Quantum random sampling is the leading proposal for demonstrating a computational
advantage of quantum computers over classical computers. Recently the first large-scale …

Practical challenges in simulating quantum systems on classical computers have been
widely recognized in the quantum physics and quantum chemistry communities over the …

One of the most promising suggested applications of quantum computing is solving
classically intractable chemistry problems. This may help to answer unresolved questions …

In this short review article, we aim to provide physicists not working within the quantum
computing community a hopefully easy-to-read introduction to the state of the art in the field …

The unique features of quantum theory offer a powerful new paradigm for information
processing. Translating these mathematical abstractions into useful algorithms and …

Implementing large instances of quantum algorithms,,,–requires the processing of many
quantum information carriers in a hardware platform that supports the integration of different …

The ability to process optical signals without passing into the electrical domain has always
attracted the attention of the research community. Processing photons by photons unfolds …

The efficient simulation of quantum systems is a primary motivating factor for develo**
controllable quantum machines. For addressing systems with underlying bosonic structure, it …

Gaussian boson sampling (GBS) is a near-term platform for photonic quantum computing.
Recent efforts have led to the discovery of GBS algorithms with applications to graph-based …

Gaussian Boson Samplers are photonic quantum devices with the potential to perform
intractable tasks for classical systems. As with other near-term quantum technologies, an …