Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
Gpu-accelerated simulations of quantum annealing and the quan- tum approximate optimization algorithm.Com- puter Physics Communications, 278:108411, 2022
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VEQ introduces a compact parametric Grad-Shafranov solver using MXH harmonics and Chebyshev coefficients that maps six input routes to a single variational residual operator and achieves millisecond solves with 10^-3 shape errors on G-EQDSK test cases.
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Feasibility-driven QAOA with penalty scheduling
Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.