2 papers
quant-ph2026
Learning to Maximize Quantum Neural Network Expressivity via Effective Rank
Juan Yao
Quantum neural networks (QNNs) are widely employed as ansätze for solving variational problems, where their expressivity directly impacts performance. Yet, accurately characterizi…
quant-ph2025
Variational quantum state diagonalization with computational-basis probabilities
Juan Yao
In this report, we propose a novel quantum diagonalization algorithm based on the optimization of variational quantum circuits. Diagonalizing a quantum state is a fundamental yet c…