Researchers Develop Compact Model to Mitigate Noise Impact on Quantum Technology

Researchers have developed a compact microscopic error model to understand and mitigate the effects of noise in quantum systems. The model only requires a single experimental input and provides a more accurate understanding of noise in quantum systems than previous models. It can be applied to established frameworks such as dynamical decoupling and dynamically-corrected gates, providing more realistic thresholds for quantum error correction. The findings are expected to contribute to developing more efficient and reliable quantum systems.

What is the Impact of Noise on Quantum Technology?

Quantum technology, a field that leverages the principles of quantum mechanics, is known for its potential to revolutionize various sectors, including computing, communication, and sensing. However, one of the significant challenges in this field is noise, which can significantly degrade the performance of quantum systems. Noise is ubiquitous and generally harmful in settings where precision is required, such as quantum technology. The utility of quantum systems typically decays rapidly under the influence of noise.

Understanding the noise in quantum devices is a prerequisite for developing efficient strategies to mitigate or eliminate its harmful effects. However, this understanding requires resources that are often prohibitive. As a result, the typically used noise models rely on simplifications that sometimes depart from experimental reality.

How Can We Model Noise in Quantum Systems?

In a recent study, researchers from the Instituto de Física Teórica UAM-CSIC, Universidad Autónoma de Madrid, Spain, and Universität Innsbruck, Institut für Experimentalphysik, Innsbruck, Austria, have derived a compact microscopic error model for single-qubit gates that only requires a single experimental input – the noise power spectral density.

This model goes beyond standard depolarizing or Pauli-twirled noise models, explicitly including non-Clifford and non-Markovian contributions to the dynamical error map. The researchers gauged their predictions for experimentally relevant metrics against established characterization techniques run on a trapped-ion quantum computer.

What are the Findings of the Study?

The researchers found that experimental estimates of average gate errors, measured through randomized benchmarking and reconstructed via quantum process tomography, are tightly lower-bounded by their analytical forecast. In contrast, the depolarizing model overestimates the gate error.

This noise modeling, including non-Markovian contributions, can be readily applied to established frameworks such as dynamical decoupling and dynamically-corrected gates or to provide more realistic thresholds for quantum error correction.

What is the Significance of this Research?

The development of quantum information processors (QIPs) requires sufficient knowledge about the device and its noise. However, demanding full detail in characterizing all noise sources would make any attempt unpractical. Therefore, there is a large effort within the quantum characterization, verification, and validation (QCVV) community to devise effective and efficient means of determining errors in QIPs and their practical dynamical quantum maps.

This research contributes to this effort by providing a compact microscopic error model for single-qubit gates that only requires a single experimental input. This model can be used to evaluate if the device is below the error threshold of a quantum error correction (QEC) code, which will depend on the specific noise model.

What is the Future Outlook?

The researchers’ work provides a more accurate model for understanding and mitigating the effects of noise in quantum systems. This model can be readily applied to established frameworks such as dynamical decoupling and dynamically-corrected gates or to provide more realistic thresholds for quantum error correction.

The findings of this study are expected to contribute to the development of more efficient and reliable quantum systems. However, further research is needed to validate and refine this model and to explore its potential applications in various quantum technologies.