Over the last two decades, tremendous advances have been made for constructing large-
scale quantum computers. In particular, quantum computing platforms based on …

Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …

Scaling up to a large number of qubits with high-precision control is essential in the
demonstrations of quantum computational advantage to exponentially outpace the classical …

Quantum error correction is a critical technique for transitioning from noisy intermediate-
scale quantum devices to fully fledged quantum computers. The surface code, which has a …

To ensure a long-term quantum computational advantage, the quantum hardware should be
upgraded to withstand the competition of continuously improved classical algorithms and …

With the rapid advance of quantum machine learning, several proposals for the quantum-
analogue of convolutional neural network (CNN) have emerged. In this work, we benchmark …

Quantum machine learning is expected to be one of the first practical applications of near-
term quantum devices. Pioneer theoretical works suggest that quantum generative …

Quantum machine learning is one of the most promising applications of quantum computing
in the noisy intermediate-scale quantum (NISQ) era. We propose a quantum convolutional …

Distributed training across several quantum computers could significantly improve the
training time and if we could share the learned model, not the data, it could potentially …

Abstract Machine learning algorithms are becoming increasingly resource-intensive. In
contrast to classical computing, quantum computing holds the potential with exponential …