Quantum variational algorithms are swamped with traps
ER Anschuetz, BT Kiani - Nature Communications, 2022 - nature.com
One of the most important properties of classical neural networks is how surprisingly
trainable they are, though their training algorithms typically rely on optimizing complicated …
trainable they are, though their training algorithms typically rely on optimizing complicated …
Quantum computing with and for many-body physics
Quantum computing technologies are making steady progress. This has opened new
opportunities for tackling problems whose complexity prevents their description on classical …
opportunities for tackling problems whose complexity prevents their description on classical …
Theory of overparametrization in quantum neural networks
The prospect of achieving quantum advantage with quantum neural networks (QNNs) is
exciting. Understanding how QNN properties (for example, the number of parameters M) …
exciting. Understanding how QNN properties (for example, the number of parameters M) …
Quantum computing in power systems
Electric power systems provide the backbone of modern industrial societies. Enabling
scalable grid analytics is the keystone to successfully operating large transmission and …
scalable grid analytics is the keystone to successfully operating large transmission and …
Understanding quantum machine learning also requires rethinking generalization
Quantum machine learning models have shown successful generalization performance
even when trained with few data. In this work, through systematic randomization …
even when trained with few data. In this work, through systematic randomization …
Absence of barren plateaus in finite local-depth circuits with long-range entanglement
Ground state preparation is classically intractable for general Hamiltonians. On quantum
devices, shallow parametrized circuits can be effectively trained to obtain short-range …
devices, shallow parametrized circuits can be effectively trained to obtain short-range …
TETRIS-ADAPT-VQE: An adaptive algorithm that yields shallower, denser circuit Ansätze
Adaptive quantum variational algorithms are particularly promising for simulating strongly
correlated systems on near-term quantum hardware, but they are not yet viable due, in large …
correlated systems on near-term quantum hardware, but they are not yet viable due, in large …
A practitioner's guide to quantum algorithms for optimisation problems
BCB Symons, D Galvin, E Sahin… - Journal of Physics A …, 2023 - iopscience.iop.org
Quantum computing is gaining popularity across a wide range of scientific disciplines due to
its potential to solve long-standing computational problems that are considered intractable …
its potential to solve long-standing computational problems that are considered intractable …
Optimizing quantum circuits with Riemannian gradient flow
R Wiersema, N Killoran - Physical Review A, 2023 - APS
Variational quantum algorithms are a promising class of algorithms that can be performed
on currently available quantum computers. In most settings, the free parameters of a …
on currently available quantum computers. In most settings, the free parameters of a …
Classification of dynamical Lie algebras for translation-invariant 2-local spin systems in one dimension
Much is understood about 1-dimensional spin chains in terms of entanglement properties,
physical phases, and integrability. However, the Lie algebraic properties of the Hamiltonians …
physical phases, and integrability. However, the Lie algebraic properties of the Hamiltonians …