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 …
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 …
Dynamical memristors for higher-complexity neuromorphic computing
Research on electronic devices and materials is currently driven by both the slowing down
of transistor scaling and the exponential growth of computing needs, which make present …
of transistor scaling and the exponential growth of computing needs, which make present …
[HTML][HTML] Quantum computing in the NISQ era and beyond
J Preskill - Quantum, 2018 - quantum-journal.org
Abstract Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near
future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass …
future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass …
Multi-qubit entanglement and algorithms on a neutral-atom quantum computer
Gate-model quantum computers promise to solve currently intractable computational
problems if they can be operated at scale with long coherence times and high-fidelity logic …
problems if they can be operated at scale with long coherence times and high-fidelity logic …
Machine learning for molecular and materials science
Here we summarize recent progress in machine learning for the chemical sciences. We
outline machine-learning techniques that are suitable for addressing research questions in …
outline machine-learning techniques that are suitable for addressing research questions in …
[HTML][HTML] A quantum engineer's guide to superconducting qubits
The aim of this review is to provide quantum engineers with an introductory guide to the
central concepts and challenges in the rapidly accelerating field of superconducting …
central concepts and challenges in the rapidly accelerating field of superconducting …
Quantum machine learning
Fuelled by increasing computer power and algorithmic advances, machine learning
techniques have become powerful tools for finding patterns in data. Quantum systems …
techniques have become powerful tools for finding patterns in data. Quantum systems …
Superconducting qubits: Current state of play
Superconducting qubits are leading candidates in the race to build a quantum computer
capable of realizing computations beyond the reach of modern supercomputers. The …
capable of realizing computations beyond the reach of modern supercomputers. The …
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 …