in superconducting qubits. It has also been shown to improve the speed of recovery from QP poisoning from high-energy impact events. Therefore, gap engineering could be a promising solution to the problem of high-energy impact events in superconducting qubit arrays.

What are the Implications of this Research?

The research conducted by the team at Google Quantum AI and Yale University has significant implications for the field of quantum computing. The team investigated the prevalence of correlated error bursts on a single device with two types of transmon qubits: strongly gap engineered and weakly gap engineered. During impact events, the weakly gap engineered qubits displayed correlated energy relaxation errors. Conversely, no correlated T1 decay errors were observed on the strongly gap engineered qubits during impact events.

Furthermore, the team showed that the strongly gap engineered qubits are robust to significant QP poisoning induced by optical illumination of the chip. This means that strongly gap engineered qubits could potentially be used in practical quantum computing applications, as they are able to resist high-energy impact events and maintain their performance. This research therefore represents a significant step forward in the development of scalable and useful quantum computing.

Conclusion

In conclusion, the research conducted by the team at Google Quantum AI and Yale University has demonstrated that gap engineering can be used to resist high-energy impact events in superconducting qubit arrays. This is a significant finding, as it means that scalable and useful quantum computing is achievable through the use of quantum error correction, provided the hardware satisfies key underlying assumptions. While there are still challenges to be overcome, such as the presence of radioactive materials in the device and packaging, this research represents a promising step forward in the field of quantum computing.