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 …
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 …
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 …
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 …
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 …
Cost function dependent barren plateaus in shallow parametrized quantum circuits
Variational quantum algorithms (VQAs) optimize the parameters θ of a parametrized
quantum circuit V (θ) to minimize a cost function C. While VQAs may enable practical …
quantum circuit V (θ) to minimize a cost function C. While VQAs may enable practical …
Hybrid quantum-classical algorithms and quantum error mitigation
Quantum computers can exploit a Hilbert space whose dimension increases exponentially
with the number of qubits. In experiment, quantum supremacy has recently been achieved …
with the number of qubits. In experiment, quantum supremacy has recently been achieved …
Parameterized quantum circuits as machine learning models
Hybrid quantum–classical systems make it possible to utilize existing quantum computers to
their fullest extent. Within this framework, parameterized quantum circuits can be regarded …
their fullest extent. Within this framework, parameterized quantum circuits can be regarded …
Absence of barren plateaus in quantum convolutional neural networks
Quantum neural networks (QNNs) have generated excitement around the possibility of
efficiently analyzing quantum data. But this excitement has been tempered by the existence …
efficiently analyzing quantum data. But this excitement has been tempered by the existence …