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 …
Quantum algorithms for quantum chemistry and quantum materials science
As we begin to reach the limits of classical computing, quantum computing has emerged as
a technology that has captured the imagination of the scientific world. While for many years …
a technology that has captured the imagination of the scientific world. While for many years …
Quantum convolutional neural networks
Neural network-based machine learning has recently proven successful for many complex
applications ranging from image recognition to precision medicine. However, its direct …
applications ranging from image recognition to precision medicine. However, its direct …
Limitations of optimization algorithms on noisy quantum devices
D Stilck França, R Garcia-Patron - Nature Physics, 2021 - nature.com
Recent successes in producing intermediate-scale quantum devices have focused interest
on establishing whether near-term devices could outperform classical computers for …
on establishing whether near-term devices could outperform classical computers for …
[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 …
Generalized unitary coupled cluster wave functions for quantum computation
We introduce a unitary coupled-cluster (UCC) ansatz termed k-UpCCGSD that is based on a
family of sparse generalized doubles operators, which provides an affordable and …
family of sparse generalized doubles operators, which provides an affordable and …
Towards quantum machine learning with tensor networks
Abstract Machine learning is a promising application of quantum computing, but challenges
remain for implementation today because near-term devices have a limited number of …
remain for implementation today because near-term devices have a limited number of …
Performance of the quantum approximate optimization algorithm on the maximum cut problem
GE Crooks - arXiv preprint arXiv:1811.08419, 2018 - arxiv.org
The Quantum Approximate Optimization Algorithm (QAOA) is a promising approach for
programming a near-term gate-based hybrid quantum computer to find good approximate …
programming a near-term gate-based hybrid quantum computer to find good approximate …
Hardware-efficient variational quantum algorithms for time evolution
Parameterized quantum circuits are a promising technology for achieving a quantum
advantage. An important application is the variational simulation of time evolution of …
advantage. An important application is the variational simulation of time evolution of …