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quant-ph2026
Transformers as Intrinsic Optimizers for Quantum Approximate Optimization Algorithm
Kuan-Cheng Chen, Xiaotian Xu, Hiromichi Matsuyama +3
The Quantum Approximate Optimization Algorithm (QAOA) is a leading variational framework for combinatorial optimization on noisy intermediate-scale quantum hardware, but its practi…
quant-ph2026
Quantum hardware noise learning via differentiable Kraus representation on tensor networks
Ryo Sakai, Yu Yamashiro
We present a method for learning quantum hardware noise from a measurement distribution of a single device experiment. Each noise channel is represented by automatically differenti…
quant-ph2026
Recursive QAOA for Interference-Aware Resource Allocation in Wireless Networks
Kuan-Cheng Chen, Hiromichi Matsuyama, Wei-hao Huang +1
Discrete radio resource management problems in dense wireless networks are naturally cast as quadratic unconstrained binary optimization (QUBO) programs but are difficult to solve…