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quant-ph2026
Accelerating Quantum Tensor Network Simulations with Unified Path Variations and Non-Degenerate Batched Sampling
Taylor Lee Patti, Paavai Pari, Yang Gao +5
Quantum trajectory methods reduce the computational overhead of simulating noisy quantum systems, approximating them with stochastically sampled -entry quantum statevector…
quant-ph2023★ 3 cited
cuQuantum SDK: A High-Performance Library for Accelerating Quantum Science
Harun Bayraktar, Ali Charara, David Clark +19
We present the NVIDIA cuQuantum SDK, a state-of-the-art library of composable primitives for GPU-accelerated quantum circuit simulations. As the size of quantum devices continues t…