Variational quantum computing schemes train a loss function by sending an initial state
through a parametrized quantum circuit, and measuring the expectation value of some …

AFV CoverSheet Page 1 LA-UR-23-30483 Accepted Manuscript A Lie algebraic theory of
barren plateaus for deep parameterized quantum circuits Cerezo de la Roca, Marco Vinicio …

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 …

Quantum generative models provide inherently efficient sampling strategies and thus show
promise for achieving an advantage using quantum hardware. In this work, we investigate …

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

In recent proposals of quantum circuit models for generative tasks, the discussion about their
performance has been limited to their ability to reproduce a known target distribution. For …

We propose an approach for learning probability distributions as differentiable quantum
circuits (DQC) that enable efficient quantum generative modeling (QGM) and synthetic data …

Variational Quantum Algorithms (VQAs) are promising candidates for finding practical
applications of near to mid-term quantum computers. There has been an increasing effort to …

There are two major approaches to building good machine learning algorithms: feeding lots
of data into large models or picking a model class with an “inductive bias” that suits the …