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quant-ph2024
Improving the trainability of VQE on NISQ computers for solving portfolio optimization using convex interpolation
Shengbin Wang, Guihui Li, Zhimin Wang +5
Solving combinatorial optimization problems using variational quantum algorithms (VQAs) might be a promise application in the NISQ era. However, the limited trainability of VQAs co…
quant-ph2024
Variational quantum eigensolver with linear depth problem-inspired ansatz for solving portfolio optimization in finance
Shengbin Wang, Peng Wang, Guihui Li +8
Great efforts have been dedicated in recent years to explore practical applications for noisy intermediate-scale quantum (NISQ) computers, which is a fundamental and challenging pr…