Superconducting qubits are leading candidates in the race to build a quantum computer
capable of realizing computations beyond the reach of modern supercomputers. The …

In the past 20 years, impressive progress has been made both experimentally and
theoretically in superconducting quantum circuits, which provide a platform for manipulating …

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical
variational algorithm designed to tackle combinatorial optimization problems. Despite its …

A critical question for quantum computing in the near future is whether quantum devices
without error correction can perform a well-defined computational task beyond the …

We report the first electronic structure calculation performed on a quantum computer without
exponentially costly precompilation. We use a programmable array of superconducting …

During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …

Deep belief network (DBN) is one of the most representative deep learning models.
However, it has a disadvantage that the network structure and parameters are basically …

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …

Large arrays of individually controlled atoms trapped in optical tweezers are a very
promising platform for quantum engineering applications. However, deterministic loading of …

Over the last two decades, tremendous advances have been made for constructing large-
scale quantum computers. In particular, quantum computing platforms based on …