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[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 …
Diagnosing barren plateaus with tools from quantum optimal control
M Larocca, P Czarnik, K Sharma, G Muraleedharan… - Quantum, 2022 - quantum-journal.org
Abstract Variational Quantum Algorithms (VQAs) have received considerable attention due
to their potential for achieving near-term quantum advantage. However, more work is …
to their potential for achieving near-term quantum advantage. However, more work is …
Theoretical guarantees for permutation-equivariant quantum neural networks
L Schatzki, M Larocca, QT Nguyen, F Sauvage… - npj Quantum …, 2024 - nature.com
Despite the great promise of quantum machine learning models, there are several
challenges one must overcome before unlocking their full potential. For instance, models …
challenges one must overcome before unlocking their full potential. For instance, models …
Equivalence of quantum barren plateaus to cost concentration and narrow gorges
Optimizing parameterized quantum circuits (PQCs) is the leading approach to make use of
near-term quantum computers. However, very little is known about the cost function …
near-term quantum computers. However, very little is known about the cost function …
Avoiding barren plateaus via transferability of smooth solutions in a Hamiltonian variational ansatz
AA Mele, GB Mbeng, GE Santoro, M Collura, P Torta - Physical Review A, 2022 - APS
A large ongoing research effort focuses on variational quantum algorithms (VQAs),
representing leading candidates to achieve computational speed-ups on current quantum …
representing leading candidates to achieve computational speed-ups on current quantum …
Lie-algebraic classical simulations for variational quantum computing
Classical simulation of quantum dynamics plays an important role in our understanding of
quantum complexity, and in the development of quantum technologies. Compared to other …
quantum complexity, and in the development of quantum technologies. Compared to other …
Trainability barriers and opportunities in quantum generative modeling
MS Rudolph, S Lerch, S Thanasilp, O Kiss… - npj Quantum …, 2024 - nature.com
Quantum generative models provide inherently efficient sampling strategies and thus show
promise for achieving an advantage using quantum hardware. In this work, we investigate …
promise for achieving an advantage using quantum hardware. In this work, we investigate …
Hyperparameter importance and optimization of quantum neural networks across small datasets
C Moussa, YJ Patel, V Dunjko, T Bäck, JN Van Rijn - Machine Learning, 2024 - Springer
As restricted quantum computers become available, research focuses on finding meaningful
applications. For example, in quantum machine learning, a special type of quantum circuit …
applications. For example, in quantum machine learning, a special type of quantum circuit …
Unsupervised strategies for identifying optimal parameters in quantum approximate optimization algorithm
As combinatorial optimization is one of the main quantum computing applications, many
methods based on parameterized quantum circuits are being developed. In general, a set of …
methods based on parameterized quantum circuits are being developed. In general, a set of …
Optimized low-depth quantum circuits for molecular electronic structure using a separable-pair approximation
JS Kottmann, A Aspuru-Guzik - Physical Review A, 2022 - APS
We present a classically tractable model that leads to optimized low-depth quantum circuits
leveraging separable-pair approximations. The obtained circuits are well suited as a …
leveraging separable-pair approximations. The obtained circuits are well suited as a …