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A review of barren plateaus in variational quantum computing
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) …
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …
Does provable absence of barren plateaus imply classical simulability? or, why we need to rethink variational quantum computing
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 …
phenomenon. In this perspective article, we face the increasingly loud elephant in the room …
A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits
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 …
through a parametrized quantum circuit, and measuring the expectation value of some …
Showcasing a barren plateau theory beyond the dynamical lie algebra
Barren plateaus have emerged as a pivotal challenge for variational quantum computing.
Our understanding of this phenomenon underwent a transformative shift with the recent …
Our understanding of this phenomenon underwent a transformative shift with the recent …
Trainability barriers and opportunities in quantum generative modeling
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 …
Do quantum circuit born machines generalize?
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 …
performance has been limited to their ability to reproduce a known target distribution. For …
Protocols for trainable and differentiable quantum generative modeling
We propose an approach for learning probability distributions as differentiable quantum
circuits (DQC) that enable efficient quantum generative modeling (QGM) and synthetic data …
circuits (DQC) that enable efficient quantum generative modeling (QGM) and synthetic data …
Orqviz: Visualizing high-dimensional landscapes in variational quantum algorithms
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 …
applications of near to mid-term quantum computers. There has been an increasing effort to …
A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits
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 …
through a parametrized quantum circuit, and measuring the expectation value of some …
Tight and efficient gradient bounds for parameterized quantum circuits
The training of a parameterized model largely depends on the landscape of the underlying
loss function. In particular, vanishing gradients are a central bottleneck in the scalability of …
loss function. In particular, vanishing gradients are a central bottleneck in the scalability of …