Functional gradient-based geometric curve synthesis for dynamic quantum error suppression

"Harnessing the quantum state of nature holds tremendous potential for creating new quantum technologies that surpass the capabilities of current systems. To create these new technologies, precise control over the quantum state must be maintained while simultaneously suppressing noise processes that would otherwise lead to decoherence and system failure. This project will address the need for efficient algorithms and software tools that produce quantum control waveforms that suppress decoherence and control errors while implementing a universal set of quantum gates for near-term quantum computing. This research and development will enable commercialization of a recently discovered geometric framework for constructing noise-robust quantum control pulses that offers several advantages over current approaches. To facilitate customization and adoption, our gate synthesis algorithms will be implemented in a modern, open-source machine learning software framework. This Phase 1 project will develop, test and benchmark proof-of-concept software for constructing error suppressing quantum gates. Theoretical advancements and extensions of the method to specific quantum devices will be pursued. Open-source, interactive tutorials demonstrating feasibility and error-suppression performance of our algorithms will be developed. There is a nascent market for quantum control, calibration, and characterization software tools for use by quantum hardware vendors to improve the performance of their quantum processors. Phase 2 will broaden the effort to include the experimental validation of our algorithms and the development of industry-grade software tools for quantum characterization and optimal control. The noise-suppressing quantum controls developed in this project will enable longer run times and more accurate results from near-term quantum computers."