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 …
[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 …
Evidence for the utility of quantum computing before fault tolerance
Quantum computing promises to offer substantial speed-ups over its classical counterpart for
certain problems. However, the greatest impediment to realizing its full potential is noise that …
certain problems. However, the greatest impediment to realizing its full potential is noise that …
Noisy intermediate-scale quantum algorithms
A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …
integer factorization and unstructured database search requires millions of qubits with low …
Quantum error mitigation
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 …
the challenge of noise: the errors that occur in elementary physical components due to …
Generalization in quantum machine learning from few training data
Modern quantum machine learning (QML) methods involve variationally optimizing a
parameterized quantum circuit on a training data set, and subsequently making predictions …
parameterized quantum circuit on a training data set, and subsequently making predictions …
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 …
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Quantum computers can be used to address electronic-structure problems and problems in
materials science and condensed matter physics that can be formulated as interacting …
materials science and condensed matter physics that can be formulated as interacting …
A rigorous and robust quantum speed-up in supervised machine learning
Recently, several quantum machine learning algorithms have been proposed that may offer
quantum speed-ups over their classical counterparts. Most of these algorithms are either …
quantum speed-ups over their classical counterparts. Most of these algorithms are either …
Supervised learning with quantum-enhanced feature spaces
Abstract Machine learning and quantum computing are two technologies that each have the
potential to alter how computation is performed to address previously untenable problems …
potential to alter how computation is performed to address previously untenable problems …