PLEASE NOTE: The Budget Justification Workbook / SF-424A template was updated on January 16, 2025. Please use the version labeled June 2024.
The Quantum Computing for Computational Chemistry program (QC3) aims to harness the transformative power of quantum computing to accelerate energy innovation. Computation plays an essential role in modern R&D, but classical computers struggle to simulate quantum systems with the speed, scale, and accuracy necessary to advance many commercial energy applications. This program will support the R&D of scalable, generalizable quantum computing approaches to computational chemistry and materials science. These approaches will be exponentially faster than the classical computing state-of-the-art (SoA), improving speed, accuracy, or problem size by 100 times (100x). This could result in a cumulative energy impact of 1 quadrillion British thermal units (1 quad), which is equal to a reduction of roughly 1 gigaton of carbon dioxide equivalent (CO2e) emissions from energy-related activities.
The QC3 program focuses on developing and applying quantum algorithms in key energy research areas where classical methods are insufficient. This includes the development of quantum chemistry algorithms, their translation into quantum circuits or analog programs, and rigorous validation against classical benchmarks and experiments. The goal is to validate these algorithms on a quantum computer with approximately 100 logical qubits to show scalability and practical advantages over classical computation for energy applications.
Projects under this program must complete the following program objectives:
- Identify a specific problem in chemistry or materials science where a quantum solution, if scalable and generalizable, can lead to cumulative quad-scale energy impact or gigaton-scale reduction in energy-related CO2e emissions.
- Develop solutions which are optimized through the full quantum computational stack (applications, software/algorithms, and hardware). The solution must have a provable ability to scale effectively as quantum hardware improves.
- Have access to and validate on quantum hardware.
- Complete one of the following:
- Achieve a scalable 100x improvement over the classical SoA in speed, accuracy, problem size, or some other relevant capability on the identified energy-relevant problem; or
- Prove scalability using hardware resource estimation and running smaller dimensional problems on available quantum hardware if 100x improvement cannot be realized on the identified energy-relevant problem by the end of the performance period.