Despite the great promise of quantum machine learning models, there are several
challenges one must overcome before unlocking their full potential. For instance, models …

Variational quantum computing offers a flexible computational paradigm with applications in
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …

A large amount of effort has recently been put into understanding the barren plateau
phenomenon. In this perspective article, we face the increasingly loud elephant in the room …

Exploiting the power of quantum computation to realize superior machine learning
algorithms has been a major research focus of recent years, but the prospects of quantum …

Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …

A basic primitive in quantum information is the computation of the moments EU [Tr [U ρ U†
O] t]. These describe the distribution of expectation values obtained by sending a state ρ …

Geometric quantum machine learning based on equivariant quantum neural networks
(EQNNs) recently appeared as a promising direction in quantum machine learning. Despite …

Barren plateaus have emerged as a pivotal challenge for variational quantum computing.
Our understanding of this phenomenon underwent a transformative shift with the recent …

Jonas Landman: jonas. landman@ qcware. com we trained on these small-scale datasets
require fewer parameters compared to standard classical benchmarks. While this …

In variational quantum algorithms the parameters of a parameterized quantum circuit are
optimized in order to minimize a cost function that encodes the solution of the problem. The …