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Minh Do

Publications and source records attributed to Minh Do.

Planning for Compilation of a Quantum Algorithm for Graph Coloring

Recently, the problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilation task, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to theMaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOAfor Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we investigate applying the planning approach to qubit initialization as well as routing. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds [20], and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring.These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.

Minh Do↗

Integrating Planning, Diagnosis and Execution for Vehicle Systems Management

We describe a prototype Vehicle System Manager (VSM) for NASA’s Gateway, a human-capable spacecraft that will also be capable of autonomous operations. The VSM consists of an execution system, planner, and fault management system, integrated via an over-arching mission management compo- nent. We describe the VSM architecture and each of its com- ponents. We describe a series of use cases, centered on a spacecraft propulsive operation that can fail at different times, for different reasons, and how the VSM detects and responds to these failures. We show the VSM is capable of detecting faults and loss of capability, and subsequently replanning, in the presence of each failure scenario.

Planning↗