Quantum Computing Algorithms for Nonlinear and History-Dependent Solid Mechanics

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $593,598 · view on nsf.gov ↗

Abstract

Quantum computing offers to transform the way engineering computations are performed and promises to allow the engineering community to solve very large and complex mechanics problems that are intractable with classical computers. Using quantum mechanics principles such as superposition and entanglement, quantum computing could lead to both an exponential growth in memory capacity, and algorithmic speed-ups compared to existing “classical” computers. This study looks to devise new quantum computing algorithms for solving mechanics problems that involve rate-dependent, history-dependent and nonlinear materials. Such materials are frequently used in a wide range of applications such as soft robotics, micro-architected structures, and biomedical systems. Increasing predictive modeling and simulation of such important applications is critical to ensuring American competitiveness from commercial and security perspectives. The quantum computing algorithms that look to be devised in this research will be rigorously tested in quantum simulators and real quantum devices to establish the promise and limitations of quantum computing for solving nonlinear mechanics problems. As a part of this study, a computational mechanics community will be established, whose members are collectively committed to advancing quantum computing for mechanics. This community building will be performed in collaboration with existing technical and professional organizations. This study seeks to (1) develo

Key facts

NSF award ID
2527249
Awardee
Vanderbilt University (TN)
SAM.gov UEI
GTNBNWXJ12D5
PI
Caglar Oskay
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
SOLID MECHANICS, MATERIALS DESIGN
Estimated total
$593,598
Funds obligated
$593,598
Transaction type
Standard Grant
Period
09/01/2025 → 08/31/2028