Phase II Amount
$1,645,510
C53-06a-271155Harnessing 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 inaccurate results. 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 optimal synthesis algorithms are implemented in open-source, machine learning software framework. In Phase I we developed proof-of-concept software for constructing error suppressing quantum gates. Theoretical advancements and extensions of the method to noise sources affecting specific quantum devices were derived. Open-source, interactive tutorials demonstrating feasibility and error-suppression performance of our algorithms were developed. Phase II will broaden the effort to include experimental partners to validate our R&D efforts and to develop industrial-grade, validated software tools required for creating noise-robust quantum algorithms. There is a nascent market for quantum control, calibration, and error suppression software tools for use by commercial customers seeking to improve the performance of their quantum algorithms and create value from near-term quantum computers. By partnering with leading quantum platform providers, the noise-suppressing quantum controls developed in this project will be available to commercial users and researchers increasing quantum algorithm run-times, decreasing cost, and providing more accurate results from near-term quantum computers.