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quant-ph2026
Breaking the Shot-Noise Barrier: Cached Recycled Variance-Reduced Gradients for Quantum Optimization
Lam M. Nguyen, Sumanta Mukherjee, Dzung T. Phan
Variational Quantum Algorithms (VQAs) rely heavily on classical optimization routines to navigate high-dimensional, noisy parameter landscapes. However, the evaluation of analytica…
quant-ph2026
Hamiltonian-Guided Leverage Embedding: Robust Subspace Compression for Efficient QAOA Parameter Estimation
Sumanta Mukherjee, Kalyan Dasgupta, Surya Shravan Kumar Sajja +5
Every Ising energy is a known linear function of measured spin features, yet the standard QAOA estimator discards this structure. We introduce Hamiltonian-Guided Leverage Embedding…
quant-ph2026
Quantum Variational Approaches to the Maximum Independent Set Problem at Utility Scale
Kalyan Dasgupta, Sumanta Mukherjee, Dhriti Verma +4
Near-optimal solutions to Maximum Independent Set on dense graphs sit in local optima that greedy correction and maximality extension cannot escape. We encode near-optimal seeds as…