I am a company Ph.D. student at Kvantify in collaboration with the Department of Physics and Astronomy at Aarhus University. At Kvantify we are developing software for quantum computers with companies’ use cases in mind alongside providing high performance computing solutions. At the moment, I am exploring possible use cases for current and near-term optical quantum computing systems such as Gaussian boson samplers.

A Gaussian boson sampler is a type of quantum computing device that is particularly difficult for a classical computer to simulate. At this point, groups around the world have built samplers that are so large that they do tasks that are superior to any classical computer. However, the trouble is that no one has convincingly shown that the tasks that have so far been carried out by boson samplers are useful as anything other than a proof-of-principle that something is hard for a classical computer but not for a quantum device. The quest is now to figure out how to use the capabilities of a boson sampler to do a task that is useful in practice. Graph problems are one of the things that one hopes to be able to solve very difficult instances of using a boson sampler, and in turn this would transform to useful problems within optimization, finance, and they may potentially also be useful to show that a boson sampler would be able to do certain tasks in machine learning better than a classical computer. These are all exciting outlooks on the topic of my Ph.D.