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) …

In the context of measurement-induced entanglement phase transitions, the influence of
quantum noises, which are inherent in real physical systems, is of great importance and …

In this work, drawing inspiration from the type of noise present in real hardware, we study the
output distribution of random quantum circuits under practical nonunital noise sources with …

Large-scale variational quantum algorithms are widely recognized as a potential pathway to
achieve practical quantum advantages. However, the presence of quantum noise might …

Understanding the capabilities of classical simulation methods is key to identifying where
quantum computers are advantageous. Not only does this ensure that quantum computers …

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 …

Quantum noise is one of the most profound obstacles to implementing large-scale quantum
algorithms and schemes. In particular, the dynamical process by which quantum noise …

Classical neural networks with random initialization famously behave as Gaussian
processes in the limit of many neurons, which allows one to completely characterize their …

We present a polynomial-time classical algorithm for estimating expectation values of
arbitrary observables on typical quantum circuits under any incoherent local noise, including …

Variational quantum algorithms (VQAs) hold much promise but face the challenge of
exponentially small gradients. Unmitigated, this barren plateau (BP) phenomenon leads to …