Classical and Quantum Algorithms for the Principled Quantification of Infrastructure Safety

This NSF grant will develop novel quantum algorithms to quantify the odds of failure of critical infrastructure systems, such as power grids and water networks, by using and simulating quantum computers. The use of existing quantum devices already extends beyond physics to materials, chemistry, optimization, and machine learning among other fields. However, this grant will create quantum algorithms for a new area of application, namely that of critical infrastructure engineering, which includes power transmission grids, to ultimately support risk‐informed decisions when resources are limited.

As quantifying infrastructure performance is notoriously challenging today due to the increasing complexity of engineered systems, this grant responds to various calls for research and implementation from the National Academy of Engineering and the National Science Foundation, by exploiting the emerging advantages of quantum information processing over classical computing. The execution of this grant is possible through an interdisciplinary team spanning civil and infrastructure engineering, algorithmic logic, algebraic optimization, and quantum physics.

The team’s disciplinary diversity also facilitates broad training, outreach, and dissemination beyond the primary field of infrastructure safety to tangibly advance quantum computing applications as anticipated by the National Quantum Initiative Act signed recently into law. The team will also seed a new workforce of algorithmicists for engineering and science, through funded graduate and undergraduate students, while reaching out to quantum technology enthusiasts, industry professionals, and high school students.

Quantifying critical infrastructure safety, reliability and resilience is essential to inform operations and steer interventions under uncertainty with limited resources. However, most methods to quantify such network metrics rely on numerical simulation and heuristic optimization today. While these approaches do offer insights to infrastructure stakeholders, they are unable to handle, in a principled way, challenging conditions such as rare‐event reliability estimation or optimal restoration decisions for increasingly complex infrastructure systems.

The team addresses these challenges with various novel strategies for infrastructure safety assessment. First, instead of adopting widely used numerical simulation for network reliability estimation, the team focuses on exact methods that count system configurations, as enabled by powerful symbolic logic tensor networks (TNs). These TNs help expand the size frontier of solvable problems while offering quality guarantees.

Second, to leverage relentless progress on quantum hardware, the team will transform TN algorithms into their quantum versions to count reliable network configurations and search for optimal restoration sequences. Third, the team will test algorithms, classical and quantum, relative to best‐performing methods, across different quantum hardware platforms, simulation tools, input resolution levels, and infrastructure topologies, including realistic power transmission grids.

This testing campaign will reveal the settings for quantum circuits that best impact computation time, solution quality and other features that support infrastructure safety assessment.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.