Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

For quantum computers to successfully solve real-world problems, it is necessary to tackle
the challenge of noise: the errors that occur in elementary physical components due to …

For the first time in history, we are seeing a branching point in computing paradigms with the
emergence of quantum processing units (QPUs). Extracting the full potential of computation …

The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

Quantum technology promises to revolutionize how we learn about the physical world. An
experiment that processes quantum data with a quantum computer could have substantial …

The ability to engineer parallel, programmable operations between desired qubits within a
quantum processor is key for building scalable quantum information systems,. In most state …

Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

Abstract Kernel methods in Quantum Machine Learning (QML) have recently gained
significant attention as a potential candidate for achieving a quantum advantage in data …

Quantum error mitigation has been proposed as a means to combat unwanted and
unavoidable errors in near-term quantum computing without the heavy resource overheads …

Noise in existing quantum processors only enables an approximation to ideal quantum
computation. However, for the computation of expectation values, these approximations can …