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A review on quantum approximate optimization algorithm and its variants
Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …
variational quantum algorithm that aims to solve combinatorial optimization problems that …
Quantum computing for high-energy physics: State of the art and challenges
Quantum computers offer an intriguing path for a paradigmatic change of computing in the
natural sciences and beyond, with the potential for achieving a so-called quantum …
natural sciences and beyond, with the potential for achieving a so-called quantum …
[HTML][HTML] The variational quantum eigensolver: a review of methods and best practices
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 …
received significant attention from the research community in recent years. It uses the …
Quantum variational algorithms are swamped with traps
One of the most important properties of classical neural networks is how surprisingly
trainable they are, though their training algorithms typically rely on optimizing complicated …
trainable they are, though their training algorithms typically rely on optimizing complicated …
Variational quantum algorithms
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 …
algebra problems are very challenging for classical computers, owing to the extremely high …
The power of quantum neural networks
It is unknown whether near-term quantum computers are advantageous for machine
learning tasks. In this work we address this question by trying to understand how powerful …
learning tasks. In this work we address this question by trying to understand how powerful …
Power of data in quantum machine learning
The use of quantum computing for machine learning is among the most exciting prospective
applications of quantum technologies. However, machine learning tasks where data is …
applications of quantum technologies. However, machine learning tasks where data is …
Connecting ansatz expressibility to gradient magnitudes and barren plateaus
Parametrized quantum circuits serve as ansatze for solving variational problems and
provide a flexible paradigm for the programming of near-term quantum computers. Ideally …
provide a flexible paradigm for the programming of near-term quantum computers. Ideally …
Noise-induced barren plateaus in variational quantum algorithms
Abstract Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on
Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise …
Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise …
Neutral atom quantum computing hardware: performance and end-user perspective
K Wintersperger, F Dommert, T Ehmer… - EPJ Quantum …, 2023 - epjqt.epj.org
We present an industrial end-user perspective on the current state of quantum computing
hardware for one specific technological approach, the neutral atom platform. Our aim is to …
hardware for one specific technological approach, the neutral atom platform. Our aim is to …