The Quantum Leap: How Machine Learning is Pushing the Boundaries of Quantum Computing

Published on:

5 October 2023

Primary Category:

Quantum Physics

Paper Authors:

Debasmita Bhoumik,

Susmita Sur-Kolay,

Latesh Kumar K. J.,

Sundaraja Sitharama Iyengar

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Key Details

Classical ML improves design and error correction of quantum circuits and algorithms

Quantum computers can run some ML models exponentially faster due to superposition

Hybrid quantum-classical algorithms show promise for near-term noisy devices

Research is ongoing into quantum neural networks, support vector machines, and more

Quantum communication and cryptography protocols benefit from ML techniques

AI generated summary

The Quantum Leap: How Machine Learning is Pushing the Boundaries of Quantum Computing

This paper provides a comprehensive overview of the synergies between machine learning and quantum computing. It summarizes key developments in applying classical machine learning techniques to improve quantum algorithms, building quantum machine learning models, and leveraging quantum properties for enhanced machine learning. The review touches on major applications like quantum chemistry, optimization, and cryptography while highlighting challenges and opportunities.

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