The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

Hybrid quantum–classical systems make it possible to utilize existing quantum computers to
their fullest extent. Within this framework, parameterized quantum circuits can be regarded …

Ground state preparation is classically intractable for general Hamiltonians. On quantum
devices, shallow parametrized circuits can be effectively trained to obtain short-range …

With the increased focus on quantum circuit learning for near-term applications on quantum
devices, in conjunction with unique challenges presented by cost function landscapes of …

Optimizing parameterized quantum circuits (PQCs) is the leading approach to make use of
near-term quantum computers. However, very little is known about the cost function …

The current generation of noisy intermediate-scale quantum computers introduces new
opportunities to study quantum many-body systems. In this paper, we show that quantum …

Variational quantum algorithms are ubiquitous in applications of noisy intermediate-scale
quantum computers. Due to the structure of conventional parametrized quantum gates, the …

Variational quantum algorithms (VQAs) offer a promising path toward using near-term
quantum hardware for applications in academic and industrial research. These algorithms …