A continuous variable Born machine

Generative Modelling has become a promising use case for near term quantum computers. In particular, due to the fundamentally probabilistic nature of mechanics, computers naturally model and learn probability distributions, perhaps more efficiently than can be achieved classically. The Born machine is an example such model, easily implemented on However, in its original form, only represents discrete distributions. Since distributions continuous are commonplace world, it essential have which represent them. Some proposals been made literature supplement with extra features however, all invariably increase resources required some extent. this work, we present variable machine, built alternative architecture computing, much suitable modelling resource-minimal way. We provide numerical results indicating models ability both classical including presence noise.