How can neuromorphic computing improve quantum computing? QNC?
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Neuromorphic computing can improve quantum computing by leveraging the inherent system dynamics and running on contemporary, noisy quantum hardware. This subfield, known as Quantum Neuromorphic Computing (QNC), has the potential to realize challenging algorithms in the near term . QNC utilizes the analog dynamics of interacting qubits with tunable coupling constants to create a quantum equivalent of the classical perceptron, which is the building block of various machine learning architectures . By adding tunable single-qubit rotations, a quantum perceptron can achieve universal quantum computation, surpassing the limited computational complexity of a classical perceptron . QNC also benefits from the trainability of variational quantum algorithms (VQAs) and the quantum neural tangent kernel, enabling it to solve various quantum machine learning problems . Overall, QNC combines the advantages of quantum computing and neuromorphic computing to enhance the capabilities of quantum systems .
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| Papers (4) | Insight |
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Open access•Posted Content | The paper proposes that neuromorphic computing can perform quantum operations by connecting spiking neurons to Ising spins. It shows that quantum gates can be learned as a change of parameters for neural network dynamics. |
13 Nov 2022 | The provided paper does not specifically discuss how neuromorphic computing can improve quantum computing. The paper focuses on proposing a quantum equivalent to the classical perceptron and demonstrating its effectiveness in quantum machine learning tasks. |
| The paper does not specifically mention how neuromorphic computing can improve quantum computing. The paper focuses on proposing a quantum equivalent to the classical perceptron and demonstrating its effectiveness in quantum machine learning tasks. | |
73 Citations | The paper does not specifically address how neuromorphic computing can improve quantum computing. The paper focuses on the implementation and advantages of quantum neuromorphic computing using existing and near future intermediate size quantum computers. |
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