SBIR-STTR Award

Functional Gradient-Based Geometric Curve Synthesis for Dynamic Quantum Error Suppression
Award last edited on: 5/1/2023

Sponsored Program
SBIR
Awarding Agency
DOE
Total Award Amount
$1,901,922
Award Phase
2
Solicitation Topic Code
C53-06a
Principal Investigator
Dennis Lucarelli

Company Information

Error Corp

4405 East-West Highway Suite 410
Bethesda, MD 20814
   (240) 988-9655
   N/A
   N/A
Location: Single
Congr. District: 08
County: Montgomery

Phase I

Contract Number: DE-SC0022389
Start Date: 2/14/2022    Completed: 2/13/2023
Phase I year
2022
Phase I Amount
$256,412
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.

Phase II

Contract Number: DE-SC0022389
Start Date: 4/3/2023    Completed: 4/2/2025
Phase II year
2023
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.