We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization. The algorithm is based on the dynamics of a quantum system moving in an energy potential which encodes the objective function. By approximating the dynamics at finite time steps, the algorithm can be expressed as alternating evolution under…

Gaussian Boson Samplers are photonic quantum devices with the potential to perform tasks that are intractable for classical systems. As with other near-term quantum technologies, an outstanding challenge is to identify specific problems of practical interest where these quantum devices can prove useful. 

Gaussian Boson Samplers are photonic quantum devices with the potential to perform tasks that are intractable for classical systems. As with other near-term quantum technologies, an outstanding challenge is to identify specific problems of practical interest where these quantum devices can prove useful.

We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization. The algorithm is based on the dynamics of a quantum system moving in an energy potential which encodes the objective function.

We demonstrate a system composed of two resonators that are coupled solely through a nonlinear interaction, and where the linear properties of each resonator can be controlled locally.

We present a hybrid linear-optical architecture that simultaneously exploits spatial and temporal degrees of freedom of light to effect arbitrary discrete unitary transformations.

Implementing spatially-encoded universal linear multiport interferometers on integrated photonic platforms with high controllability becomes increasingly difficult as the number of modes increases.

An important application for near-term quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning.

We propose a method for decomposing continuous-variable operations into a universal gate set, without the use of any approximations. We fully characterize a set of transformations admitting exact decompositions and describe a process for obtaining them systematically.

We show that a certain class of complex symmetric matrices has a nonnegative hafnian. These are positive scalar multiples of matrices that are encodable in a Gaussian boson sampler.

The Franck-Condon Factor (FCF) associated to a transition between initial and final vibrational states in two different potential energy surfaces is equivalent to calculating the number of perfect matchings of a weighted graph with loops that has P=N+M vertices.

PennyLane is a Python 3 software framework for optimization and machine learning of quantum and hybrid quantum-classical computations. The library provides a unified architecture for near-term quantum computing devices, supporting both qubit and continuous-variable paradigms.