Quantum linear programming offers polynomial speedups over classical methods for computing Young measures in nonlinear PDEs for random cases, but provides no advantage when only expected values are needed.
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Quantum algorithms for Young measures: applications to nonlinear partial differential equations
Quantum linear programming offers polynomial speedups over classical methods for computing Young measures in nonlinear PDEs for random cases, but provides no advantage when only expected values are needed.