Cutting a quantum circuit into smaller trainable subcircuits allows hybrid quantum-classical neural networks to run on devices with fewer qubits while roughly preserving accuracy.
Demonstration of algorithmic quantum speedup,
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Cutting is All You Need: Execution of Large-Scale Quantum Neural Networks on Limited-Qubit Devices
Cutting a quantum circuit into smaller trainable subcircuits allows hybrid quantum-classical neural networks to run on devices with fewer qubits while roughly preserving accuracy.