Quantum Computing Strategy 2026

Technical Report · Thu Oct 30 04:00:00 EDT 2025

DOI:https://doi.org/10.2172/3000356· OSTI ID:3000356

Hammond, Simon ^[1]; Lang, Michael K. ^[2]; Richards, David ^[3]; Coffrin, Carleton ^[4]; Eidenbenz, Stephan ^[4]; Lowrie, Robert ^[4]; Sornborger, Andrew ^[4]; Rudin, Sven ^[4]; Beck, Kristi ^[5]; DuBois, Jonathan ^[5]; Graziani, Frank ^[5]; Rosen, Yaniv ^[5]; Wendt, Kyle ^[5]; Baczewski, Andrew ^[6]; Descour, Michael ^[6]; Metodi, Tzvetan ^[6]

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1. US Department of Energy (USDOE) National Nuclear Security Administration (NNSA), Washington, DC (United States)
2. US Department of Energy (USDOE) National Nuclear Security Administration (NNSA), Washington, DC (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
3. US Department of Energy (USDOE) National Nuclear Security Administration (NNSA), Washington, DC (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
4. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
5. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
6. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA), Office of Defense Programs (DP)
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 3000356
• Report Number(s): LLNL--TR-2012045
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING