A compact neural statebank based on autoregressive Transformers simulates 34-qubit quantum circuits with ~0.01 infidelity using 0.3 million parameters, outperforming tested approximate simulators.
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PIDN replaces repeated multi-noise ZNE evaluations with a trained network that denoises expectation values and gradients from noisy data plus history, achieving comparable optimization on quantum models with 4-6x fewer circuits.
Ground-state energies of homogeneous and random-coupling Ising models are obtained via CVQE with GSA on quantum hardware up to 63 qubits, with error-boundary, entropic, and subspace analyses indicating suitability for near-term devices.
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.
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The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.