Quantum Stochastic Programming [SWR-26-040]

Maack, Jonathan [National Laboratory of the Rockies (NLR), Golden, CO (United States)]; Reynolds, Matthew [National Laboratory of the Rockies (NLR), Golden, CO (United States)]; Rotello, Caleb [National Laboratory of the Rockies (NLR), Golden, CO (United States)]

doi:10.11578/dc.20260527.2

DOE OSTI · code-181801

Quantum Stochastic Programming [SWR-26-040]

Maack, Jonathan [National Laboratory of the Rockies (NLR), Golden, CO (United States)]·Reynolds, Matthew [National Laboratory of the Rockies (NLR), Golden, CO (United States)]·Rotello, Caleb [National Laboratory of the Rockies (NLR), Golden, CO (United States)]

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Abstract

The Quantum Stochastic Programming tool contains quantum computing algorithms for two-stage stochastic optimization, with a focus on the Unit Commitment (UC) problem in power systems. The algorithms combine Discrete Quantum Annealing (DQA) with Quantum Amplitude Estimation (QAE) to compute expected-value objective functions over a probability distribution of wind-power scenarios. Based on: arXiv 2402.15029 - "Quantum algorithms for the two-stage stochastic unit commitment problem"

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Maack, Jonathan [National Laboratory of the Rockies (NLR), Golden, CO (United States)], Reynolds, Matthew [National Laboratory of the Rockies (NLR), Golden, CO (United States)], Rotello, Caleb [National Laboratory of the Rockies (NLR), Golden, CO (United States)]. 2026-04-22. Quantum Stochastic Programming [SWR-26-040]. https://doi.org/10.11578/dc.20260527.2

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